API experiment part2 + ugly frontend

* FFmpeg with progress bar

* Fix typing

* FFmpeg with progress bar part2

* Restore streaming wording

.github/workflows/ci.yml

@@ -8,10 +8,10 @@ jobs:
   steps:
   - name: Checkout
     uses: actions/checkout@v4
-  - name: Set up Python 3.10
+  - name: Set up Python 3.12
     uses: actions/setup-python@v5
     with:
-     python-version: '3.10'
+     python-version: '3.12'
   - run: pip install flake8
   - run: pip install flake8-import-order
   - run: pip install mypy
@@ -22,17 +22,17 @@ jobs:
  test:
   strategy:
    matrix:
-    os: [ macos-13, ubuntu-latest, windows-latest ]
+    os: [ macos-latest, ubuntu-latest, windows-latest ]
   runs-on: ${{ matrix.os }}
   steps:
   - name: Checkout
     uses: actions/checkout@v4
   - name: Set up FFmpeg
-    uses: FedericoCarboni/setup-ffmpeg@v3
-  - name: Set up Python 3.10
+    uses: AnimMouse/setup-ffmpeg@v1
+  - name: Set up Python 3.12
     uses: actions/setup-python@v5
     with:
-     python-version: '3.10'
+     python-version: '3.12'
   - run: python install.py --onnxruntime default --skip-conda
   - run: pip install pytest
   - run: pytest
@@ -44,10 +44,10 @@ jobs:
     uses: actions/checkout@v4
   - name: Set up FFmpeg
     uses: FedericoCarboni/setup-ffmpeg@v3
-  - name: Set up Python 3.10
+  - name: Set up Python 3.12
     uses: actions/setup-python@v5
     with:
-     python-version: '3.10'
+     python-version: '3.12'
   - run: python install.py --onnxruntime default --skip-conda
   - run: pip install coveralls
   - run: pip install pytest

.gitignore

@@ -1,3 +1,4 @@
+__pycache__
 .assets
 .caches
 .jobs

README.md

@@ -35,6 +35,7 @@ options:
 commands:
     run                                           run the program
     headless-run                                  run the program in headless mode
+    batch-run                                     run the program in batch mode
     force-download                                force automate downloads and exit
     job-list                                      list jobs by status
     job-create                                    create a drafted job

facefusion.ini

@@ -1,9 +1,15 @@
 [paths]
+temp_path =
 jobs_path =
 source_paths =
 target_path =
 output_path =
 
+[patterns]
+source_pattern =
+target_pattern =
+output_pattern =
+
 [face_detector]
 face_detector_model =
 face_detector_size =
@@ -52,6 +58,8 @@ skip_audio =
 processors =
 age_modifier_model =
 age_modifier_direction =
+deep_swapper_model =
+deep_swapper_morph =
 expression_restorer_model =
 expression_restorer_factor =
 face_debugger_items =
@@ -72,6 +80,7 @@ face_editor_head_yaw =
 face_editor_head_roll =
 face_enhancer_model =
 face_enhancer_blend =
+face_enhancer_weight =
 face_swapper_model =
 face_swapper_pixel_boost =
 frame_colorizer_model =
@@ -92,10 +101,13 @@ execution_providers =
 execution_thread_count =
 execution_queue_count =
 
+[download]
+download_providers =
+download_scope =
+
 [memory]
 video_memory_strategy =
 system_memory_limit =
 
 [misc]
-skip_download =
 log_level =

facefusion/_preview.py

@@ -0,0 +1,72 @@
+from typing import Optional
+
+import cv2
+import numpy
+
+from facefusion import core, state_manager
+from facefusion.audio import create_empty_audio_frame, get_audio_frame
+from facefusion.common_helper import get_first
+from facefusion.content_analyser import analyse_frame
+from facefusion.face_analyser import get_average_face, get_many_faces
+from facefusion.face_selector import sort_faces_by_order
+from facefusion.face_store import get_reference_faces
+from facefusion.filesystem import filter_audio_paths, is_image, is_video
+from facefusion.processors.core import get_processors_modules
+from facefusion.typing import AudioFrame, Face, FaceSet, VisionFrame
+from facefusion.vision import get_video_frame, read_static_image, read_static_images, resize_frame_resolution
+
+
+def process_frame(frame_number : int = 0) -> Optional[VisionFrame]:
+	core.conditional_append_reference_faces()
+	reference_faces = get_reference_faces() if 'reference' in state_manager.get_item('face_selector_mode') else None
+	source_frames = read_static_images(state_manager.get_item('source_paths'))
+	source_faces = []
+
+	for source_frame in source_frames:
+		temp_faces = get_many_faces([ source_frame ])
+		temp_faces = sort_faces_by_order(temp_faces, 'large-small')
+		if temp_faces:
+			source_faces.append(get_first(temp_faces))
+	source_face = get_average_face(source_faces)
+	source_audio_path = get_first(filter_audio_paths(state_manager.get_item('source_paths')))
+	source_audio_frame = create_empty_audio_frame()
+
+	if source_audio_path and state_manager.get_item('output_video_fps') and state_manager.get_item('reference_frame_number'):
+		reference_audio_frame_number = state_manager.get_item('reference_frame_number')
+		if state_manager.get_item('trim_frame_start'):
+			reference_audio_frame_number -= state_manager.get_item('trim_frame_start')
+		temp_audio_frame = get_audio_frame(source_audio_path, state_manager.get_item('output_video_fps'), reference_audio_frame_number)
+		if numpy.any(temp_audio_frame):
+			source_audio_frame = temp_audio_frame
+
+	if is_image(state_manager.get_item('target_path')):
+		target_vision_frame = read_static_image(state_manager.get_item('target_path'))
+		preview_vision_frame = process_preview_frame(reference_faces, source_face, source_audio_frame, target_vision_frame)
+		return preview_vision_frame
+
+	if is_video(state_manager.get_item('target_path')):
+		temp_vision_frame = get_video_frame(state_manager.get_item('target_path'), frame_number)
+		preview_vision_frame = process_preview_frame(reference_faces, source_face, source_audio_frame, temp_vision_frame)
+		return preview_vision_frame
+
+	return None
+
+
+def process_preview_frame(reference_faces : FaceSet, source_face : Face, source_audio_frame : AudioFrame, target_vision_frame : VisionFrame) -> VisionFrame:
+	target_vision_frame = resize_frame_resolution(target_vision_frame, (1024, 1024))
+	source_vision_frame = target_vision_frame.copy()
+
+	if analyse_frame(target_vision_frame):
+		return cv2.GaussianBlur(target_vision_frame, (99, 99), 0)
+
+	for processor_module in get_processors_modules(state_manager.get_item('processors')):
+		if processor_module.pre_process('preview'):
+			target_vision_frame = processor_module.process_frame(
+			{
+				'reference_faces': reference_faces,
+				'source_face': source_face,
+				'source_audio_frame': source_audio_frame,
+				'source_vision_frame': source_vision_frame,
+				'target_vision_frame': target_vision_frame
+			})
+	return target_vision_frame

facefusion/api.py

@@ -0,0 +1,121 @@
+import asyncio
+import json
+from typing import Any, List
+
+import cv2
+import uvicorn
+from litestar import Litestar, WebSocket, get as read, websocket as stream, websocket_listener
+from litestar.static_files import create_static_files_router
+
+from facefusion import _preview, choices, execution, state_manager, vision
+from facefusion.processors import choices as processors_choices
+from facefusion.state_manager import get_state
+from facefusion.typing import ExecutionDevice
+
+
+@read('/choices')
+async def read_choices() -> Any:
+	__choices__ = {}
+
+	for key in dir(choices):
+		if not key.startswith('__'):
+			value = getattr(choices, key)
+
+			if isinstance(value, (dict, list)):
+				__choices__[key] = value
+
+	return __choices__
+
+
+@read('/processors/choices')
+async def read_processors_choices() -> Any:
+	__processors_choices__ = {}
+
+	for key in dir(processors_choices):
+		if not key.startswith('__'):
+			value = getattr(processors_choices, key)
+
+			if isinstance(value, (dict, list)):
+				__processors_choices__[key] = value
+
+	return __processors_choices__
+
+
+@read('/execution/providers')
+async def read_execution_providers() -> Any:
+	return execution.get_execution_provider_set()
+
+
+@stream('/execution/devices')
+async def stream_execution_devices(socket : WebSocket[Any, Any, Any]) -> None:
+	await socket.accept()
+
+	while True:
+		await socket.send_json(execution.detect_execution_devices())
+		await asyncio.sleep(0.5)
+
+
+@read('/execution/devices')
+async def read_execution_devices() -> List[ExecutionDevice]:
+	return execution.detect_execution_devices()
+
+
+@read('/static_execution/devices')
+async def read_static_execution_devices() -> List[ExecutionDevice]:
+	return execution.detect_static_execution_devices()
+
+
+@stream('/state')
+async def stream_state(socket : WebSocket[Any, Any, Any]) -> None:
+	await socket.accept()
+
+	while True:
+		await socket.send_json(get_state())
+		await asyncio.sleep(0.5)
+
+
+@read('/preview', media_type = 'image/png', mode = "binary")
+async def read_preview(frame_number : int) -> bytes:
+	_, preview_vision_frame = cv2.imencode('.png', _preview.process_frame(frame_number)) #type:ignore
+	return preview_vision_frame.tobytes()
+
+
+@websocket_listener("/preview", send_mode = "binary")
+async def stream_preview(data : str) -> bytes:
+	frame_number = int(json.loads(data).get('frame_number'))
+	_, preview_vision_frame = cv2.imencode('.png', _preview.process_frame(frame_number)) #type:ignore
+	return preview_vision_frame.tobytes()
+
+
+@read('/ui/preview_slider')
+async def read_ui_preview_slider() -> Any:
+	target_path = state_manager.get_item('target_path')
+	video_frame_total = vision.count_video_frame_total(target_path)
+
+	return\
+	{
+		'video_frame_total': video_frame_total
+	}
+
+
+api = Litestar(
+[
+	read_choices,
+	read_processors_choices,
+	stream_execution_devices,
+	read_execution_devices,
+	read_static_execution_devices,
+	stream_state,
+	read_preview,
+	read_ui_preview_slider,
+	stream_preview,
+	create_static_files_router(
+		path = '/frontend',
+		directories = [ 'facefusion/static' ],
+		html_mode = True,
+    )
+])
+
+
+def run() -> None:
+	uvicorn.run(api)

facefusion/args.py

@@ -15,6 +15,14 @@ def reduce_step_args(args : Args) -> Args:
 	return step_args
 
 
+def reduce_job_args(args : Args) -> Args:
+	job_args =\
+	{
+		key: args[key] for key in args if key in job_store.get_job_keys()
+	}
+	return job_args
+
+
 def collect_step_args() -> Args:
 	step_args =\
 	{
@@ -35,10 +43,15 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
 	# general
 	apply_state_item('command', args.get('command'))
 	# paths
+	apply_state_item('temp_path', args.get('temp_path'))
 	apply_state_item('jobs_path', args.get('jobs_path'))
 	apply_state_item('source_paths', args.get('source_paths'))
 	apply_state_item('target_path', args.get('target_path'))
 	apply_state_item('output_path', args.get('output_path'))
+	# patterns
+	apply_state_item('source_pattern', args.get('source_pattern'))
+	apply_state_item('target_pattern', args.get('target_pattern'))
+	apply_state_item('output_pattern', args.get('output_pattern'))
 	# face detector
 	apply_state_item('face_detector_model', args.get('face_detector_model'))
 	apply_state_item('face_detector_size', args.get('face_detector_size'))
@@ -48,15 +61,15 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
 	apply_state_item('face_landmarker_model', args.get('face_landmarker_model'))
 	apply_state_item('face_landmarker_score', args.get('face_landmarker_score'))
 	# face selector
-	state_manager.init_item('face_selector_mode', args.get('face_selector_mode'))
-	state_manager.init_item('face_selector_order', args.get('face_selector_order'))
-	state_manager.init_item('face_selector_age_start', args.get('face_selector_age_start'))
-	state_manager.init_item('face_selector_age_end', args.get('face_selector_age_end'))
-	state_manager.init_item('face_selector_gender', args.get('face_selector_gender'))
-	state_manager.init_item('face_selector_race', args.get('face_selector_race'))
-	state_manager.init_item('reference_face_position', args.get('reference_face_position'))
-	state_manager.init_item('reference_face_distance', args.get('reference_face_distance'))
-	state_manager.init_item('reference_frame_number', args.get('reference_frame_number'))
+	apply_state_item('face_selector_mode', args.get('face_selector_mode'))
+	apply_state_item('face_selector_order', args.get('face_selector_order'))
+	apply_state_item('face_selector_age_start', args.get('face_selector_age_start'))
+	apply_state_item('face_selector_age_end', args.get('face_selector_age_end'))
+	apply_state_item('face_selector_gender', args.get('face_selector_gender'))
+	apply_state_item('face_selector_race', args.get('face_selector_race'))
+	apply_state_item('reference_face_position', args.get('reference_face_position'))
+	apply_state_item('reference_face_distance', args.get('reference_face_distance'))
+	apply_state_item('reference_frame_number', args.get('reference_frame_number'))
 	# face masker
 	apply_state_item('face_mask_types', args.get('face_mask_types'))
 	apply_state_item('face_mask_blur', args.get('face_mask_blur'))
@@ -105,11 +118,13 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
 	apply_state_item('execution_providers', args.get('execution_providers'))
 	apply_state_item('execution_thread_count', args.get('execution_thread_count'))
 	apply_state_item('execution_queue_count', args.get('execution_queue_count'))
+	# download
+	apply_state_item('download_providers', args.get('download_providers'))
+	apply_state_item('download_scope', args.get('download_scope'))
 	# memory
 	apply_state_item('video_memory_strategy', args.get('video_memory_strategy'))
 	apply_state_item('system_memory_limit', args.get('system_memory_limit'))
 	# misc
-	apply_state_item('skip_download', args.get('skip_download'))
 	apply_state_item('log_level', args.get('log_level'))
 	# jobs
 	apply_state_item('job_id', args.get('job_id'))

facefusion/choices.py

@@ -2,9 +2,7 @@ import logging
 from typing import List, Sequence
 
 from facefusion.common_helper import create_float_range, create_int_range
-from facefusion.typing import Angle, ExecutionProviderSet, FaceDetectorSet, FaceLandmarkerModel, FaceMaskRegion, FaceMaskType, FaceSelectorMode, FaceSelectorOrder, Gender, JobStatus, LogLevelSet, OutputAudioEncoder, OutputVideoEncoder, OutputVideoPreset, Race, Score, TempFrameFormat, UiWorkflow, VideoMemoryStrategy
-
-video_memory_strategies : List[VideoMemoryStrategy] = [ 'strict', 'moderate', 'tolerant' ]
+from facefusion.typing import Angle, DownloadProviderSet, DownloadScope, ExecutionProviderSet, FaceDetectorSet, FaceLandmarkerModel, FaceMaskRegion, FaceMaskType, FaceSelectorMode, FaceSelectorOrder, Gender, JobStatus, LogLevelSet, OutputAudioEncoder, OutputVideoEncoder, OutputVideoPreset, Race, Score, TempFrameFormat, UiWorkflow, VideoMemoryStrategy
 
 face_detector_set : FaceDetectorSet =\
 {
@@ -22,20 +20,12 @@ face_mask_types : List[FaceMaskType] = [ 'box', 'occlusion', 'region' ]
 face_mask_regions : List[FaceMaskRegion] = [ 'skin', 'left-eyebrow', 'right-eyebrow', 'left-eye', 'right-eye', 'glasses', 'nose', 'mouth', 'upper-lip', 'lower-lip' ]
 temp_frame_formats : List[TempFrameFormat] = [ 'bmp', 'jpg', 'png' ]
 output_audio_encoders : List[OutputAudioEncoder] = [ 'aac', 'libmp3lame', 'libopus', 'libvorbis' ]
-output_video_encoders : List[OutputVideoEncoder] = [ 'libx264', 'libx265', 'libvpx-vp9', 'h264_nvenc', 'hevc_nvenc', 'h264_amf', 'hevc_amf', 'h264_videotoolbox', 'hevc_videotoolbox' ]
+output_video_encoders : List[OutputVideoEncoder] = [ 'libx264', 'libx265', 'libvpx-vp9', 'h264_nvenc', 'hevc_nvenc', 'h264_amf', 'hevc_amf', 'h264_qsv', 'hevc_qsv', 'h264_videotoolbox', 'hevc_videotoolbox' ]
 output_video_presets : List[OutputVideoPreset] = [ 'ultrafast', 'superfast', 'veryfast', 'faster', 'fast', 'medium', 'slow', 'slower', 'veryslow' ]
 
 image_template_sizes : List[float] = [ 0.25, 0.5, 0.75, 1, 1.5, 2, 2.5, 3, 3.5, 4 ]
 video_template_sizes : List[int] = [ 240, 360, 480, 540, 720, 1080, 1440, 2160, 4320 ]
 
-log_level_set : LogLevelSet =\
-{
-	'error': logging.ERROR,
-	'warn': logging.WARNING,
-	'info': logging.INFO,
-	'debug': logging.DEBUG
-}
-
 execution_provider_set : ExecutionProviderSet =\
 {
 	'cpu': 'CPUExecutionProvider',
@@ -46,6 +36,22 @@ execution_provider_set : ExecutionProviderSet =\
 	'rocm': 'ROCMExecutionProvider',
 	'tensorrt': 'TensorrtExecutionProvider'
 }
+download_provider_set : DownloadProviderSet =\
+{
+	'github': 'https://github.com/facefusion/facefusion-assets/releases/download/{base_name}/{file_name}',
+	'huggingface': 'https://huggingface.co/facefusion/{base_name}/resolve/main/{file_name}'
+}
+download_scopes : List[DownloadScope] = [ 'lite', 'full' ]
+
+video_memory_strategies : List[VideoMemoryStrategy] = [ 'strict', 'moderate', 'tolerant' ]
+
+log_level_set : LogLevelSet =\
+{
+	'error': logging.ERROR,
+	'warn': logging.WARNING,
+	'info': logging.INFO,
+	'debug': logging.DEBUG
+}
 
 ui_workflows : List[UiWorkflow] = [ 'instant_runner', 'job_runner', 'job_manager' ]
 job_statuses : List[JobStatus] = [ 'drafted', 'queued', 'completed', 'failed' ]

facefusion/content_analyser.py

@@ -5,41 +5,45 @@ import numpy
 from tqdm import tqdm
 
 from facefusion import inference_manager, state_manager, wording
-from facefusion.download import conditional_download_hashes, conditional_download_sources
+from facefusion.download import conditional_download_hashes, conditional_download_sources, resolve_download_url
 from facefusion.filesystem import resolve_relative_path
 from facefusion.thread_helper import conditional_thread_semaphore
-from facefusion.typing import Fps, InferencePool, ModelOptions, ModelSet, VisionFrame
+from facefusion.typing import DownloadScope, Fps, InferencePool, ModelOptions, ModelSet, VisionFrame
 from facefusion.vision import count_video_frame_total, detect_video_fps, get_video_frame, read_image
 
-MODEL_SET : ModelSet =\
-{
-	'open_nsfw':
-	{
-		'hashes':
-		{
-			'content_analyser':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/open_nsfw.hash',
-				'path': resolve_relative_path('../.assets/models/open_nsfw.hash')
-			}
-		},
-		'sources':
-		{
-			'content_analyser':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/open_nsfw.onnx',
-				'path': resolve_relative_path('../.assets/models/open_nsfw.onnx')
-			}
-		},
-		'size': (224, 224),
-		'mean': [ 104, 117, 123 ]
-	}
-}
 PROBABILITY_LIMIT = 0.80
 RATE_LIMIT = 10
 STREAM_COUNTER = 0
 
 
+@lru_cache(maxsize = None)
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
+	return\
+	{
+		'open_nsfw':
+		{
+			'hashes':
+			{
+				'content_analyser':
+				{
+					'url': resolve_download_url('models-3.0.0', 'open_nsfw.hash'),
+					'path': resolve_relative_path('../.assets/models/open_nsfw.hash')
+				}
+			},
+			'sources':
+			{
+				'content_analyser':
+				{
+					'url': resolve_download_url('models-3.0.0', 'open_nsfw.onnx'),
+					'path': resolve_relative_path('../.assets/models/open_nsfw.onnx')
+				}
+			},
+			'size': (224, 224),
+			'mean': [ 104, 117, 123 ]
+		}
+	}
+
+
 def get_inference_pool() -> InferencePool:
 	model_sources = get_model_options().get('sources')
 	return inference_manager.get_inference_pool(__name__, model_sources)
@@ -50,15 +54,14 @@ def clear_inference_pool() -> None:
 
 
 def get_model_options() -> ModelOptions:
-	return MODEL_SET.get('open_nsfw')
+	return create_static_model_set('full').get('open_nsfw')
 
 
 def pre_check() -> bool:
-	download_directory_path = resolve_relative_path('../.assets/models')
 	model_hashes = get_model_options().get('hashes')
 	model_sources = get_model_options().get('sources')
 
-	return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources)
+	return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
 
 
 def analyse_stream(vision_frame : VisionFrame, video_fps : Fps) -> bool:
@@ -100,8 +103,8 @@ def prepare_frame(vision_frame : VisionFrame) -> VisionFrame:
 
 @lru_cache(maxsize = None)
 def analyse_image(image_path : str) -> bool:
-	frame = read_image(image_path)
-	return analyse_frame(frame)
+	vision_frame = read_image(image_path)
+	return analyse_frame(vision_frame)
 
 
 @lru_cache(maxsize = None)
@@ -115,8 +118,8 @@ def analyse_video(video_path : str, start_frame : int, end_frame : int) -> bool:
 	with tqdm(total = len(frame_range), desc = wording.get('analysing'), unit = 'frame', ascii = ' =', disable = state_manager.get_item('log_level') in [ 'warn', 'error' ]) as progress:
 		for frame_number in frame_range:
 			if frame_number % int(video_fps) == 0:
-				frame = get_video_frame(video_path, frame_number)
-				if analyse_frame(frame):
+				vision_frame = get_video_frame(video_path, frame_number)
+				if analyse_frame(vision_frame):
 					counter += 1
 			rate = counter * int(video_fps) / len(frame_range) * 100
 			progress.update()

facefusion/core.py

@@ -1,12 +1,14 @@
+import itertools
 import shutil
 import signal
 import sys
+import webbrowser
 from time import time
 
 import numpy
 
-from facefusion import content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer, logger, process_manager, state_manager, voice_extractor, wording
-from facefusion.args import apply_args, collect_job_args, reduce_step_args
+from facefusion import api, content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer, logger, process_manager, state_manager, voice_extractor, wording
+from facefusion.args import apply_args, collect_job_args, reduce_job_args, reduce_step_args
 from facefusion.common_helper import get_first
 from facefusion.content_analyser import analyse_image, analyse_video
 from facefusion.download import conditional_download_hashes, conditional_download_sources
@@ -15,7 +17,7 @@ from facefusion.face_analyser import get_average_face, get_many_faces, get_one_f
 from facefusion.face_selector import sort_and_filter_faces
 from facefusion.face_store import append_reference_face, clear_reference_faces, get_reference_faces
 from facefusion.ffmpeg import copy_image, extract_frames, finalize_image, merge_video, replace_audio, restore_audio
-from facefusion.filesystem import filter_audio_paths, is_image, is_video, list_directory, resolve_relative_path
+from facefusion.filesystem import filter_audio_paths, is_image, is_video, list_directory, resolve_file_pattern
 from facefusion.jobs import job_helper, job_manager, job_runner
 from facefusion.jobs.job_list import compose_job_list
 from facefusion.memory import limit_system_memory
@@ -41,6 +43,8 @@ def cli() -> None:
 			route(args)
 		else:
 			program.print_help()
+	else:
+		hard_exit(2)
 
 
 def route(args : Args) -> None:
@@ -58,19 +62,20 @@ def route(args : Args) -> None:
 	if not pre_check():
 		return conditional_exit(2)
 	if state_manager.get_item('command') == 'run':
-		import facefusion.uis.core as ui
-
-		if not common_pre_check() or not processors_pre_check():
-			return conditional_exit(2)
-		for ui_layout in ui.get_ui_layouts_modules(state_manager.get_item('ui_layouts')):
-			if not ui_layout.pre_check():
-				return conditional_exit(2)
-		ui.launch()
+		if state_manager.get_item('open_browser'):
+			webbrowser.open('http://127.0.0.1:8000/frontend')
+		logger.info('http://127.0.0.1:8000/frontend', __name__)
+		api.run()
 	if state_manager.get_item('command') == 'headless-run':
 		if not job_manager.init_jobs(state_manager.get_item('jobs_path')):
 			hard_exit(1)
 		error_core = process_headless(args)
 		hard_exit(error_core)
+	if state_manager.get_item('command') == 'batch-run':
+		if not job_manager.init_jobs(state_manager.get_item('jobs_path')):
+			hard_exit(1)
+		error_core = process_batch(args)
+		hard_exit(error_core)
 	if state_manager.get_item('command') in [ 'job-run', 'job-run-all', 'job-retry', 'job-retry-all' ]:
 		if not job_manager.init_jobs(state_manager.get_item('jobs_path')):
 			hard_exit(1)
@@ -79,8 +84,8 @@ def route(args : Args) -> None:
 
 
 def pre_check() -> bool:
-	if sys.version_info < (3, 9):
-		logger.error(wording.get('python_not_supported').format(version = '3.9'), __name__)
+	if sys.version_info < (3, 10):
+		logger.error(wording.get('python_not_supported').format(version = '3.10'), __name__)
 		return False
 	if not shutil.which('curl'):
 		logger.error(wording.get('curl_not_installed'), __name__)
@@ -92,7 +97,7 @@ def pre_check() -> bool:
 
 
 def common_pre_check() -> bool:
-	modules =\
+	common_modules =\
 	[
 		content_analyser,
 		face_classifier,
@@ -103,7 +108,7 @@ def common_pre_check() -> bool:
 		voice_extractor
 	]
 
-	return all(module.pre_check() for module in modules)
+	return all(module.pre_check() for module in common_modules)
 
 
 def processors_pre_check() -> bool:
@@ -113,64 +118,28 @@ def processors_pre_check() -> bool:
 	return True
 
 
-def conditional_process() -> ErrorCode:
-	start_time = time()
-	for processor_module in get_processors_modules(state_manager.get_item('processors')):
-		if not processor_module.pre_process('output'):
-			return 2
-	conditional_append_reference_faces()
-	if is_image(state_manager.get_item('target_path')):
-		return process_image(start_time)
-	if is_video(state_manager.get_item('target_path')):
-		return process_video(start_time)
-	return 0
-
-
-def conditional_append_reference_faces() -> None:
-	if 'reference' in state_manager.get_item('face_selector_mode') and not get_reference_faces():
-		source_frames = read_static_images(state_manager.get_item('source_paths'))
-		source_faces = get_many_faces(source_frames)
-		source_face = get_average_face(source_faces)
-		if is_video(state_manager.get_item('target_path')):
-			reference_frame = get_video_frame(state_manager.get_item('target_path'), state_manager.get_item('reference_frame_number'))
-		else:
-			reference_frame = read_image(state_manager.get_item('target_path'))
-		reference_faces = sort_and_filter_faces(get_many_faces([ reference_frame ]))
-		reference_face = get_one_face(reference_faces, state_manager.get_item('reference_face_position'))
-		append_reference_face('origin', reference_face)
-
-		if source_face and reference_face:
-			for processor_module in get_processors_modules(state_manager.get_item('processors')):
-				abstract_reference_frame = processor_module.get_reference_frame(source_face, reference_face, reference_frame)
-				if numpy.any(abstract_reference_frame):
-					abstract_reference_faces = sort_and_filter_faces(get_many_faces([ abstract_reference_frame ]))
-					abstract_reference_face = get_one_face(abstract_reference_faces, state_manager.get_item('reference_face_position'))
-					append_reference_face(processor_module.__name__, abstract_reference_face)
-
-
 def force_download() -> ErrorCode:
-	download_directory_path = resolve_relative_path('../.assets/models')
-	available_processors = list_directory('facefusion/processors/modules')
 	common_modules =\
 	[
 		content_analyser,
 		face_classifier,
 		face_detector,
 		face_landmarker,
-		face_recognizer,
 		face_masker,
+		face_recognizer,
 		voice_extractor
 	]
+	available_processors = list_directory('facefusion/processors/modules')
 	processor_modules = get_processors_modules(available_processors)
 
 	for module in common_modules + processor_modules:
-		if hasattr(module, 'MODEL_SET'):
-			for model in module.MODEL_SET.values():
+		if hasattr(module, 'create_static_model_set'):
+			for model in module.create_static_model_set(state_manager.get_item('download_scope')).values():
 				model_hashes = model.get('hashes')
 				model_sources = model.get('sources')
 
 				if model_hashes and model_sources:
-					if not conditional_download_hashes(download_directory_path, model_hashes) or not conditional_download_sources(download_directory_path, model_sources):
+					if not conditional_download_hashes(model_hashes) or not conditional_download_sources(model_sources):
 						return 1
 
 	return 0
@@ -279,6 +248,44 @@ def route_job_runner() -> ErrorCode:
 	return 2
 
 
+def process_headless(args : Args) -> ErrorCode:
+	job_id = job_helper.suggest_job_id('headless')
+	step_args = reduce_step_args(args)
+
+	if job_manager.create_job(job_id) and job_manager.add_step(job_id, step_args) and job_manager.submit_job(job_id) and job_runner.run_job(job_id, process_step):
+		return 0
+	return 1
+
+
+def process_batch(args : Args) -> ErrorCode:
+	job_id = job_helper.suggest_job_id('batch')
+	step_args = reduce_step_args(args)
+	job_args = reduce_job_args(args)
+	source_paths = resolve_file_pattern(job_args.get('source_pattern'))
+	target_paths = resolve_file_pattern(job_args.get('target_pattern'))
+
+	if job_manager.create_job(job_id):
+		if source_paths and target_paths:
+			for index, (source_path, target_path) in enumerate(itertools.product(source_paths, target_paths)):
+				step_args['source_paths'] = [ source_path ]
+				step_args['target_path'] = target_path
+				step_args['output_path'] = job_args.get('output_pattern').format(index = index)
+				if not job_manager.add_step(job_id, step_args):
+					return 1
+			if job_manager.submit_job(job_id) and job_runner.run_job(job_id, process_step):
+				return 0
+
+		if not source_paths and target_paths:
+			for index, target_path in enumerate(target_paths):
+				step_args['target_path'] = target_path
+				step_args['output_path'] = job_args.get('output_pattern').format(index = index)
+				if not job_manager.add_step(job_id, step_args):
+					return 1
+			if job_manager.submit_job(job_id) and job_runner.run_job(job_id, process_step):
+				return 0
+	return 1
+
+
 def process_step(job_id : str, step_index : int, step_args : Args) -> bool:
 	clear_reference_faces()
 	step_total = job_manager.count_step_total(job_id)
@@ -292,13 +299,39 @@ def process_step(job_id : str, step_index : int, step_args : Args) -> bool:
 	return False
 
 
-def process_headless(args : Args) -> ErrorCode:
-	job_id = job_helper.suggest_job_id('headless')
-	step_args = reduce_step_args(args)
+def conditional_process() -> ErrorCode:
+	start_time = time()
+	for processor_module in get_processors_modules(state_manager.get_item('processors')):
+		if not processor_module.pre_process('output'):
+			return 2
+	conditional_append_reference_faces()
+	if is_image(state_manager.get_item('target_path')):
+		return process_image(start_time)
+	if is_video(state_manager.get_item('target_path')):
+		return process_video(start_time)
+	return 0
 
-	if job_manager.create_job(job_id) and job_manager.add_step(job_id, step_args) and job_manager.submit_job(job_id) and job_runner.run_job(job_id, process_step):
-		return 0
-	return 1
+
+def conditional_append_reference_faces() -> None:
+	if 'reference' in state_manager.get_item('face_selector_mode') and not get_reference_faces():
+		source_frames = read_static_images(state_manager.get_item('source_paths'))
+		source_faces = get_many_faces(source_frames)
+		source_face = get_average_face(source_faces)
+		if is_video(state_manager.get_item('target_path')):
+			reference_frame = get_video_frame(state_manager.get_item('target_path'), state_manager.get_item('reference_frame_number'))
+		else:
+			reference_frame = read_image(state_manager.get_item('target_path'))
+		reference_faces = sort_and_filter_faces(get_many_faces([ reference_frame ]))
+		reference_face = get_one_face(reference_faces, state_manager.get_item('reference_face_position'))
+		append_reference_face('origin', reference_face)
+
+		if source_face and reference_face:
+			for processor_module in get_processors_modules(state_manager.get_item('processors')):
+				abstract_reference_frame = processor_module.get_reference_frame(source_face, reference_face, reference_frame)
+				if numpy.any(abstract_reference_frame):
+					abstract_reference_faces = sort_and_filter_faces(get_many_faces([ abstract_reference_frame ]))
+					abstract_reference_face = get_one_face(abstract_reference_faces, state_manager.get_item('reference_face_position'))
+					append_reference_face(processor_module.__name__, abstract_reference_face)
 
 
 def process_image(start_time : float) -> ErrorCode:

facefusion/download.py

@@ -4,16 +4,17 @@ import ssl
 import subprocess
 import urllib.request
 from functools import lru_cache
-from typing import List, Tuple
+from typing import List, Optional, Tuple
 from urllib.parse import urlparse
 
 from tqdm import tqdm
 
 from facefusion import logger, process_manager, state_manager, wording
+from facefusion.choices import download_provider_set
 from facefusion.common_helper import is_macos
 from facefusion.filesystem import get_file_size, is_file, remove_file
 from facefusion.hash_helper import validate_hash
-from facefusion.typing import DownloadSet
+from facefusion.typing import DownloadProviderKey, DownloadSet
 
 if is_macos():
 	ssl._create_default_https_context = ssl._create_unverified_context
@@ -30,8 +31,7 @@ def conditional_download(download_directory_path : str, urls : List[str]) -> Non
 			with tqdm(total = download_size, initial = initial_size, desc = wording.get('downloading'), unit = 'B', unit_scale = True, unit_divisor = 1024, ascii = ' =', disable = state_manager.get_item('log_level') in [ 'warn', 'error' ]) as progress:
 				subprocess.Popen([ shutil.which('curl'), '--create-dirs', '--silent', '--insecure', '--location', '--continue-at', '-', '--output', download_file_path, url ])
 				current_size = initial_size
-
-				progress.set_postfix(file = download_file_name)
+				progress.set_postfix(download_providers = state_manager.get_item('download_providers'), file_name = download_file_name)
 				while current_size < download_size:
 					if is_file(download_file_path):
 						current_size = get_file_size(download_file_path)
@@ -48,23 +48,17 @@ def get_download_size(url : str) -> int:
 		return 0
 
 
-def is_download_done(url : str, file_path : str) -> bool:
-	if is_file(file_path):
-		return get_download_size(url) == get_file_size(file_path)
-	return False
-
-
-def conditional_download_hashes(download_directory_path : str, hashes : DownloadSet) -> bool:
+def conditional_download_hashes(hashes : DownloadSet) -> bool:
 	hash_paths = [ hashes.get(hash_key).get('path') for hash_key in hashes.keys() ]
 
 	process_manager.check()
-	if not state_manager.get_item('skip_download'):
-		_, invalid_hash_paths = validate_hash_paths(hash_paths)
-		if invalid_hash_paths:
-			for index in hashes:
-				if hashes.get(index).get('path') in invalid_hash_paths:
-					invalid_hash_url = hashes.get(index).get('url')
-					conditional_download(download_directory_path, [ invalid_hash_url ])
+	_, invalid_hash_paths = validate_hash_paths(hash_paths)
+	if invalid_hash_paths:
+		for index in hashes:
+			if hashes.get(index).get('path') in invalid_hash_paths:
+				invalid_hash_url = hashes.get(index).get('url')
+				download_directory_path = os.path.dirname(hashes.get(index).get('path'))
+				conditional_download(download_directory_path, [ invalid_hash_url ])
 
 	valid_hash_paths, invalid_hash_paths = validate_hash_paths(hash_paths)
 	for valid_hash_path in valid_hash_paths:
@@ -79,17 +73,17 @@ def conditional_download_hashes(download_directory_path : str, hashes : Download
 	return not invalid_hash_paths
 
 
-def conditional_download_sources(download_directory_path : str, sources : DownloadSet) -> bool:
+def conditional_download_sources(sources : DownloadSet) -> bool:
 	source_paths = [ sources.get(source_key).get('path') for source_key in sources.keys() ]
 
 	process_manager.check()
-	if not state_manager.get_item('skip_download'):
-		_, invalid_source_paths = validate_source_paths(source_paths)
-		if invalid_source_paths:
-			for index in sources:
-				if sources.get(index).get('path') in invalid_source_paths:
-					invalid_source_url = sources.get(index).get('url')
-					conditional_download(download_directory_path, [ invalid_source_url ])
+	_, invalid_source_paths = validate_source_paths(source_paths)
+	if invalid_source_paths:
+		for index in sources:
+			if sources.get(index).get('path') in invalid_source_paths:
+				invalid_source_url = sources.get(index).get('url')
+				download_directory_path = os.path.dirname(sources.get(index).get('path'))
+				conditional_download(download_directory_path, [ invalid_source_url ])
 
 	valid_source_paths, invalid_source_paths = validate_source_paths(source_paths)
 	for valid_source_path in valid_source_paths:
@@ -129,3 +123,16 @@ def validate_source_paths(source_paths : List[str]) -> Tuple[List[str], List[str
 		else:
 			invalid_source_paths.append(source_path)
 	return valid_source_paths, invalid_source_paths
+
+
+def resolve_download_url(base_name : str, file_name : str) -> Optional[str]:
+	download_providers = state_manager.get_item('download_providers')
+
+	for download_provider in download_provider_set:
+		if download_provider in download_providers:
+			return resolve_download_url_by_provider(download_provider, base_name, file_name)
+	return None
+
+
+def resolve_download_url_by_provider(download_provider : DownloadProviderKey, base_name : str, file_name : str) -> Optional[str]:
+	return download_provider_set.get(download_provider).format(base_name = base_name, file_name = file_name)

facefusion/execution.py

@@ -1,7 +1,8 @@
+import shutil
 import subprocess
 import xml.etree.ElementTree as ElementTree
 from functools import lru_cache
-from typing import Any, List
+from typing import Any, List, Optional
 
 from onnxruntime import get_available_providers, set_default_logger_severity
 
@@ -11,15 +12,11 @@ from facefusion.typing import ExecutionDevice, ExecutionProviderKey, ExecutionPr
 set_default_logger_severity(3)
 
 
-def get_execution_provider_choices() -> List[ExecutionProviderKey]:
-	return list(get_available_execution_provider_set().keys())
-
-
 def has_execution_provider(execution_provider_key : ExecutionProviderKey) -> bool:
-	return execution_provider_key in get_execution_provider_choices()
+	return execution_provider_key in get_execution_provider_set().keys()
 
 
-def get_available_execution_provider_set() -> ExecutionProviderSet:
+def get_execution_provider_set() -> ExecutionProviderSet:
 	available_execution_providers = get_available_providers()
 	available_execution_provider_set : ExecutionProviderSet = {}
 
@@ -36,8 +33,7 @@ def create_execution_providers(execution_device_id : str, execution_provider_key
 		if execution_provider_key == 'cuda':
 			execution_providers.append((execution_provider_set.get(execution_provider_key),
 			{
-				'device_id': execution_device_id,
-				'cudnn_conv_algo_search': 'EXHAUSTIVE' if use_exhaustive() else 'DEFAULT'
+				'device_id': execution_device_id
 			}))
 		if execution_provider_key == 'tensorrt':
 			execution_providers.append((execution_provider_set.get(execution_provider_key),
@@ -52,7 +48,7 @@ def create_execution_providers(execution_device_id : str, execution_provider_key
 		if execution_provider_key == 'openvino':
 			execution_providers.append((execution_provider_set.get(execution_provider_key),
 			{
-				'device_type': 'GPU.' + execution_device_id,
+				'device_type': 'GPU' if execution_device_id == '0' else 'GPU.' + execution_device_id,
 				'precision': 'FP32'
 			}))
 		if execution_provider_key in [ 'directml', 'rocm' ]:
@@ -69,15 +65,8 @@ def create_execution_providers(execution_device_id : str, execution_provider_key
 	return execution_providers
 
 
-def use_exhaustive() -> bool:
-	execution_devices = detect_static_execution_devices()
-	product_names = ('GeForce GTX 1630', 'GeForce GTX 1650', 'GeForce GTX 1660')
-
-	return any(execution_device.get('product').get('name').startswith(product_names) for execution_device in execution_devices)
-
-
 def run_nvidia_smi() -> subprocess.Popen[bytes]:
-	commands = [ 'nvidia-smi', '--query', '--xml-format' ]
+	commands = [ shutil.which('nvidia-smi'), '--query', '--xml-format' ]
 	return subprocess.Popen(commands, stdout = subprocess.PIPE)
 
 
@@ -98,37 +87,44 @@ def detect_execution_devices() -> List[ExecutionDevice]:
 	for gpu_element in root_element.findall('gpu'):
 		execution_devices.append(
 		{
-			'driver_version': root_element.find('driver_version').text,
+			'driver_version': root_element.findtext('driver_version'),
 			'framework':
 			{
 				'name': 'CUDA',
-				'version': root_element.find('cuda_version').text
+				'version': root_element.findtext('cuda_version')
 			},
 			'product':
 			{
 				'vendor': 'NVIDIA',
-				'name': gpu_element.find('product_name').text.replace('NVIDIA ', '')
+				'name': gpu_element.findtext('product_name').replace('NVIDIA', '').strip()
 			},
 			'video_memory':
 			{
-				'total': create_value_and_unit(gpu_element.find('fb_memory_usage/total').text),
-				'free': create_value_and_unit(gpu_element.find('fb_memory_usage/free').text)
+				'total': create_value_and_unit(gpu_element.findtext('fb_memory_usage/total')),
+				'free': create_value_and_unit(gpu_element.findtext('fb_memory_usage/free'))
+			},
+			'temperature':
+			{
+				'gpu': create_value_and_unit(gpu_element.findtext('temperature/gpu_temp')),
+				'memory': create_value_and_unit(gpu_element.findtext('temperature/memory_temp'))
 			},
 			'utilization':
 			{
-				'gpu': create_value_and_unit(gpu_element.find('utilization/gpu_util').text),
-				'memory': create_value_and_unit(gpu_element.find('utilization/memory_util').text)
+				'gpu': create_value_and_unit(gpu_element.findtext('utilization/gpu_util')),
+				'memory': create_value_and_unit(gpu_element.findtext('utilization/memory_util'))
 			}
 		})
+
 	return execution_devices
 
 
-def create_value_and_unit(text : str) -> ValueAndUnit:
-	value, unit = text.split()
-	value_and_unit : ValueAndUnit =\
-	{
-		'value': int(value),
-		'unit': str(unit)
-	}
+def create_value_and_unit(text : str) -> Optional[ValueAndUnit]:
+	if ' ' in text:
+		value, unit = text.split(' ')
 
-	return value_and_unit
+		return\
+		{
+			'value': int(value),
+			'unit': str(unit)
+		}
+	return None

facefusion/face_classifier.py

@@ -1,40 +1,44 @@
+from functools import lru_cache
 from typing import List, Tuple
 
 import numpy
 
 from facefusion import inference_manager
-from facefusion.download import conditional_download_hashes, conditional_download_sources
+from facefusion.download import conditional_download_hashes, conditional_download_sources, resolve_download_url
 from facefusion.face_helper import warp_face_by_face_landmark_5
 from facefusion.filesystem import resolve_relative_path
 from facefusion.thread_helper import conditional_thread_semaphore
-from facefusion.typing import Age, FaceLandmark5, Gender, InferencePool, ModelOptions, ModelSet, Race, VisionFrame
+from facefusion.typing import Age, DownloadScope, FaceLandmark5, Gender, InferencePool, ModelOptions, ModelSet, Race, VisionFrame
 
-MODEL_SET : ModelSet =\
-{
-	'fairface':
+
+@lru_cache(maxsize = None)
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
+	return\
 	{
-		'hashes':
+		'fairface':
 		{
-			'face_classifier':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/fairface.hash',
-				'path': resolve_relative_path('../.assets/models/fairface.hash')
-			}
-		},
-		'sources':
-		{
-			'face_classifier':
+				'face_classifier':
+				{
+					'url': resolve_download_url('models-3.0.0', 'fairface.hash'),
+					'path': resolve_relative_path('../.assets/models/fairface.hash')
+				}
+			},
+			'sources':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/fairface.onnx',
-				'path': resolve_relative_path('../.assets/models/fairface.onnx')
-			}
-		},
-		'template': 'arcface_112_v2',
-		'size': (224, 224),
-		'mean': [ 0.485, 0.456, 0.406 ],
-		'standard_deviation': [ 0.229, 0.224, 0.225 ]
+				'face_classifier':
+				{
+					'url': resolve_download_url('models-3.0.0', 'fairface.onnx'),
+					'path': resolve_relative_path('../.assets/models/fairface.onnx')
+				}
+			},
+			'template': 'arcface_112_v2',
+			'size': (224, 224),
+			'mean': [ 0.485, 0.456, 0.406 ],
+			'standard_deviation': [ 0.229, 0.224, 0.225 ]
+		}
 	}
-}
 
 
 def get_inference_pool() -> InferencePool:
@@ -47,15 +51,14 @@ def clear_inference_pool() -> None:
 
 
 def get_model_options() -> ModelOptions:
-	return MODEL_SET.get('fairface')
+	return create_static_model_set('full').get('fairface')
 
 
 def pre_check() -> bool:
-	download_directory_path = resolve_relative_path('../.assets/models')
 	model_hashes = get_model_options().get('hashes')
 	model_sources = get_model_options().get('sources')
 
-	return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources)
+	return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
 
 
 def classify_face(temp_vision_frame : VisionFrame, face_landmark_5 : FaceLandmark5) -> Tuple[Gender, Age, Race]:

facefusion/face_detector.py

@@ -2,75 +2,79 @@ from typing import List, Tuple
 
 import cv2
 import numpy
+from charset_normalizer.md import lru_cache
 
 from facefusion import inference_manager, state_manager
-from facefusion.download import conditional_download_hashes, conditional_download_sources
+from facefusion.download import conditional_download_hashes, conditional_download_sources, resolve_download_url
 from facefusion.face_helper import create_rotated_matrix_and_size, create_static_anchors, distance_to_bounding_box, distance_to_face_landmark_5, normalize_bounding_box, transform_bounding_box, transform_points
 from facefusion.filesystem import resolve_relative_path
 from facefusion.thread_helper import thread_semaphore
-from facefusion.typing import Angle, BoundingBox, Detection, DownloadSet, FaceLandmark5, InferencePool, ModelSet, Score, VisionFrame
+from facefusion.typing import Angle, BoundingBox, Detection, DownloadScope, DownloadSet, FaceLandmark5, InferencePool, ModelSet, Score, VisionFrame
 from facefusion.vision import resize_frame_resolution, unpack_resolution
 
-MODEL_SET : ModelSet =\
-{
-	'retinaface':
+
+@lru_cache(maxsize = None)
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
+	return\
 	{
-		'hashes':
+		'retinaface':
 		{
-			'retinaface':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/retinaface_10g.hash',
-				'path': resolve_relative_path('../.assets/models/retinaface_10g.hash')
+				'retinaface':
+				{
+					'url': resolve_download_url('models-3.0.0', 'retinaface_10g.hash'),
+					'path': resolve_relative_path('../.assets/models/retinaface_10g.hash')
+				}
+			},
+			'sources':
+			{
+				'retinaface':
+				{
+					'url': resolve_download_url('models-3.0.0', 'retinaface_10g.onnx'),
+					'path': resolve_relative_path('../.assets/models/retinaface_10g.onnx')
+				}
 			}
 		},
-		'sources':
+		'scrfd':
 		{
-			'retinaface':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/retinaface_10g.onnx',
-				'path': resolve_relative_path('../.assets/models/retinaface_10g.onnx')
-			}
-		}
-	},
-	'scrfd':
-	{
-		'hashes':
-		{
-			'scrfd':
+				'scrfd':
+				{
+					'url': resolve_download_url('models-3.0.0', 'scrfd_2.5g.hash'),
+					'path': resolve_relative_path('../.assets/models/scrfd_2.5g.hash')
+				}
+			},
+			'sources':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/scrfd_2.5g.hash',
-				'path': resolve_relative_path('../.assets/models/scrfd_2.5g.hash')
+				'scrfd':
+				{
+					'url': resolve_download_url('models-3.0.0', 'scrfd_2.5g.onnx'),
+					'path': resolve_relative_path('../.assets/models/scrfd_2.5g.onnx')
+				}
 			}
 		},
-		'sources':
+		'yoloface':
 		{
-			'scrfd':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/scrfd_2.5g.onnx',
-				'path': resolve_relative_path('../.assets/models/scrfd_2.5g.onnx')
-			}
-		}
-	},
-	'yoloface':
-	{
-		'hashes':
-		{
-			'yoloface':
+				'yoloface':
+				{
+					'url': resolve_download_url('models-3.0.0', 'yoloface_8n.hash'),
+					'path': resolve_relative_path('../.assets/models/yoloface_8n.hash')
+				}
+			},
+			'sources':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/yoloface_8n.hash',
-				'path': resolve_relative_path('../.assets/models/yoloface_8n.hash')
-			}
-		},
-		'sources':
-		{
-			'yoloface':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/yoloface_8n.onnx',
-				'path': resolve_relative_path('../.assets/models/yoloface_8n.onnx')
+				'yoloface':
+				{
+					'url': resolve_download_url('models-3.0.0', 'yoloface_8n.onnx'),
+					'path': resolve_relative_path('../.assets/models/yoloface_8n.onnx')
+				}
 			}
 		}
 	}
-}
 
 
 def get_inference_pool() -> InferencePool:
@@ -87,24 +91,24 @@ def clear_inference_pool() -> None:
 def collect_model_downloads() -> Tuple[DownloadSet, DownloadSet]:
 	model_hashes = {}
 	model_sources = {}
+	model_set = create_static_model_set('full')
 
 	if state_manager.get_item('face_detector_model') in [ 'many', 'retinaface' ]:
-		model_hashes['retinaface'] = MODEL_SET.get('retinaface').get('hashes').get('retinaface')
-		model_sources['retinaface'] = MODEL_SET.get('retinaface').get('sources').get('retinaface')
+		model_hashes['retinaface'] = model_set.get('retinaface').get('hashes').get('retinaface')
+		model_sources['retinaface'] = model_set.get('retinaface').get('sources').get('retinaface')
 	if state_manager.get_item('face_detector_model') in [ 'many', 'scrfd' ]:
-		model_hashes['scrfd'] = MODEL_SET.get('scrfd').get('hashes').get('scrfd')
-		model_sources['scrfd'] = MODEL_SET.get('scrfd').get('sources').get('scrfd')
+		model_hashes['scrfd'] = model_set.get('scrfd').get('hashes').get('scrfd')
+		model_sources['scrfd'] = model_set.get('scrfd').get('sources').get('scrfd')
 	if state_manager.get_item('face_detector_model') in [ 'many', 'yoloface' ]:
-		model_hashes['yoloface'] = MODEL_SET.get('yoloface').get('hashes').get('yoloface')
-		model_sources['yoloface'] = MODEL_SET.get('yoloface').get('sources').get('yoloface')
+		model_hashes['yoloface'] = model_set.get('yoloface').get('hashes').get('yoloface')
+		model_sources['yoloface'] = model_set.get('yoloface').get('sources').get('yoloface')
 	return model_hashes, model_sources
 
 
 def pre_check() -> bool:
-	download_directory_path = resolve_relative_path('../.assets/models')
 	model_hashes, model_sources = collect_model_downloads()
 
-	return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources)
+	return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
 
 
 def detect_faces(vision_frame : VisionFrame) -> Tuple[List[BoundingBox], List[Score], List[FaceLandmark5]]:

facefusion/face_helper.py

@@ -33,6 +33,14 @@ WARP_TEMPLATES : WarpTemplateSet =\
 		[ 0.38710391, 0.72160547 ],
 		[ 0.61507734, 0.72034453 ]
 	]),
+	'dfl_whole_face': numpy.array(
+	[
+		[ 0.35342266, 0.39285716 ],
+		[ 0.62797622, 0.39285716 ],
+		[ 0.48660713, 0.54017860 ],
+		[ 0.38839287, 0.68750011 ],
+		[ 0.59821427, 0.68750011 ]
+	]),
 	'ffhq_512': numpy.array(
 	[
 		[ 0.37691676, 0.46864664 ],
@@ -40,6 +48,22 @@ WARP_TEMPLATES : WarpTemplateSet =\
 		[ 0.50123859, 0.61331904 ],
 		[ 0.39308822, 0.72541100 ],
 		[ 0.61150205, 0.72490465 ]
+	]),
+	'mtcnn_512': numpy.array(
+	[
+		[ 0.36562865, 0.46733799 ],
+		[ 0.63305391, 0.46585885 ],
+		[ 0.50019127, 0.61942959 ],
+		[ 0.39032951, 0.77598822 ],
+		[ 0.61178945, 0.77476328 ]
+	]),
+	'styleganex_384': numpy.array(
+	[
+		[ 0.42353745, 0.52289879 ],
+		[ 0.57725008, 0.52319972 ],
+		[ 0.50123859, 0.61331904 ],
+		[ 0.43364461, 0.68337652 ],
+		[ 0.57015325, 0.68306005 ]
 	])
 }
 

facefusion/face_landmarker.py

@@ -1,77 +1,81 @@
+from functools import lru_cache
 from typing import Tuple
 
 import cv2
 import numpy
 
 from facefusion import inference_manager, state_manager
-from facefusion.download import conditional_download_hashes, conditional_download_sources
+from facefusion.download import conditional_download_hashes, conditional_download_sources, resolve_download_url
 from facefusion.face_helper import create_rotated_matrix_and_size, estimate_matrix_by_face_landmark_5, transform_points, warp_face_by_translation
 from facefusion.filesystem import resolve_relative_path
 from facefusion.thread_helper import conditional_thread_semaphore
-from facefusion.typing import Angle, BoundingBox, DownloadSet, FaceLandmark5, FaceLandmark68, InferencePool, ModelSet, Prediction, Score, VisionFrame
+from facefusion.typing import Angle, BoundingBox, DownloadScope, DownloadSet, FaceLandmark5, FaceLandmark68, InferencePool, ModelSet, Prediction, Score, VisionFrame
 
-MODEL_SET : ModelSet =\
-{
-	'2dfan4':
+
+@lru_cache(maxsize = None)
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
+	return\
 	{
-		'hashes':
+		'2dfan4':
 		{
-			'2dfan4':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/2dfan4.hash',
-				'path': resolve_relative_path('../.assets/models/2dfan4.hash')
-			}
+				'2dfan4':
+				{
+					'url': resolve_download_url('models-3.0.0', '2dfan4.hash'),
+					'path': resolve_relative_path('../.assets/models/2dfan4.hash')
+				}
+			},
+			'sources':
+			{
+				'2dfan4':
+				{
+					'url': resolve_download_url('models-3.0.0', '2dfan4.onnx'),
+					'path': resolve_relative_path('../.assets/models/2dfan4.onnx')
+				}
+			},
+			'size': (256, 256)
 		},
-		'sources':
+		'peppa_wutz':
 		{
-			'2dfan4':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/2dfan4.onnx',
-				'path': resolve_relative_path('../.assets/models/2dfan4.onnx')
-			}
+				'peppa_wutz':
+				{
+					'url': resolve_download_url('models-3.0.0', 'peppa_wutz.hash'),
+					'path': resolve_relative_path('../.assets/models/peppa_wutz.hash')
+				}
+			},
+			'sources':
+			{
+				'peppa_wutz':
+				{
+					'url': resolve_download_url('models-3.0.0', 'peppa_wutz.onnx'),
+					'path': resolve_relative_path('../.assets/models/peppa_wutz.onnx')
+				}
+			},
+			'size': (256, 256)
 		},
-		'size': (256, 256)
-	},
-	'peppa_wutz':
-	{
-		'hashes':
+		'fan_68_5':
 		{
-			'peppa_wutz':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/peppa_wutz.hash',
-				'path': resolve_relative_path('../.assets/models/peppa_wutz.hash')
-			}
-		},
-		'sources':
-		{
-			'peppa_wutz':
+				'fan_68_5':
+				{
+					'url': resolve_download_url('models-3.0.0', 'fan_68_5.hash'),
+					'path': resolve_relative_path('../.assets/models/fan_68_5.hash')
+				}
+			},
+			'sources':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/peppa_wutz.onnx',
-				'path': resolve_relative_path('../.assets/models/peppa_wutz.onnx')
-			}
-		},
-		'size': (256, 256)
-	},
-	'fan_68_5':
-	{
-		'hashes':
-		{
-			'fan_68_5':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/fan_68_5.hash',
-				'path': resolve_relative_path('../.assets/models/fan_68_5.hash')
-			}
-		},
-		'sources':
-		{
-			'fan_68_5':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/fan_68_5.onnx',
-				'path': resolve_relative_path('../.assets/models/fan_68_5.onnx')
+				'fan_68_5':
+				{
+					'url': resolve_download_url('models-3.0.0', 'fan_68_5.onnx'),
+					'path': resolve_relative_path('../.assets/models/fan_68_5.onnx')
+				}
 			}
 		}
 	}
-}
 
 
 def get_inference_pool() -> InferencePool:
@@ -86,29 +90,29 @@ def clear_inference_pool() -> None:
 
 
 def collect_model_downloads() -> Tuple[DownloadSet, DownloadSet]:
+	model_set = create_static_model_set('full')
 	model_hashes =\
 	{
-		'fan_68_5': MODEL_SET.get('fan_68_5').get('hashes').get('fan_68_5')
+		'fan_68_5': model_set.get('fan_68_5').get('hashes').get('fan_68_5')
 	}
 	model_sources =\
 	{
-		'fan_68_5': MODEL_SET.get('fan_68_5').get('sources').get('fan_68_5')
+		'fan_68_5': model_set.get('fan_68_5').get('sources').get('fan_68_5')
 	}
 
 	if state_manager.get_item('face_landmarker_model') in [ 'many', '2dfan4' ]:
-		model_hashes['2dfan4'] = MODEL_SET.get('2dfan4').get('hashes').get('2dfan4')
-		model_sources['2dfan4'] = MODEL_SET.get('2dfan4').get('sources').get('2dfan4')
+		model_hashes['2dfan4'] = model_set.get('2dfan4').get('hashes').get('2dfan4')
+		model_sources['2dfan4'] = model_set.get('2dfan4').get('sources').get('2dfan4')
 	if state_manager.get_item('face_landmarker_model') in [ 'many', 'peppa_wutz' ]:
-		model_hashes['peppa_wutz'] = MODEL_SET.get('peppa_wutz').get('hashes').get('peppa_wutz')
-		model_sources['peppa_wutz'] = MODEL_SET.get('peppa_wutz').get('sources').get('peppa_wutz')
+		model_hashes['peppa_wutz'] = model_set.get('peppa_wutz').get('hashes').get('peppa_wutz')
+		model_sources['peppa_wutz'] = model_set.get('peppa_wutz').get('sources').get('peppa_wutz')
 	return model_hashes, model_sources
 
 
 def pre_check() -> bool:
-	download_directory_path = resolve_relative_path('../.assets/models')
 	model_hashes, model_sources = collect_model_downloads()
 
-	return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources)
+	return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
 
 
 def detect_face_landmarks(vision_frame : VisionFrame, bounding_box : BoundingBox, face_angle : Angle) -> Tuple[FaceLandmark68, Score]:
@@ -128,7 +132,7 @@ def detect_face_landmarks(vision_frame : VisionFrame, bounding_box : BoundingBox
 
 
 def detect_with_2dfan4(temp_vision_frame: VisionFrame, bounding_box: BoundingBox, face_angle: Angle) -> Tuple[FaceLandmark68, Score]:
-	model_size = MODEL_SET.get('2dfan4').get('size')
+	model_size = create_static_model_set('full').get('2dfan4').get('size')
 	scale = 195 / numpy.subtract(bounding_box[2:], bounding_box[:2]).max().clip(1, None)
 	translation = (model_size[0] - numpy.add(bounding_box[2:], bounding_box[:2]) * scale) * 0.5
 	rotated_matrix, rotated_size = create_rotated_matrix_and_size(face_angle, model_size)
@@ -147,7 +151,7 @@ def detect_with_2dfan4(temp_vision_frame: VisionFrame, bounding_box: BoundingBox
 
 
 def detect_with_peppa_wutz(temp_vision_frame : VisionFrame, bounding_box : BoundingBox, face_angle : Angle) -> Tuple[FaceLandmark68, Score]:
-	model_size = MODEL_SET.get('peppa_wutz').get('size')
+	model_size = create_static_model_set('full').get('peppa_wutz').get('size')
 	scale = 195 / numpy.subtract(bounding_box[2:], bounding_box[:2]).max().clip(1, None)
 	translation = (model_size[0] - numpy.add(bounding_box[2:], bounding_box[:2]) * scale) * 0.5
 	rotated_matrix, rotated_size = create_rotated_matrix_and_size(face_angle, model_size)
@@ -167,7 +171,7 @@ def detect_with_peppa_wutz(temp_vision_frame : VisionFrame, bounding_box : Bound
 
 def conditional_optimize_contrast(crop_vision_frame : VisionFrame) -> VisionFrame:
 	crop_vision_frame = cv2.cvtColor(crop_vision_frame, cv2.COLOR_RGB2Lab)
-	if numpy.mean(crop_vision_frame[:, :, 0]) < 30: # type:ignore[arg-type]
+	if numpy.mean(crop_vision_frame[:, :, 0]) < 30: #type:ignore[arg-type]
 		crop_vision_frame[:, :, 0] = cv2.createCLAHE(clipLimit = 2).apply(crop_vision_frame[:, :, 0])
 	crop_vision_frame = cv2.cvtColor(crop_vision_frame, cv2.COLOR_Lab2RGB)
 	return crop_vision_frame

facefusion/face_masker.py

@@ -6,54 +6,11 @@ import numpy
 from cv2.typing import Size
 
 from facefusion import inference_manager
-from facefusion.download import conditional_download_hashes, conditional_download_sources
+from facefusion.download import conditional_download_hashes, conditional_download_sources, resolve_download_url
 from facefusion.filesystem import resolve_relative_path
 from facefusion.thread_helper import conditional_thread_semaphore
-from facefusion.typing import DownloadSet, FaceLandmark68, FaceMaskRegion, InferencePool, Mask, ModelSet, Padding, VisionFrame
+from facefusion.typing import DownloadScope, DownloadSet, FaceLandmark68, FaceMaskRegion, InferencePool, Mask, ModelSet, Padding, VisionFrame
 
-MODEL_SET : ModelSet =\
-{
-	'face_occluder':
-	{
-		'hashes':
-		{
-			'face_occluder':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/dfl_xseg.hash',
-				'path': resolve_relative_path('../.assets/models/dfl_xseg.hash')
-			}
-		},
-		'sources':
-		{
-			'face_occluder':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/dfl_xseg.onnx',
-				'path': resolve_relative_path('../.assets/models/dfl_xseg.onnx')
-			}
-		},
-		'size': (256, 256)
-	},
-	'face_parser':
-	{
-		'hashes':
-		{
-			'face_parser':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/bisenet_resnet_34.hash',
-				'path': resolve_relative_path('../.assets/models/bisenet_resnet_34.hash')
-			}
-		},
-		'sources':
-		{
-			'face_parser':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/bisenet_resnet_34.onnx',
-				'path': resolve_relative_path('../.assets/models/bisenet_resnet_34.onnx')
-			}
-		},
-		'size': (512, 512)
-	}
-}
 FACE_MASK_REGIONS : Dict[FaceMaskRegion, int] =\
 {
 	'skin': 1,
@@ -69,6 +26,53 @@ FACE_MASK_REGIONS : Dict[FaceMaskRegion, int] =\
 }
 
 
+@lru_cache(maxsize = None)
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
+	return\
+	{
+		'face_occluder':
+		{
+			'hashes':
+			{
+				'face_occluder':
+				{
+					'url': resolve_download_url('models-3.1.0', 'xseg_groggy_5.hash'),
+					'path': resolve_relative_path('../.assets/models/xseg_groggy_5.hash')
+				}
+			},
+			'sources':
+			{
+				'face_occluder':
+				{
+					'url': resolve_download_url('models-3.1.0', 'xseg_groggy_5.onnx'),
+					'path': resolve_relative_path('../.assets/models/xseg_groggy_5.onnx')
+				}
+			},
+			'size': (256, 256)
+		},
+		'face_parser':
+		{
+			'hashes':
+			{
+				'face_parser':
+				{
+					'url': resolve_download_url('models-3.0.0', 'bisenet_resnet_34.hash'),
+					'path': resolve_relative_path('../.assets/models/bisenet_resnet_34.hash')
+				}
+			},
+			'sources':
+			{
+				'face_parser':
+				{
+					'url': resolve_download_url('models-3.0.0', 'bisenet_resnet_34.onnx'),
+					'path': resolve_relative_path('../.assets/models/bisenet_resnet_34.onnx')
+				}
+			},
+			'size': (512, 512)
+		}
+	}
+
+
 def get_inference_pool() -> InferencePool:
 	_, model_sources = collect_model_downloads()
 	return inference_manager.get_inference_pool(__name__, model_sources)
@@ -79,24 +83,24 @@ def clear_inference_pool() -> None:
 
 
 def collect_model_downloads() -> Tuple[DownloadSet, DownloadSet]:
+	model_set = create_static_model_set('full')
 	model_hashes =\
 	{
-		'face_occluder': MODEL_SET.get('face_occluder').get('hashes').get('face_occluder'),
-		'face_parser': MODEL_SET.get('face_parser').get('hashes').get('face_parser')
+		'face_occluder': model_set.get('face_occluder').get('hashes').get('face_occluder'),
+		'face_parser': model_set.get('face_parser').get('hashes').get('face_parser')
 	}
 	model_sources =\
 	{
-		'face_occluder': MODEL_SET.get('face_occluder').get('sources').get('face_occluder'),
-		'face_parser': MODEL_SET.get('face_parser').get('sources').get('face_parser')
+		'face_occluder': model_set.get('face_occluder').get('sources').get('face_occluder'),
+		'face_parser': model_set.get('face_parser').get('sources').get('face_parser')
 	}
 	return model_hashes, model_sources
 
 
 def pre_check() -> bool:
-	download_directory_path = resolve_relative_path('../.assets/models')
 	model_hashes, model_sources = collect_model_downloads()
 
-	return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources)
+	return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
 
 
 @lru_cache(maxsize = None)
@@ -114,7 +118,7 @@ def create_static_box_mask(crop_size : Size, face_mask_blur : float, face_mask_p
 
 
 def create_occlusion_mask(crop_vision_frame : VisionFrame) -> Mask:
-	model_size = MODEL_SET.get('face_occluder').get('size')
+	model_size = create_static_model_set('full').get('face_occluder').get('size')
 	prepare_vision_frame = cv2.resize(crop_vision_frame, model_size)
 	prepare_vision_frame = numpy.expand_dims(prepare_vision_frame, axis = 0).astype(numpy.float32) / 255
 	prepare_vision_frame = prepare_vision_frame.transpose(0, 1, 2, 3)
@@ -126,7 +130,7 @@ def create_occlusion_mask(crop_vision_frame : VisionFrame) -> Mask:
 
 
 def create_region_mask(crop_vision_frame : VisionFrame, face_mask_regions : List[FaceMaskRegion]) -> Mask:
-	model_size = MODEL_SET.get('face_parser').get('size')
+	model_size = create_static_model_set('full').get('face_parser').get('size')
 	prepare_vision_frame = cv2.resize(crop_vision_frame, model_size)
 	prepare_vision_frame = prepare_vision_frame[:, :, ::-1].astype(numpy.float32) / 255
 	prepare_vision_frame = numpy.subtract(prepare_vision_frame, numpy.array([ 0.485, 0.456, 0.406 ]).astype(numpy.float32))

facefusion/face_recognizer.py

@@ -1,38 +1,42 @@
+from functools import lru_cache
 from typing import Tuple
 
 import numpy
 
 from facefusion import inference_manager
-from facefusion.download import conditional_download_hashes, conditional_download_sources
+from facefusion.download import conditional_download_hashes, conditional_download_sources, resolve_download_url
 from facefusion.face_helper import warp_face_by_face_landmark_5
 from facefusion.filesystem import resolve_relative_path
 from facefusion.thread_helper import conditional_thread_semaphore
-from facefusion.typing import Embedding, FaceLandmark5, InferencePool, ModelOptions, ModelSet, VisionFrame
+from facefusion.typing import DownloadScope, Embedding, FaceLandmark5, InferencePool, ModelOptions, ModelSet, VisionFrame
 
-MODEL_SET : ModelSet =\
-{
-	'arcface':
+
+@lru_cache(maxsize = None)
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
+	return\
 	{
-		'hashes':
+		'arcface':
 		{
-			'face_recognizer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_w600k_r50.hash',
-				'path': resolve_relative_path('../.assets/models/arcface_w600k_r50.hash')
-			}
-		},
-		'sources':
-		{
-			'face_recognizer':
+				'face_recognizer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'arcface_w600k_r50.hash'),
+					'path': resolve_relative_path('../.assets/models/arcface_w600k_r50.hash')
+				}
+			},
+			'sources':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_w600k_r50.onnx',
-				'path': resolve_relative_path('../.assets/models/arcface_w600k_r50.onnx')
-			}
-		},
-		'template': 'arcface_112_v2',
-		'size': (112, 112)
+				'face_recognizer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'arcface_w600k_r50.onnx'),
+					'path': resolve_relative_path('../.assets/models/arcface_w600k_r50.onnx')
+				}
+			},
+			'template': 'arcface_112_v2',
+			'size': (112, 112)
+		}
 	}
-}
 
 
 def get_inference_pool() -> InferencePool:
@@ -45,15 +49,14 @@ def clear_inference_pool() -> None:
 
 
 def get_model_options() -> ModelOptions:
-	return MODEL_SET.get('arcface')
+	return create_static_model_set('full').get('arcface')
 
 
 def pre_check() -> bool:
-	download_directory_path = resolve_relative_path('../.assets/models')
 	model_hashes = get_model_options().get('hashes')
 	model_sources = get_model_options().get('sources')
 
-	return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources)
+	return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
 
 
 def calc_embedding(temp_vision_frame : VisionFrame, face_landmark_5 : FaceLandmark5) -> Tuple[Embedding, Embedding]:

facefusion/face_selector.py

@@ -33,17 +33,17 @@ def calc_face_distance(face : Face, reference_face : Face) -> float:
 def sort_and_filter_faces(faces : List[Face]) -> List[Face]:
 	if faces:
 		if state_manager.get_item('face_selector_order'):
-			faces = sort_by_order(faces, state_manager.get_item('face_selector_order'))
+			faces = sort_faces_by_order(faces, state_manager.get_item('face_selector_order'))
 		if state_manager.get_item('face_selector_gender'):
-			faces = filter_by_gender(faces, state_manager.get_item('face_selector_gender'))
+			faces = filter_faces_by_gender(faces, state_manager.get_item('face_selector_gender'))
 		if state_manager.get_item('face_selector_race'):
-			faces = filter_by_race(faces, state_manager.get_item('face_selector_race'))
+			faces = filter_faces_by_race(faces, state_manager.get_item('face_selector_race'))
 		if state_manager.get_item('face_selector_age_start') or state_manager.get_item('face_selector_age_end'):
-			faces = filter_by_age(faces, state_manager.get_item('face_selector_age_start'), state_manager.get_item('face_selector_age_end'))
+			faces = filter_faces_by_age(faces, state_manager.get_item('face_selector_age_start'), state_manager.get_item('face_selector_age_end'))
 	return faces
 
 
-def sort_by_order(faces : List[Face], order : FaceSelectorOrder) -> List[Face]:
+def sort_faces_by_order(faces : List[Face], order : FaceSelectorOrder) -> List[Face]:
 	if order == 'left-right':
 		return sorted(faces, key = lambda face: face.bounding_box[0])
 	if order == 'right-left':
@@ -63,7 +63,7 @@ def sort_by_order(faces : List[Face], order : FaceSelectorOrder) -> List[Face]:
 	return faces
 
 
-def filter_by_gender(faces : List[Face], gender : Gender) -> List[Face]:
+def filter_faces_by_gender(faces : List[Face], gender : Gender) -> List[Face]:
 	filter_faces = []
 
 	for face in faces:
@@ -72,7 +72,7 @@ def filter_by_gender(faces : List[Face], gender : Gender) -> List[Face]:
 	return filter_faces
 
 
-def filter_by_age(faces : List[Face], face_selector_age_start : int, face_selector_age_end : int) -> List[Face]:
+def filter_faces_by_age(faces : List[Face], face_selector_age_start : int, face_selector_age_end : int) -> List[Face]:
 	filter_faces = []
 	age = range(face_selector_age_start, face_selector_age_end)
 
@@ -82,7 +82,7 @@ def filter_by_age(faces : List[Face], face_selector_age_start : int, face_select
 	return filter_faces
 
 
-def filter_by_race(faces : List[Face], race : Race) -> List[Face]:
+def filter_faces_by_race(faces : List[Face], race : Race) -> List[Face]:
 	filter_faces = []
 
 	for face in faces:

facefusion/ffmpeg.py

@@ -5,22 +5,48 @@ import tempfile
 from typing import List, Optional
 
 import filetype
+from tqdm import tqdm
 
-from facefusion import logger, process_manager, state_manager
+from facefusion import logger, process_manager, state_manager, wording
 from facefusion.filesystem import remove_file
-from facefusion.temp_helper import get_temp_file_path, get_temp_frames_pattern
-from facefusion.typing import AudioBuffer, Fps, OutputVideoPreset
-from facefusion.vision import restrict_video_fps
+from facefusion.temp_helper import get_temp_file_path, get_temp_frame_paths, get_temp_frames_pattern
+from facefusion.typing import AudioBuffer, Fps, OutputVideoPreset, UpdateProgress
+from facefusion.vision import count_video_frame_total, detect_video_duration, restrict_video_fps
 
 
-def run_ffmpeg(args : List[str]) -> subprocess.Popen[bytes]:
-	commands = [ shutil.which('ffmpeg'), '-hide_banner', '-loglevel', 'error' ]
+def run_ffmpeg_with_progress(args: List[str], update_progress : UpdateProgress) -> subprocess.Popen[bytes]:
+	log_level = state_manager.get_item('log_level')
+	commands = [ shutil.which('ffmpeg'), '-hide_banner', '-nostats', '-loglevel', 'error', '-progress', '-' ]
 	commands.extend(args)
 	process = subprocess.Popen(commands, stderr = subprocess.PIPE, stdout = subprocess.PIPE)
 
 	while process_manager.is_processing():
 		try:
-			if state_manager.get_item('log_level') == 'debug':
+			while line := process.stdout.readline().decode():
+				if 'frame=' in line:
+					_, frame_number = line.split('frame=')
+					update_progress(int(frame_number))
+			if log_level == 'debug':
+				log_debug(process)
+			process.wait(timeout = 0.5)
+		except subprocess.TimeoutExpired:
+			continue
+		return process
+
+	if process_manager.is_stopping():
+		process.terminate()
+	return process
+
+
+def run_ffmpeg(args : List[str]) -> subprocess.Popen[bytes]:
+	log_level = state_manager.get_item('log_level')
+	commands = [ shutil.which('ffmpeg'), '-hide_banner', '-nostats', '-loglevel', 'error' ]
+	commands.extend(args)
+	process = subprocess.Popen(commands, stderr = subprocess.PIPE, stdout = subprocess.PIPE)
+
+	while process_manager.is_processing():
+		try:
+			if log_level == 'debug':
 				log_debug(process)
 			process.wait(timeout = 0.5)
 		except subprocess.TimeoutExpired:
@@ -33,7 +59,7 @@ def run_ffmpeg(args : List[str]) -> subprocess.Popen[bytes]:
 
 
 def open_ffmpeg(args : List[str]) -> subprocess.Popen[bytes]:
-	commands = [ shutil.which('ffmpeg'), '-hide_banner', '-loglevel', 'quiet' ]
+	commands = [ shutil.which('ffmpeg'), '-loglevel', 'quiet' ]
 	commands.extend(args)
 	return subprocess.Popen(commands, stdin = subprocess.PIPE, stdout = subprocess.PIPE)
 
@@ -48,6 +74,7 @@ def log_debug(process : subprocess.Popen[bytes]) -> None:
 
 
 def extract_frames(target_path : str, temp_video_resolution : str, temp_video_fps : Fps) -> bool:
+	extract_frame_total = count_video_frame_total(state_manager.get_item('target_path'))
 	trim_frame_start = state_manager.get_item('trim_frame_start')
 	trim_frame_end = state_manager.get_item('trim_frame_end')
 	temp_frames_pattern = get_temp_frames_pattern(target_path, '%08d')
@@ -55,41 +82,58 @@ def extract_frames(target_path : str, temp_video_resolution : str, temp_video_fp
 
 	if isinstance(trim_frame_start, int) and isinstance(trim_frame_end, int):
 		commands.extend([ '-vf', 'trim=start_frame=' + str(trim_frame_start) + ':end_frame=' + str(trim_frame_end) + ',fps=' + str(temp_video_fps) ])
+		extract_frame_total = trim_frame_end - trim_frame_start
 	elif isinstance(trim_frame_start, int):
 		commands.extend([ '-vf', 'trim=start_frame=' + str(trim_frame_start) + ',fps=' + str(temp_video_fps) ])
+		extract_frame_total -= trim_frame_start
 	elif isinstance(trim_frame_end, int):
 		commands.extend([ '-vf', 'trim=end_frame=' + str(trim_frame_end) + ',fps=' + str(temp_video_fps) ])
+		extract_frame_total -= trim_frame_end
 	else:
 		commands.extend([ '-vf', 'fps=' + str(temp_video_fps) ])
 	commands.extend([ '-vsync', '0', temp_frames_pattern ])
-	return run_ffmpeg(commands).returncode == 0
+
+	with tqdm(total = extract_frame_total, desc = wording.get('extracting'), unit = 'frame', ascii = ' =', disable = state_manager.get_item('log_level') in [ 'warn', 'error' ]) as progress:
+		process = run_ffmpeg_with_progress(commands, lambda frame_number: progress.update(frame_number - progress.n))
+		return process.returncode == 0
 
 
-def merge_video(target_path : str, output_video_resolution : str, output_video_fps : Fps) -> bool:
+def merge_video(target_path : str, output_video_resolution : str, output_video_fps: Fps) -> bool:
+	merge_frame_total = len(get_temp_frame_paths(target_path))
+	output_video_encoder = state_manager.get_item('output_video_encoder')
+	output_video_quality = state_manager.get_item('output_video_quality')
+	output_video_preset = state_manager.get_item('output_video_preset')
 	temp_video_fps = restrict_video_fps(target_path, output_video_fps)
 	temp_file_path = get_temp_file_path(target_path)
 	temp_frames_pattern = get_temp_frames_pattern(target_path, '%08d')
-	commands = [ '-r', str(temp_video_fps), '-i', temp_frames_pattern, '-s', str(output_video_resolution), '-c:v', state_manager.get_item('output_video_encoder') ]
+	is_webm = filetype.guess_mime(target_path) == 'video/webm'
 
-	if state_manager.get_item('output_video_encoder') in [ 'libx264', 'libx265' ]:
-		output_video_compression = round(51 - (state_manager.get_item('output_video_quality') * 0.51))
-		commands.extend([ '-crf', str(output_video_compression), '-preset', state_manager.get_item('output_video_preset') ])
-	if state_manager.get_item('output_video_encoder') in [ 'libvpx-vp9' ]:
-		output_video_compression = round(63 - (state_manager.get_item('output_video_quality') * 0.63))
+	if is_webm:
+		output_video_encoder = 'libvpx-vp9'
+	commands = [ '-r', str(temp_video_fps), '-i', temp_frames_pattern, '-s', str(output_video_resolution), '-c:v', output_video_encoder ]
+	if output_video_encoder in [ 'libx264', 'libx265' ]:
+		output_video_compression = round(51 - (output_video_quality * 0.51))
+		commands.extend([ '-crf', str(output_video_compression), '-preset', output_video_preset ])
+	if output_video_encoder in [ 'libvpx-vp9' ]:
+		output_video_compression = round(63 - (output_video_quality * 0.63))
 		commands.extend([ '-crf', str(output_video_compression) ])
-	if state_manager.get_item('output_video_encoder') in [ 'h264_nvenc', 'hevc_nvenc' ]:
-		output_video_compression = round(51 - (state_manager.get_item('output_video_quality') * 0.51))
-		commands.extend([ '-cq', str(output_video_compression), '-preset', map_nvenc_preset(state_manager.get_item('output_video_preset')) ])
-	if state_manager.get_item('output_video_encoder') in [ 'h264_amf', 'hevc_amf' ]:
-		output_video_compression = round(51 - (state_manager.get_item('output_video_quality') * 0.51))
-		commands.extend([ '-qp_i', str(output_video_compression), '-qp_p', str(output_video_compression), '-quality', map_amf_preset(state_manager.get_item('output_video_preset')) ])
-	if state_manager.get_item('output_video_encoder') in [ 'h264_videotoolbox', 'hevc_videotoolbox' ]:
-		commands.extend([ '-q:v', str(state_manager.get_item('output_video_quality')) ])
+	if output_video_encoder in [ 'h264_nvenc', 'hevc_nvenc' ]:
+		output_video_compression = round(51 - (output_video_quality * 0.51))
+		commands.extend([ '-cq', str(output_video_compression), '-preset', map_nvenc_preset(output_video_preset) ])
+	if output_video_encoder in [ 'h264_amf', 'hevc_amf' ]:
+		output_video_compression = round(51 - (output_video_quality * 0.51))
+		commands.extend([ '-qp_i', str(output_video_compression), '-qp_p', str(output_video_compression), '-quality', map_amf_preset(output_video_preset) ])
+	if output_video_encoder in [ 'h264_videotoolbox', 'hevc_videotoolbox' ]:
+		commands.extend([ '-q:v', str(output_video_quality) ])
 	commands.extend([ '-vf', 'framerate=fps=' + str(output_video_fps), '-pix_fmt', 'yuv420p', '-colorspace', 'bt709', '-y', temp_file_path ])
-	return run_ffmpeg(commands).returncode == 0
+
+	with tqdm(total = merge_frame_total, desc = wording.get('merging'), unit = 'frame', ascii = ' =', disable = state_manager.get_item('log_level') in [ 'warn', 'error' ]) as progress:
+		process = run_ffmpeg_with_progress(commands, lambda frame_number: progress.update(frame_number - progress.n))
+		return process.returncode == 0
 
 
 def concat_video(output_path : str, temp_output_paths : List[str]) -> bool:
+	output_audio_encoder = state_manager.get_item('output_audio_encoder')
 	concat_video_path = tempfile.mktemp()
 
 	with open(concat_video_path, 'w') as concat_video_file:
@@ -97,7 +141,7 @@ def concat_video(output_path : str, temp_output_paths : List[str]) -> bool:
 			concat_video_file.write('file \'' + os.path.abspath(temp_output_path) + '\'' + os.linesep)
 		concat_video_file.flush()
 		concat_video_file.close()
-	commands = [ '-f', 'concat', '-safe', '0', '-i', concat_video_file.name, '-c:v', 'copy', '-c:a', state_manager.get_item('output_audio_encoder'), '-y', os.path.abspath(output_path) ]
+	commands = [ '-f', 'concat', '-safe', '0', '-i', concat_video_file.name, '-c:v', 'copy', '-c:a', output_audio_encoder, '-y', os.path.abspath(output_path) ]
 	process = run_ffmpeg(commands)
 	process.communicate()
 	remove_file(concat_video_path)
@@ -112,8 +156,9 @@ def copy_image(target_path : str, temp_image_resolution : str) -> bool:
 
 
 def finalize_image(target_path : str, output_path : str, output_image_resolution : str) -> bool:
+	output_image_quality = state_manager.get_item('output_image_quality')
 	temp_file_path = get_temp_file_path(target_path)
-	output_image_compression = calc_image_compression(target_path, state_manager.get_item('output_image_quality'))
+	output_image_compression = calc_image_compression(target_path, output_image_quality)
 	commands = [ '-i', temp_file_path, '-s', str(output_image_resolution), '-q:v', str(output_image_compression), '-y', output_path ]
 	return run_ffmpeg(commands).returncode == 0
 
@@ -137,7 +182,9 @@ def read_audio_buffer(target_path : str, sample_rate : int, channel_total : int)
 def restore_audio(target_path : str, output_path : str, output_video_fps : Fps) -> bool:
 	trim_frame_start = state_manager.get_item('trim_frame_start')
 	trim_frame_end = state_manager.get_item('trim_frame_end')
+	output_audio_encoder = state_manager.get_item('output_audio_encoder')
 	temp_file_path = get_temp_file_path(target_path)
+	temp_video_duration = detect_video_duration(temp_file_path)
 	commands = [ '-i', temp_file_path ]
 
 	if isinstance(trim_frame_start, int):
@@ -146,13 +193,15 @@ def restore_audio(target_path : str, output_path : str, output_video_fps : Fps)
 	if isinstance(trim_frame_end, int):
 		end_time = trim_frame_end / output_video_fps
 		commands.extend([ '-to', str(end_time) ])
-	commands.extend([ '-i', target_path, '-c:v', 'copy', '-c:a', state_manager.get_item('output_audio_encoder'), '-map', '0:v:0', '-map', '1:a:0', '-shortest', '-y', output_path ])
+	commands.extend([ '-i', target_path, '-c:v', 'copy', '-c:a', output_audio_encoder, '-map', '0:v:0', '-map', '1:a:0', '-t', str(temp_video_duration), '-y', output_path ])
 	return run_ffmpeg(commands).returncode == 0
 
 
 def replace_audio(target_path : str, audio_path : str, output_path : str) -> bool:
+	output_audio_encoder = state_manager.get_item('output_audio_encoder')
 	temp_file_path = get_temp_file_path(target_path)
-	commands = [ '-i', temp_file_path, '-i', audio_path, '-c:a', state_manager.get_item('output_audio_encoder'), '-af', 'apad', '-shortest', '-y', output_path ]
+	temp_video_duration = detect_video_duration(temp_file_path)
+	commands = [ '-i', temp_file_path, '-i', audio_path, '-c:v', 'copy', '-c:a', output_audio_encoder, '-t', str(temp_video_duration), '-y', output_path ]
 	return run_ffmpeg(commands).returncode == 0
 
 
@@ -174,3 +223,13 @@ def map_amf_preset(output_video_preset : OutputVideoPreset) -> Optional[str]:
 	if output_video_preset in [ 'slow', 'slower', 'veryslow' ]:
 		return 'quality'
 	return None
+
+
+def map_qsv_preset(output_video_preset : OutputVideoPreset) -> Optional[str]:
+	if output_video_preset in [ 'ultrafast', 'superfast', 'veryfast', 'faster', 'fast' ]:
+		return 'fast'
+	if output_video_preset == 'medium':
+		return 'medium'
+	if output_video_preset in [ 'slow', 'slower', 'veryslow' ]:
+		return 'slow'
+	return None

facefusion/filesystem.py

@@ -1,3 +1,4 @@
+import glob
 import os
 import shutil
 from pathlib import Path
@@ -127,12 +128,18 @@ def create_directory(directory_path : str) -> bool:
 
 def list_directory(directory_path : str) -> Optional[List[str]]:
 	if is_directory(directory_path):
-		files = os.listdir(directory_path)
-		files = [ Path(file).stem for file in files if not Path(file).stem.startswith(('.', '__')) ]
-		return sorted(files)
+		file_paths = os.listdir(directory_path)
+		file_paths = [ Path(file_path).stem for file_path in file_paths if not Path(file_path).stem.startswith(('.', '__')) ]
+		return sorted(file_paths)
 	return None
 
 
+def resolve_file_pattern(file_pattern : str) -> List[str]:
+	if in_directory(file_pattern):
+		return sorted(glob.glob(file_pattern))
+	return []
+
+
 def remove_directory(directory_path : str) -> bool:
 	if is_directory(directory_path):
 		shutil.rmtree(directory_path, ignore_errors = True)

facefusion/inference_manager.py

@@ -1,20 +1,18 @@
-from functools import lru_cache
 from time import sleep
 from typing import List
 
-import onnx
 from onnxruntime import InferenceSession
 
 from facefusion import process_manager, state_manager
 from facefusion.app_context import detect_app_context
-from facefusion.execution import create_execution_providers, has_execution_provider
+from facefusion.execution import create_execution_providers
 from facefusion.thread_helper import thread_lock
-from facefusion.typing import DownloadSet, ExecutionProviderKey, InferencePool, InferencePoolSet, ModelInitializer
+from facefusion.typing import DownloadSet, ExecutionProviderKey, InferencePool, InferencePoolSet
 
 INFERENCE_POOLS : InferencePoolSet =\
 {
-	'cli': {}, # type:ignore[typeddict-item]
-	'ui': {} # type:ignore[typeddict-item]
+	'cli': {}, #type:ignore[typeddict-item]
+	'ui': {} #type:ignore[typeddict-item]
 }
 
 
@@ -32,8 +30,7 @@ def get_inference_pool(model_context : str, model_sources : DownloadSet) -> Infe
 		if app_context == 'ui' and INFERENCE_POOLS.get('cli').get(inference_context):
 			INFERENCE_POOLS['ui'][inference_context] = INFERENCE_POOLS.get('cli').get(inference_context)
 		if not INFERENCE_POOLS.get(app_context).get(inference_context):
-			execution_provider_keys = resolve_execution_provider_keys(model_context)
-			INFERENCE_POOLS[app_context][inference_context] = create_inference_pool(model_sources, state_manager.get_item('execution_device_id'), execution_provider_keys)
+			INFERENCE_POOLS[app_context][inference_context] = create_inference_pool(model_sources, state_manager.get_item('execution_device_id'), state_manager.get_item('execution_providers'))
 
 		return INFERENCE_POOLS.get(app_context).get(inference_context)
 
@@ -61,19 +58,6 @@ def create_inference_session(model_path : str, execution_device_id : str, execut
 	return InferenceSession(model_path, providers = execution_providers)
 
 
-@lru_cache(maxsize = None)
-def get_static_model_initializer(model_path : str) -> ModelInitializer:
-	model = onnx.load(model_path)
-	return onnx.numpy_helper.to_array(model.graph.initializer[-1])
-
-
-def resolve_execution_provider_keys(model_context : str) -> List[ExecutionProviderKey]:
-	if has_execution_provider('coreml') and (model_context.startswith('facefusion.processors.modules.age_modifier') or model_context.startswith('facefusion.processors.modules.frame_colorizer')):
-		return [ 'cpu' ]
-	return state_manager.get_item('execution_providers')
-
-
 def get_inference_context(model_context : str) -> str:
-	execution_provider_keys = resolve_execution_provider_keys(model_context)
-	inference_context = model_context + '.' + '_'.join(execution_provider_keys)
+	inference_context = model_context + '.' + '_'.join(state_manager.get_item('execution_providers'))
 	return inference_context

facefusion/installer.py

@@ -13,11 +13,11 @@ from facefusion.common_helper import is_linux, is_macos, is_windows
 ONNXRUNTIMES : Dict[str, Tuple[str, str]] = {}
 
 if is_macos():
-	ONNXRUNTIMES['default'] = ('onnxruntime', '1.19.2')
+	ONNXRUNTIMES['default'] = ('onnxruntime', '1.20.1')
 else:
-	ONNXRUNTIMES['default'] = ('onnxruntime', '1.19.2')
-	ONNXRUNTIMES['cuda'] = ('onnxruntime-gpu', '1.19.2')
-	ONNXRUNTIMES['openvino'] = ('onnxruntime-openvino', '1.19.0')
+	ONNXRUNTIMES['default'] = ('onnxruntime', '1.20.1')
+	ONNXRUNTIMES['cuda'] = ('onnxruntime-gpu', '1.20.1')
+	ONNXRUNTIMES['openvino'] = ('onnxruntime-openvino', '1.20.0')
 if is_linux():
 	ONNXRUNTIMES['rocm'] = ('onnxruntime-rocm', '1.18.0')
 if is_windows():
@@ -72,7 +72,7 @@ def run(program : ArgumentParser) -> None:
 				os.path.join(os.getenv('CONDA_PREFIX'), 'lib'),
 				os.path.join(os.getenv('CONDA_PREFIX'), 'lib', python_id, 'site-packages', 'tensorrt_libs')
 			])
-			library_paths = [ library_path for library_path in library_paths if os.path.exists(library_path) ]
+			library_paths = list(dict.fromkeys([ library_path for library_path in library_paths if os.path.exists(library_path) ]))
 
 			subprocess.call([ shutil.which('conda'), 'env', 'config', 'vars', 'set', 'LD_LIBRARY_PATH=' + os.pathsep.join(library_paths) ])
 
@@ -85,10 +85,9 @@ def run(program : ArgumentParser) -> None:
 				os.path.join(os.getenv('CONDA_PREFIX'), 'Lib'),
 				os.path.join(os.getenv('CONDA_PREFIX'), 'Lib', 'site-packages', 'tensorrt_libs')
 			])
-			library_paths = [ library_path for library_path in library_paths if os.path.exists(library_path) ]
+			library_paths = list(dict.fromkeys([ library_path for library_path in library_paths if os.path.exists(library_path) ]))
 
 			subprocess.call([ shutil.which('conda'), 'env', 'config', 'vars', 'set', 'PATH=' + os.pathsep.join(library_paths) ])
 
 	if onnxruntime_version < '1.19.0':
 		subprocess.call([ shutil.which('pip'), 'install', 'numpy==1.26.4', '--force-reinstall' ])
-	subprocess.call([ shutil.which('pip'), 'install', 'python-multipart==0.0.12', '--force-reinstall' ])

facefusion/jobs/job_manager.py

@@ -1,14 +1,12 @@
-import glob
 import os
 from copy import copy
 from typing import List, Optional
 
 from facefusion.choices import job_statuses
 from facefusion.date_helper import get_current_date_time
-from facefusion.filesystem import create_directory, is_directory, is_file, move_file, remove_directory, remove_file
+from facefusion.filesystem import create_directory, is_directory, is_file, move_file, remove_directory, remove_file, resolve_file_pattern
 from facefusion.jobs.job_helper import get_step_output_path
 from facefusion.json import read_json, write_json
-from facefusion.temp_helper import create_base_directory
 from facefusion.typing import Args, Job, JobSet, JobStatus, JobStep, JobStepStatus
 
 JOBS_PATH : Optional[str] = None
@@ -20,7 +18,6 @@ def init_jobs(jobs_path : str) -> bool:
 	JOBS_PATH = jobs_path
 	job_status_paths = [ os.path.join(JOBS_PATH, job_status) for job_status in job_statuses ]
 
-	create_base_directory()
 	for job_status_path in job_status_paths:
 		create_directory(job_status_path)
 	return all(is_directory(status_path) for status_path in job_status_paths)
@@ -88,12 +85,12 @@ def find_jobs(job_status : JobStatus) -> JobSet:
 
 def find_job_ids(job_status : JobStatus) -> List[str]:
 	job_pattern = os.path.join(JOBS_PATH, job_status, '*.json')
-	job_files = glob.glob(job_pattern)
-	job_files.sort(key = os.path.getmtime)
+	job_paths = resolve_file_pattern(job_pattern)
+	job_paths.sort(key = os.path.getmtime)
 	job_ids = []
 
-	for job_file in job_files:
-		job_id, _ = os.path.splitext(os.path.basename(job_file))
+	for job_path in job_paths:
+		job_id, _ = os.path.splitext(os.path.basename(job_path))
 		job_ids.append(job_id)
 	return job_ids
 
@@ -250,7 +247,7 @@ def find_job_path(job_id : str) -> Optional[str]:
 	if job_file_name:
 		for job_status in job_statuses:
 			job_pattern = os.path.join(JOBS_PATH, job_status, job_file_name)
-			job_paths = glob.glob(job_pattern)
+			job_paths = resolve_file_pattern(job_pattern)
 
 			for job_path in job_paths:
 				return job_path

facefusion/metadata.py

@@ -4,7 +4,7 @@ METADATA =\
 {
 	'name': 'FaceFusion',
 	'description': 'Industry leading face manipulation platform',
-	'version': '3.0.1',
+	'version': 'NEXT',
 	'license': 'MIT',
 	'author': 'Henry Ruhs',
 	'url': 'https://facefusion.io'

facefusion/model_helper.py

@@ -0,0 +1,11 @@
+from functools import lru_cache
+
+import onnx
+
+from facefusion.typing import ModelInitializer
+
+
+@lru_cache(maxsize = None)
+def get_static_model_initializer(model_path : str) -> ModelInitializer:
+	model = onnx.load(model_path)
+	return onnx.numpy_helper.to_array(model.graph.initializer[-1])

facefusion/processors/choices.py

@@ -1,9 +1,158 @@
 from typing import List, Sequence
 
 from facefusion.common_helper import create_float_range, create_int_range
-from facefusion.processors.typing import AgeModifierModel, ExpressionRestorerModel, FaceDebuggerItem, FaceEditorModel, FaceEnhancerModel, FaceSwapperSet, FrameColorizerModel, FrameEnhancerModel, LipSyncerModel
+from facefusion.processors.typing import AgeModifierModel, DeepSwapperModel, ExpressionRestorerModel, FaceDebuggerItem, FaceEditorModel, FaceEnhancerModel, FaceSwapperSet, FrameColorizerModel, FrameEnhancerModel, LipSyncerModel
 
 age_modifier_models : List[AgeModifierModel] = [ 'styleganex_age' ]
+deep_swapper_models : List[DeepSwapperModel] =\
+[
+	'druuzil/adrianne_palicki_384',
+	'druuzil/agnetha_falskog_224',
+	'druuzil/alan_ritchson_320',
+	'druuzil/alicia_vikander_320',
+	'druuzil/amber_midthunder_320',
+	'druuzil/andras_arato_384',
+	'druuzil/andrew_tate_320',
+	'druuzil/anne_hathaway_320',
+	'druuzil/anya_chalotra_320',
+	'druuzil/arnold_schwarzenegger_320',
+	'druuzil/benjamin_affleck_320',
+	'druuzil/benjamin_stiller_384',
+	'druuzil/bradley_pitt_224',
+	'druuzil/bryan_cranston_320',
+	'druuzil/catherine_blanchett_352',
+	'druuzil/christian_bale_320',
+	'druuzil/christopher_hemsworth_320',
+	'druuzil/christoph_waltz_384',
+	'druuzil/cillian_murphy_320',
+	'druuzil/cobie_smulders_256',
+	'druuzil/dwayne_johnson_384',
+	'druuzil/edward_norton_320',
+	'druuzil/elisabeth_shue_320',
+	'druuzil/elizabeth_olsen_384',
+	'druuzil/elon_musk_320',
+	'druuzil/emily_blunt_320',
+	'druuzil/emma_stone_384',
+	'druuzil/emma_watson_320',
+	'druuzil/erin_moriarty_384',
+	'druuzil/eva_green_320',
+	'druuzil/ewan_mcgregor_320',
+	'druuzil/florence_pugh_320',
+	'druuzil/freya_allan_320',
+	'druuzil/gary_cole_224',
+	'druuzil/gigi_hadid_224',
+	'druuzil/harrison_ford_384',
+	'druuzil/hayden_christensen_320',
+	'druuzil/heath_ledger_320',
+	'druuzil/henry_cavill_448',
+	'druuzil/hugh_jackman_384',
+	'druuzil/idris_elba_320',
+	'druuzil/jack_nicholson_320',
+	'druuzil/james_mcavoy_320',
+	'druuzil/james_varney_320',
+	'druuzil/jason_momoa_320',
+	'druuzil/jason_statham_320',
+	'druuzil/jennifer_connelly_384',
+	'druuzil/jimmy_donaldson_320',
+	'druuzil/jordan_peterson_384',
+	'druuzil/karl_urban_224',
+	'druuzil/kate_beckinsale_384',
+	'druuzil/laurence_fishburne_384',
+	'druuzil/lili_reinhart_320',
+	'druuzil/mads_mikkelsen_384',
+	'druuzil/mary_winstead_320',
+	'druuzil/melina_juergens_320',
+	'druuzil/michael_fassbender_320',
+	'druuzil/michael_fox_320',
+	'druuzil/millie_bobby_brown_320',
+	'druuzil/morgan_freeman_320',
+	'druuzil/patrick_stewart_320',
+	'druuzil/rebecca_ferguson_320',
+	'druuzil/scarlett_johansson_320',
+	'druuzil/seth_macfarlane_384',
+	'druuzil/thomas_cruise_320',
+	'druuzil/thomas_hanks_384',
+	'edel/emma_roberts_224',
+	'edel/ivanka_trump_224',
+	'edel/lize_dzjabrailova_224',
+	'edel/sidney_sweeney_224',
+	'edel/winona_ryder_224',
+	'iperov/alexandra_daddario_224',
+	'iperov/alexei_navalny_224',
+	'iperov/amber_heard_224',
+	'iperov/dilraba_dilmurat_224',
+	'iperov/elon_musk_224',
+	'iperov/emilia_clarke_224',
+	'iperov/emma_watson_224',
+	'iperov/erin_moriarty_224',
+	'iperov/jackie_chan_224',
+	'iperov/james_carrey_224',
+	'iperov/jason_statham_320',
+	'iperov/keanu_reeves_320',
+	'iperov/margot_robbie_224',
+	'iperov/natalie_dormer_224',
+	'iperov/nicolas_coppola_224',
+	'iperov/robert_downey_224',
+	'iperov/rowan_atkinson_224',
+	'iperov/ryan_reynolds_224',
+	'iperov/scarlett_johansson_224',
+	'iperov/sylvester_stallone_224',
+	'iperov/thomas_cruise_224',
+	'iperov/thomas_holland_224',
+	'iperov/vin_diesel_224',
+	'iperov/vladimir_putin_224',
+	'jen/angelica_trae_288',
+	'jen/ella_freya_224',
+	'jen/emma_myers_320',
+	'jen/evie_pickerill_224',
+	'jen/kang_hyewon_320',
+	'jen/maddie_mead_224',
+	'jen/nicole_turnbull_288',
+	'mats/alica_schmidt_320',
+	'mats/ashley_alexiss_224',
+	'mats/billie_eilish_224',
+	'mats/brie_larson_224',
+	'mats/cara_delevingne_224',
+	'mats/carolin_kebekus_224',
+	'mats/chelsea_clinton_224',
+	'mats/claire_boucher_224',
+	'mats/corinna_kopf_224',
+	'mats/florence_pugh_224',
+	'mats/hillary_clinton_224',
+	'mats/jenna_fischer_224',
+	'mats/kim_jisoo_320',
+	'mats/mica_suarez_320',
+	'mats/shailene_woodley_224',
+	'mats/shraddha_kapoor_320',
+	'mats/yu_jimin_352',
+	'rumateus/alison_brie_224',
+	'rumateus/amber_heard_224',
+	'rumateus/angelina_jolie_224',
+	'rumateus/aubrey_plaza_224',
+	'rumateus/bridget_regan_224',
+	'rumateus/cobie_smulders_224',
+	'rumateus/deborah_woll_224',
+	'rumateus/dua_lipa_224',
+	'rumateus/emma_stone_224',
+	'rumateus/hailee_steinfeld_224',
+	'rumateus/hilary_duff_224',
+	'rumateus/jessica_alba_224',
+	'rumateus/jessica_biel_224',
+	'rumateus/john_cena_224',
+	'rumateus/kim_kardashian_224',
+	'rumateus/kristen_bell_224',
+	'rumateus/lucy_liu_224',
+	'rumateus/margot_robbie_224',
+	'rumateus/megan_fox_224',
+	'rumateus/meghan_markle_224',
+	'rumateus/millie_bobby_brown_224',
+	'rumateus/natalie_portman_224',
+	'rumateus/nicki_minaj_224',
+	'rumateus/olivia_wilde_224',
+	'rumateus/shay_mitchell_224',
+	'rumateus/sophie_turner_224',
+	'rumateus/taylor_swift_224'
+]
 expression_restorer_models : List[ExpressionRestorerModel] = [ 'live_portrait' ]
 face_debugger_items : List[FaceDebuggerItem] = [ 'bounding-box', 'face-landmark-5', 'face-landmark-5/68', 'face-landmark-68', 'face-landmark-68/5', 'face-mask', 'face-detector-score', 'face-landmarker-score', 'age', 'gender', 'race' ]
 face_editor_models : List[FaceEditorModel] = [ 'live_portrait' ]
@@ -14,6 +163,7 @@ face_swapper_set : FaceSwapperSet =\
 	'ghost_1_256': [ '256x256', '512x512', '768x768', '1024x1024' ],
 	'ghost_2_256': [ '256x256', '512x512', '768x768', '1024x1024' ],
 	'ghost_3_256': [ '256x256', '512x512', '768x768', '1024x1024' ],
+	'hififace_unofficial_256': [ '256x256', '512x512', '768x768', '1024x1024' ],
 	'inswapper_128': [ '128x128', '256x256', '384x384', '512x512', '768x768', '1024x1024' ],
 	'inswapper_128_fp16': [ '128x128', '256x256', '384x384', '512x512', '768x768', '1024x1024' ],
 	'simswap_256': [ '256x256', '512x512', '768x768', '1024x1024' ],
@@ -22,10 +172,11 @@ face_swapper_set : FaceSwapperSet =\
 }
 frame_colorizer_models : List[FrameColorizerModel] = [ 'ddcolor', 'ddcolor_artistic', 'deoldify', 'deoldify_artistic', 'deoldify_stable' ]
 frame_colorizer_sizes : List[str] = [ '192x192', '256x256', '384x384', '512x512' ]
-frame_enhancer_models : List[FrameEnhancerModel] = [ 'clear_reality_x4', 'lsdir_x4', 'nomos8k_sc_x4', 'real_esrgan_x2', 'real_esrgan_x2_fp16', 'real_esrgan_x4', 'real_esrgan_x4_fp16', 'real_esrgan_x8', 'real_esrgan_x8_fp16', 'real_hatgan_x4', 'span_kendata_x4', 'ultra_sharp_x4' ]
+frame_enhancer_models : List[FrameEnhancerModel] = [ 'clear_reality_x4', 'lsdir_x4', 'nomos8k_sc_x4', 'real_esrgan_x2', 'real_esrgan_x2_fp16', 'real_esrgan_x4', 'real_esrgan_x4_fp16', 'real_esrgan_x8', 'real_esrgan_x8_fp16', 'real_hatgan_x4', 'real_web_photo_x4', 'realistic_rescaler_x4', 'remacri_x4', 'siax_x4', 'span_kendata_x4', 'swin2_sr_x4', 'ultra_sharp_x4' ]
 lip_syncer_models : List[LipSyncerModel] = [ 'wav2lip_96', 'wav2lip_gan_96' ]
 
 age_modifier_direction_range : Sequence[int] = create_int_range(-100, 100, 1)
+deep_swapper_morph_range : Sequence[int] = create_int_range(0, 100, 1)
 expression_restorer_factor_range : Sequence[int] = create_int_range(0, 100, 1)
 face_editor_eyebrow_direction_range : Sequence[float] = create_float_range(-1.0, 1.0, 0.05)
 face_editor_eye_gaze_horizontal_range : Sequence[float] = create_float_range(-1.0, 1.0, 0.05)
@@ -42,5 +193,6 @@ face_editor_head_pitch_range : Sequence[float] = create_float_range(-1.0, 1.0, 0
 face_editor_head_yaw_range : Sequence[float] = create_float_range(-1.0, 1.0, 0.05)
 face_editor_head_roll_range : Sequence[float] = create_float_range(-1.0, 1.0, 0.05)
 face_enhancer_blend_range : Sequence[int] = create_int_range(0, 100, 1)
+face_enhancer_weight_range : Sequence[float] = create_float_range(0.0, 1.0, 0.05)
 frame_colorizer_blend_range : Sequence[int] = create_int_range(0, 100, 1)
 frame_enhancer_blend_range : Sequence[int] = create_int_range(0, 100, 1)

facefusion/processors/core.py

@@ -53,21 +53,10 @@ def get_processors_modules(processors : List[str]) -> List[ModuleType]:
 	return processor_modules
 
 
-def clear_processors_modules(processors : List[str]) -> None:
-	for processor in processors:
-		processor_module = load_processor_module(processor)
-		processor_module.clear_inference_pool()
-
-
 def multi_process_frames(source_paths : List[str], temp_frame_paths : List[str], process_frames : ProcessFrames) -> None:
 	queue_payloads = create_queue_payloads(temp_frame_paths)
 	with tqdm(total = len(queue_payloads), desc = wording.get('processing'), unit = 'frame', ascii = ' =', disable = state_manager.get_item('log_level') in [ 'warn', 'error' ]) as progress:
-		progress.set_postfix(
-		{
-			'execution_providers': state_manager.get_item('execution_providers'),
-			'execution_thread_count': state_manager.get_item('execution_thread_count'),
-			'execution_queue_count': state_manager.get_item('execution_queue_count')
-		})
+		progress.set_postfix(execution_providers = state_manager.get_item('execution_providers'))
 		with ThreadPoolExecutor(max_workers = state_manager.get_item('execution_thread_count')) as executor:
 			futures = []
 			queue : Queue[QueuePayload] = create_queue(queue_payloads)

facefusion/processors/modules/age_modifier.py

@@ -1,17 +1,18 @@
 from argparse import ArgumentParser
-from typing import Any, List
+from functools import lru_cache
+from typing import List
 
 import cv2
 import numpy
-from cv2.typing import Size
-from numpy.typing import NDArray
 
 import facefusion.jobs.job_manager
 import facefusion.jobs.job_store
 import facefusion.processors.core as processors
 from facefusion import config, content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer, inference_manager, logger, process_manager, state_manager, wording
+from facefusion.choices import execution_provider_set
 from facefusion.common_helper import create_int_metavar
-from facefusion.download import conditional_download_hashes, conditional_download_sources
+from facefusion.download import conditional_download_hashes, conditional_download_sources, resolve_download_url
+from facefusion.execution import has_execution_provider
 from facefusion.face_analyser import get_many_faces, get_one_face
 from facefusion.face_helper import merge_matrix, paste_back, scale_face_landmark_5, warp_face_by_face_landmark_5
 from facefusion.face_masker import create_occlusion_mask, create_static_box_mask
@@ -19,36 +20,47 @@ from facefusion.face_selector import find_similar_faces, sort_and_filter_faces
 from facefusion.face_store import get_reference_faces
 from facefusion.filesystem import in_directory, is_image, is_video, resolve_relative_path, same_file_extension
 from facefusion.processors import choices as processors_choices
-from facefusion.processors.typing import AgeModifierInputs
+from facefusion.processors.typing import AgeModifierDirection, AgeModifierInputs
 from facefusion.program_helper import find_argument_group
 from facefusion.thread_helper import thread_semaphore
-from facefusion.typing import ApplyStateItem, Args, Face, InferencePool, Mask, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
-from facefusion.vision import read_image, read_static_image, write_image
+from facefusion.typing import ApplyStateItem, Args, DownloadScope, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
+from facefusion.vision import match_frame_color, read_image, read_static_image, write_image
 
-MODEL_SET : ModelSet =\
-{
-	'styleganex_age':
+
+@lru_cache(maxsize = None)
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
+	return\
 	{
-		'hashes':
+		'styleganex_age':
 		{
-			'age_modifier':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/styleganex_age.hash',
-				'path': resolve_relative_path('../.assets/models/styleganex_age.hash')
-			}
-		},
-		'sources':
-		{
-			'age_modifier':
+				'age_modifier':
+				{
+					'url': resolve_download_url('models-3.1.0', 'styleganex_age.hash'),
+					'path': resolve_relative_path('../.assets/models/styleganex_age.hash')
+				}
+			},
+			'sources':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/styleganex_age.onnx',
-				'path': resolve_relative_path('../.assets/models/styleganex_age.onnx')
+				'age_modifier':
+				{
+					'url': resolve_download_url('models-3.1.0', 'styleganex_age.onnx'),
+					'path': resolve_relative_path('../.assets/models/styleganex_age.onnx')
+				}
+			},
+			'templates':
+			{
+				'target': 'ffhq_512',
+				'target_with_background': 'styleganex_384'
+			},
+			'sizes':
+			{
+				'target': (256, 256),
+				'target_with_background': (384, 384)
 			}
-		},
-		'template': 'ffhq_512',
-		'size': (512, 512)
+		}
 	}
-}
 
 
 def get_inference_pool() -> InferencePool:
@@ -64,7 +76,7 @@ def clear_inference_pool() -> None:
 
 def get_model_options() -> ModelOptions:
 	age_modifier_model = state_manager.get_item('age_modifier_model')
-	return MODEL_SET.get(age_modifier_model)
+	return create_static_model_set('full').get(age_modifier_model)
 
 
 def register_args(program : ArgumentParser) -> None:
@@ -81,11 +93,10 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
 
 
 def pre_check() -> bool:
-	download_directory_path = resolve_relative_path('../.assets/models')
 	model_hashes = get_model_options().get('hashes')
 	model_sources = get_model_options().get('sources')
 
-	return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources)
+	return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
 
 
 def pre_process(mode : ProcessMode) -> bool:
@@ -115,15 +126,14 @@ def post_process() -> None:
 
 
 def modify_age(target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame:
-	model_template = get_model_options().get('template')
-	model_size = get_model_options().get('size')
-	crop_size = (model_size[0] // 2, model_size[1] // 2)
+	model_templates = get_model_options().get('templates')
+	model_sizes = get_model_options().get('sizes')
 	face_landmark_5 = target_face.landmark_set.get('5/68').copy()
-	extend_face_landmark_5 = scale_face_landmark_5(face_landmark_5, 2.0)
-	crop_vision_frame, affine_matrix = warp_face_by_face_landmark_5(temp_vision_frame, face_landmark_5, model_template, crop_size)
-	extend_vision_frame, extend_affine_matrix = warp_face_by_face_landmark_5(temp_vision_frame, extend_face_landmark_5, model_template, model_size)
+	crop_vision_frame, affine_matrix = warp_face_by_face_landmark_5(temp_vision_frame, face_landmark_5, model_templates.get('target'), model_sizes.get('target'))
+	extend_face_landmark_5 = scale_face_landmark_5(face_landmark_5, 0.875)
+	extend_vision_frame, extend_affine_matrix = warp_face_by_face_landmark_5(temp_vision_frame, extend_face_landmark_5, model_templates.get('target_with_background'), model_sizes.get('target_with_background'))
 	extend_vision_frame_raw = extend_vision_frame.copy()
-	box_mask = create_static_box_mask(model_size, state_manager.get_item('face_mask_blur'), (0, 0, 0, 0))
+	box_mask = create_static_box_mask(model_sizes.get('target_with_background'), state_manager.get_item('face_mask_blur'), (0, 0, 0, 0))
 	crop_masks =\
 	[
 		box_mask
@@ -132,31 +142,36 @@ def modify_age(target_face : Face, temp_vision_frame : VisionFrame) -> VisionFra
 	if 'occlusion' in state_manager.get_item('face_mask_types'):
 		occlusion_mask = create_occlusion_mask(crop_vision_frame)
 		combined_matrix = merge_matrix([ extend_affine_matrix, cv2.invertAffineTransform(affine_matrix) ])
-		occlusion_mask = cv2.warpAffine(occlusion_mask, combined_matrix, model_size)
+		occlusion_mask = cv2.warpAffine(occlusion_mask, combined_matrix, model_sizes.get('target_with_background'))
 		crop_masks.append(occlusion_mask)
 
 	crop_vision_frame = prepare_vision_frame(crop_vision_frame)
 	extend_vision_frame = prepare_vision_frame(extend_vision_frame)
-	extend_vision_frame = forward(crop_vision_frame, extend_vision_frame)
+	age_modifier_direction = numpy.array(numpy.interp(state_manager.get_item('age_modifier_direction'), [-100, 100], [2.5, -2.5])).astype(numpy.float32)
+	extend_vision_frame = forward(crop_vision_frame, extend_vision_frame, age_modifier_direction)
 	extend_vision_frame = normalize_extend_frame(extend_vision_frame)
-	extend_vision_frame = fix_color(extend_vision_frame_raw, extend_vision_frame)
-	extend_crop_mask = cv2.pyrUp(numpy.minimum.reduce(crop_masks).clip(0, 1))
-	extend_affine_matrix *= extend_vision_frame.shape[0] / 512
-	paste_vision_frame = paste_back(temp_vision_frame, extend_vision_frame, extend_crop_mask, extend_affine_matrix)
+	extend_vision_frame = match_frame_color(extend_vision_frame_raw, extend_vision_frame)
+	extend_affine_matrix *= (model_sizes.get('target')[0] * 4) / model_sizes.get('target_with_background')[0]
+	crop_mask = numpy.minimum.reduce(crop_masks).clip(0, 1)
+	crop_mask = cv2.resize(crop_mask, (model_sizes.get('target')[0] * 4, model_sizes.get('target')[1] * 4))
+	paste_vision_frame = paste_back(temp_vision_frame, extend_vision_frame, crop_mask, extend_affine_matrix)
 	return paste_vision_frame
 
 
-def forward(crop_vision_frame : VisionFrame, extend_vision_frame : VisionFrame) -> VisionFrame:
+def forward(crop_vision_frame : VisionFrame, extend_vision_frame : VisionFrame, age_modifier_direction : AgeModifierDirection) -> VisionFrame:
 	age_modifier = get_inference_pool().get('age_modifier')
 	age_modifier_inputs = {}
 
+	if has_execution_provider('coreml'):
+		age_modifier.set_providers([ execution_provider_set.get('cpu') ])
+
 	for age_modifier_input in age_modifier.get_inputs():
 		if age_modifier_input.name == 'target':
 			age_modifier_inputs[age_modifier_input.name] = crop_vision_frame
 		if age_modifier_input.name == 'target_with_background':
 			age_modifier_inputs[age_modifier_input.name] = extend_vision_frame
 		if age_modifier_input.name == 'direction':
-			age_modifier_inputs[age_modifier_input.name] = prepare_direction(state_manager.get_item('age_modifier_direction'))
+			age_modifier_inputs[age_modifier_input.name] = age_modifier_direction
 
 	with thread_semaphore():
 		crop_vision_frame = age_modifier.run(None, age_modifier_inputs)[0][0]
@@ -164,38 +179,6 @@ def forward(crop_vision_frame : VisionFrame, extend_vision_frame : VisionFrame)
 	return crop_vision_frame
 
 
-def fix_color(extend_vision_frame_raw : VisionFrame, extend_vision_frame : VisionFrame) -> VisionFrame:
-	color_difference = compute_color_difference(extend_vision_frame_raw, extend_vision_frame, (48, 48))
-	color_difference_mask = create_static_box_mask(extend_vision_frame.shape[:2][::-1], 1.0, (0, 0, 0, 0))
-	color_difference_mask = numpy.stack((color_difference_mask, ) * 3, axis = -1)
-	extend_vision_frame = normalize_color_difference(color_difference, color_difference_mask, extend_vision_frame)
-	return extend_vision_frame
-
-
-def compute_color_difference(extend_vision_frame_raw : VisionFrame, extend_vision_frame : VisionFrame, size : Size) -> VisionFrame:
-	extend_vision_frame_raw = extend_vision_frame_raw.astype(numpy.float32) / 255
-	extend_vision_frame_raw = cv2.resize(extend_vision_frame_raw, size, interpolation = cv2.INTER_AREA)
-	extend_vision_frame = extend_vision_frame.astype(numpy.float32) / 255
-	extend_vision_frame = cv2.resize(extend_vision_frame, size, interpolation = cv2.INTER_AREA)
-	color_difference = extend_vision_frame_raw - extend_vision_frame
-	return color_difference
-
-
-def normalize_color_difference(color_difference : VisionFrame, color_difference_mask : Mask, extend_vision_frame : VisionFrame) -> VisionFrame:
-	color_difference = cv2.resize(color_difference, extend_vision_frame.shape[:2][::-1], interpolation = cv2.INTER_CUBIC)
-	color_difference_mask = 1 - color_difference_mask.clip(0, 0.75)
-	extend_vision_frame = extend_vision_frame.astype(numpy.float32) / 255
-	extend_vision_frame += color_difference * color_difference_mask
-	extend_vision_frame = extend_vision_frame.clip(0, 1)
-	extend_vision_frame = numpy.multiply(extend_vision_frame, 255).astype(numpy.uint8)
-	return extend_vision_frame
-
-
-def prepare_direction(direction : int) -> NDArray[Any]:
-	direction = numpy.interp(float(direction), [ -100, 100 ], [ 2.5, -2.5 ]) #type:ignore[assignment]
-	return numpy.array(direction).astype(numpy.float32)
-
-
 def prepare_vision_frame(vision_frame : VisionFrame) -> VisionFrame:
 	vision_frame = vision_frame[:, :, ::-1] / 255.0
 	vision_frame = (vision_frame - 0.5) / 0.5
@@ -204,12 +187,13 @@ def prepare_vision_frame(vision_frame : VisionFrame) -> VisionFrame:
 
 
 def normalize_extend_frame(extend_vision_frame : VisionFrame) -> VisionFrame:
+	model_sizes = get_model_options().get('sizes')
 	extend_vision_frame = numpy.clip(extend_vision_frame, -1, 1)
 	extend_vision_frame = (extend_vision_frame + 1) / 2
 	extend_vision_frame = extend_vision_frame.transpose(1, 2, 0).clip(0, 255)
 	extend_vision_frame = (extend_vision_frame * 255.0)
 	extend_vision_frame = extend_vision_frame.astype(numpy.uint8)[:, :, ::-1]
-	extend_vision_frame = cv2.pyrDown(extend_vision_frame)
+	extend_vision_frame = cv2.resize(extend_vision_frame, (model_sizes.get('target')[0] * 4, model_sizes.get('target')[1] * 4), interpolation = cv2.INTER_AREA)
 	return extend_vision_frame
 
 

facefusion/processors/modules/deep_swapper.py

@@ -0,0 +1,409 @@
+from argparse import ArgumentParser
+from functools import lru_cache
+from typing import List, Tuple
+
+import cv2
+import numpy
+
+import facefusion.jobs.job_manager
+import facefusion.jobs.job_store
+import facefusion.processors.core as processors
+from facefusion import config, content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer, inference_manager, logger, process_manager, state_manager, wording
+from facefusion.common_helper import create_int_metavar
+from facefusion.download import conditional_download_hashes, conditional_download_sources, resolve_download_url_by_provider
+from facefusion.face_analyser import get_many_faces, get_one_face
+from facefusion.face_helper import paste_back, warp_face_by_face_landmark_5
+from facefusion.face_masker import create_occlusion_mask, create_static_box_mask
+from facefusion.face_selector import find_similar_faces, sort_and_filter_faces
+from facefusion.face_store import get_reference_faces
+from facefusion.filesystem import in_directory, is_image, is_video, resolve_relative_path, same_file_extension
+from facefusion.processors import choices as processors_choices
+from facefusion.processors.typing import DeepSwapperInputs, DeepSwapperMorph
+from facefusion.program_helper import find_argument_group
+from facefusion.thread_helper import thread_semaphore
+from facefusion.typing import ApplyStateItem, Args, DownloadScope, Face, InferencePool, Mask, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
+from facefusion.vision import conditional_match_frame_color, read_image, read_static_image, write_image
+
+
+@lru_cache(maxsize = None)
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
+	model_config = []
+
+	if download_scope == 'full':
+		model_config.extend(
+		[
+			('druuzil', 'adrianne_palicki_384', (384, 384)),
+			('druuzil', 'agnetha_falskog_224', (224, 224)),
+			('druuzil', 'alan_ritchson_320', (320, 320)),
+			('druuzil', 'alicia_vikander_320', (320, 320)),
+			('druuzil', 'amber_midthunder_320', (320, 320)),
+			('druuzil', 'andras_arato_384', (384, 384)),
+			('druuzil', 'andrew_tate_320', (320, 320)),
+			('druuzil', 'anne_hathaway_320', (320, 320)),
+			('druuzil', 'anya_chalotra_320', (320, 320)),
+			('druuzil', 'arnold_schwarzenegger_320', (320, 320)),
+			('druuzil', 'benjamin_affleck_320', (320, 320)),
+			('druuzil', 'benjamin_stiller_384', (384, 384)),
+			('druuzil', 'bradley_pitt_224', (224, 224)),
+			('druuzil', 'bryan_cranston_320', (320, 320)),
+			('druuzil', 'catherine_blanchett_352', (352, 352)),
+			('druuzil', 'christian_bale_320', (320, 320)),
+			('druuzil', 'christopher_hemsworth_320', (320, 320)),
+			('druuzil', 'christoph_waltz_384', (384, 384)),
+			('druuzil', 'cillian_murphy_320', (320, 320)),
+			('druuzil', 'cobie_smulders_256', (256, 256)),
+			('druuzil', 'dwayne_johnson_384', (384, 384)),
+			('druuzil', 'edward_norton_320', (320, 320)),
+			('druuzil', 'elisabeth_shue_320', (320, 320)),
+			('druuzil', 'elizabeth_olsen_384', (384, 384)),
+			('druuzil', 'elon_musk_320', (320, 320)),
+			('druuzil', 'emily_blunt_320', (320, 320)),
+			('druuzil', 'emma_stone_384', (384, 384)),
+			('druuzil', 'emma_watson_320', (320, 320)),
+			('druuzil', 'erin_moriarty_384', (384, 384)),
+			('druuzil', 'eva_green_320', (320, 320)),
+			('druuzil', 'ewan_mcgregor_320', (320, 320)),
+			('druuzil', 'florence_pugh_320', (320, 320)),
+			('druuzil', 'freya_allan_320', (320, 320)),
+			('druuzil', 'gary_cole_224', (224, 224)),
+			('druuzil', 'gigi_hadid_224', (224, 224)),
+			('druuzil', 'harrison_ford_384', (384, 384)),
+			('druuzil', 'hayden_christensen_320', (320, 320)),
+			('druuzil', 'heath_ledger_320', (320, 320)),
+			('druuzil', 'henry_cavill_448', (448, 448)),
+			('druuzil', 'hugh_jackman_384', (384, 384)),
+			('druuzil', 'idris_elba_320', (320, 320)),
+			('druuzil', 'jack_nicholson_320', (320, 320)),
+			('druuzil', 'james_mcavoy_320', (320, 320)),
+			('druuzil', 'james_varney_320', (320, 320)),
+			('druuzil', 'jason_momoa_320', (320, 320)),
+			('druuzil', 'jason_statham_320', (320, 320)),
+			('druuzil', 'jennifer_connelly_384', (384, 384)),
+			('druuzil', 'jimmy_donaldson_320', (320, 320)),
+			('druuzil', 'jordan_peterson_384', (384, 384)),
+			('druuzil', 'karl_urban_224', (224, 224)),
+			('druuzil', 'kate_beckinsale_384', (384, 384)),
+			('druuzil', 'laurence_fishburne_384', (384, 384)),
+			('druuzil', 'lili_reinhart_320', (320, 320)),
+			('druuzil', 'mads_mikkelsen_384', (384, 384)),
+			('druuzil', 'mary_winstead_320', (320, 320)),
+			('druuzil', 'melina_juergens_320', (320, 320)),
+			('druuzil', 'michael_fassbender_320', (320, 320)),
+			('druuzil', 'michael_fox_320', (320, 320)),
+			('druuzil', 'millie_bobby_brown_320', (320, 320)),
+			('druuzil', 'morgan_freeman_320', (320, 320)),
+			('druuzil', 'patrick_stewart_320', (320, 320)),
+			('druuzil', 'rebecca_ferguson_320', (320, 320)),
+			('druuzil', 'scarlett_johansson_320', (320, 320)),
+			('druuzil', 'seth_macfarlane_384', (384, 384)),
+			('druuzil', 'thomas_cruise_320', (320, 320)),
+			('druuzil', 'thomas_hanks_384', (384, 384)),
+			('edel', 'emma_roberts_224', (224, 224)),
+			('edel', 'ivanka_trump_224', (224, 224)),
+			('edel', 'lize_dzjabrailova_224', (224, 224)),
+			('edel', 'sidney_sweeney_224', (224, 224)),
+			('edel', 'winona_ryder_224', (224, 224))
+		])
+	if download_scope in [ 'lite', 'full' ]:
+		model_config.extend(
+		[
+			('iperov', 'alexandra_daddario_224', (224, 224)),
+			('iperov', 'alexei_navalny_224', (224, 224)),
+			('iperov', 'amber_heard_224', (224, 224)),
+			('iperov', 'dilraba_dilmurat_224', (224, 224)),
+			('iperov', 'elon_musk_224', (224, 224)),
+			('iperov', 'emilia_clarke_224', (224, 224)),
+			('iperov', 'emma_watson_224', (224, 224)),
+			('iperov', 'erin_moriarty_224', (224, 224)),
+			('iperov', 'jackie_chan_224', (224, 224)),
+			('iperov', 'james_carrey_224', (224, 224)),
+			('iperov', 'jason_statham_320', (320, 320)),
+			('iperov', 'keanu_reeves_320', (320, 320)),
+			('iperov', 'margot_robbie_224', (224, 224)),
+			('iperov', 'natalie_dormer_224', (224, 224)),
+			('iperov', 'nicolas_coppola_224', (224, 224)),
+			('iperov', 'robert_downey_224', (224, 224)),
+			('iperov', 'rowan_atkinson_224', (224, 224)),
+			('iperov', 'ryan_reynolds_224', (224, 224)),
+			('iperov', 'scarlett_johansson_224', (224, 224)),
+			('iperov', 'sylvester_stallone_224', (224, 224)),
+			('iperov', 'thomas_cruise_224', (224, 224)),
+			('iperov', 'thomas_holland_224', (224, 224)),
+			('iperov', 'vin_diesel_224', (224, 224)),
+			('iperov', 'vladimir_putin_224', (224, 224))
+		])
+	if download_scope == 'full':
+		model_config.extend(
+		[
+			('jen', 'angelica_trae_288', (288, 288)),
+			('jen', 'ella_freya_224', (224, 224)),
+			('jen', 'emma_myers_320', (320, 320)),
+			('jen', 'evie_pickerill_224', (224, 224)),
+			('jen', 'kang_hyewon_320', (320, 320)),
+			('jen', 'maddie_mead_224', (224, 224)),
+			('jen', 'nicole_turnbull_288', (288, 288)),
+			('mats', 'alica_schmidt_320', (320, 320)),
+			('mats', 'ashley_alexiss_224', (224, 224)),
+			('mats', 'billie_eilish_224', (224, 224)),
+			('mats', 'brie_larson_224', (224, 224)),
+			('mats', 'cara_delevingne_224', (224, 224)),
+			('mats', 'carolin_kebekus_224', (224, 224)),
+			('mats', 'chelsea_clinton_224', (224, 224)),
+			('mats', 'claire_boucher_224', (224, 224)),
+			('mats', 'corinna_kopf_224', (224, 224)),
+			('mats', 'florence_pugh_224', (224, 224)),
+			('mats', 'hillary_clinton_224', (224, 224)),
+			('mats', 'jenna_fischer_224', (224, 224)),
+			('mats', 'kim_jisoo_320', (320, 320)),
+			('mats', 'mica_suarez_320', (320, 320)),
+			('mats', 'shailene_woodley_224', (224, 224)),
+			('mats', 'shraddha_kapoor_320', (320, 320)),
+			('mats', 'yu_jimin_352', (352, 352)),
+			('rumateus', 'alison_brie_224', (224, 224)),
+			('rumateus', 'amber_heard_224', (224, 224)),
+			('rumateus', 'angelina_jolie_224', (224, 224)),
+			('rumateus', 'aubrey_plaza_224', (224, 224)),
+			('rumateus', 'bridget_regan_224', (224, 224)),
+			('rumateus', 'cobie_smulders_224', (224, 224)),
+			('rumateus', 'deborah_woll_224', (224, 224)),
+			('rumateus', 'dua_lipa_224', (224, 224)),
+			('rumateus', 'emma_stone_224', (224, 224)),
+			('rumateus', 'hailee_steinfeld_224', (224, 224)),
+			('rumateus', 'hilary_duff_224', (224, 224)),
+			('rumateus', 'jessica_alba_224', (224, 224)),
+			('rumateus', 'jessica_biel_224', (224, 224)),
+			('rumateus', 'john_cena_224', (224, 224)),
+			('rumateus', 'kim_kardashian_224', (224, 224)),
+			('rumateus', 'kristen_bell_224', (224, 224)),
+			('rumateus', 'lucy_liu_224', (224, 224)),
+			('rumateus', 'margot_robbie_224', (224, 224)),
+			('rumateus', 'megan_fox_224', (224, 224)),
+			('rumateus', 'meghan_markle_224', (224, 224)),
+			('rumateus', 'millie_bobby_brown_224', (224, 224)),
+			('rumateus', 'natalie_portman_224', (224, 224)),
+			('rumateus', 'nicki_minaj_224', (224, 224)),
+			('rumateus', 'olivia_wilde_224', (224, 224)),
+			('rumateus', 'shay_mitchell_224', (224, 224)),
+			('rumateus', 'sophie_turner_224', (224, 224)),
+			('rumateus', 'taylor_swift_224', (224, 224))
+		])
+	model_set : ModelSet = {}
+
+	for model_creator, model_name, model_size in model_config:
+		model_id = '/'.join([ model_creator, model_name ])
+
+		model_set[model_id] =\
+		{
+			'hashes':
+			{
+				'deep_swapper':
+				{
+					'url': resolve_download_url_by_provider('huggingface', 'deepfacelive-models-' + model_creator, model_name + '.hash'),
+					'path': resolve_relative_path('../.assets/models/' + model_creator + '/' + model_name + '.hash')
+				}
+			},
+			'sources':
+			{
+				'deep_swapper':
+				{
+					'url': resolve_download_url_by_provider('huggingface', 'deepfacelive-models-' + model_creator, model_name + '.dfm'),
+					'path': resolve_relative_path('../.assets/models/' + model_creator + '/' + model_name + '.dfm')
+				}
+			},
+			'template': 'dfl_whole_face',
+			'size': model_size
+		}
+
+	return model_set
+
+
+def get_inference_pool() -> InferencePool:
+	model_sources = get_model_options().get('sources')
+	model_context = __name__ + '.' + state_manager.get_item('deep_swapper_model')
+	return inference_manager.get_inference_pool(model_context, model_sources)
+
+
+def clear_inference_pool() -> None:
+	model_context = __name__ + '.' + state_manager.get_item('deep_swapper_model')
+	inference_manager.clear_inference_pool(model_context)
+
+
+def get_model_options() -> ModelOptions:
+	deep_swapper_model = state_manager.get_item('deep_swapper_model')
+	return create_static_model_set('full').get(deep_swapper_model)
+
+
+def register_args(program : ArgumentParser) -> None:
+	group_processors = find_argument_group(program, 'processors')
+	if group_processors:
+		group_processors.add_argument('--deep-swapper-model', help = wording.get('help.deep_swapper_model'), default = config.get_str_value('processors.deep_swapper_model', 'iperov/elon_musk_224'), choices = processors_choices.deep_swapper_models)
+		group_processors.add_argument('--deep-swapper-morph', help = wording.get('help.deep_swapper_morph'), type = int, default = config.get_int_value('processors.deep_swapper_morph', '80'), choices = processors_choices.deep_swapper_morph_range, metavar = create_int_metavar(processors_choices.deep_swapper_morph_range))
+		facefusion.jobs.job_store.register_step_keys([ 'deep_swapper_model', 'deep_swapper_morph' ])
+
+
+def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
+	apply_state_item('deep_swapper_model', args.get('deep_swapper_model'))
+	apply_state_item('deep_swapper_morph', args.get('deep_swapper_morph'))
+
+
+def pre_check() -> bool:
+	model_hashes = get_model_options().get('hashes')
+	model_sources = get_model_options().get('sources')
+
+	return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
+
+
+def pre_process(mode : ProcessMode) -> bool:
+	if mode in [ 'output', 'preview' ] and not is_image(state_manager.get_item('target_path')) and not is_video(state_manager.get_item('target_path')):
+		logger.error(wording.get('choose_image_or_video_target') + wording.get('exclamation_mark'), __name__)
+		return False
+	if mode == 'output' and not in_directory(state_manager.get_item('output_path')):
+		logger.error(wording.get('specify_image_or_video_output') + wording.get('exclamation_mark'), __name__)
+		return False
+	if mode == 'output' and not same_file_extension([ state_manager.get_item('target_path'), state_manager.get_item('output_path') ]):
+		logger.error(wording.get('match_target_and_output_extension') + wording.get('exclamation_mark'), __name__)
+		return False
+	return True
+
+
+def post_process() -> None:
+	read_static_image.cache_clear()
+	if state_manager.get_item('video_memory_strategy') in [ 'strict', 'moderate' ]:
+		clear_inference_pool()
+	if state_manager.get_item('video_memory_strategy') == 'strict':
+		content_analyser.clear_inference_pool()
+		face_classifier.clear_inference_pool()
+		face_detector.clear_inference_pool()
+		face_landmarker.clear_inference_pool()
+		face_masker.clear_inference_pool()
+		face_recognizer.clear_inference_pool()
+
+
+def swap_face(target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame:
+	model_template = get_model_options().get('template')
+	model_size = get_model_options().get('size')
+	crop_vision_frame, affine_matrix = warp_face_by_face_landmark_5(temp_vision_frame, target_face.landmark_set.get('5/68'), model_template, model_size)
+	crop_vision_frame_raw = crop_vision_frame.copy()
+	box_mask = create_static_box_mask(crop_vision_frame.shape[:2][::-1], state_manager.get_item('face_mask_blur'), state_manager.get_item('face_mask_padding'))
+	crop_masks =\
+	[
+		box_mask
+	]
+
+	if 'occlusion' in state_manager.get_item('face_mask_types'):
+		occlusion_mask = create_occlusion_mask(crop_vision_frame)
+		crop_masks.append(occlusion_mask)
+
+	crop_vision_frame = prepare_crop_frame(crop_vision_frame)
+	deep_swapper_morph = numpy.array([ numpy.interp(state_manager.get_item('deep_swapper_morph'), [ 0, 100 ], [ 0, 1 ]) ]).astype(numpy.float32)
+	crop_vision_frame, crop_source_mask, crop_target_mask = forward(crop_vision_frame, deep_swapper_morph)
+	crop_vision_frame = normalize_crop_frame(crop_vision_frame)
+	crop_vision_frame = conditional_match_frame_color(crop_vision_frame_raw, crop_vision_frame)
+	crop_masks.append(prepare_crop_mask(crop_source_mask, crop_target_mask))
+	crop_mask = numpy.minimum.reduce(crop_masks).clip(0, 1)
+	paste_vision_frame = paste_back(temp_vision_frame, crop_vision_frame, crop_mask, affine_matrix)
+	return paste_vision_frame
+
+
+def forward(crop_vision_frame : VisionFrame, deep_swapper_morph : DeepSwapperMorph) -> Tuple[VisionFrame, Mask, Mask]:
+	deep_swapper = get_inference_pool().get('deep_swapper')
+	deep_swapper_inputs = {}
+
+	for deep_swapper_input in deep_swapper.get_inputs():
+		if deep_swapper_input.name == 'in_face:0':
+			deep_swapper_inputs[deep_swapper_input.name] = crop_vision_frame
+		if deep_swapper_input.name == 'morph_value:0':
+			deep_swapper_inputs[deep_swapper_input.name] = deep_swapper_morph
+
+	with thread_semaphore():
+		crop_target_mask, crop_vision_frame, crop_source_mask = deep_swapper.run(None, deep_swapper_inputs)
+
+	return crop_vision_frame[0], crop_source_mask[0], crop_target_mask[0]
+
+
+def has_morph_input() -> bool:
+	deep_swapper = get_inference_pool().get('deep_swapper')
+
+	for deep_swapper_input in deep_swapper.get_inputs():
+		if deep_swapper_input.name == 'morph_value:0':
+			return True
+	return False
+
+
+def prepare_crop_frame(crop_vision_frame : VisionFrame) -> VisionFrame:
+	crop_vision_frame = cv2.addWeighted(crop_vision_frame, 1.75, cv2.GaussianBlur(crop_vision_frame, (0, 0), 2), -0.75, 0)
+	crop_vision_frame = crop_vision_frame / 255.0
+	crop_vision_frame = numpy.expand_dims(crop_vision_frame, axis = 0).astype(numpy.float32)
+	return crop_vision_frame
+
+
+def normalize_crop_frame(crop_vision_frame : VisionFrame) -> VisionFrame:
+	crop_vision_frame = (crop_vision_frame * 255.0).clip(0, 255)
+	crop_vision_frame = crop_vision_frame.astype(numpy.uint8)
+	return crop_vision_frame
+
+
+def prepare_crop_mask(crop_source_mask : Mask, crop_target_mask : Mask) -> Mask:
+	model_size = get_model_options().get('size')
+	blur_size = 6.25
+	kernel_size = 3
+	crop_mask = numpy.minimum.reduce([ crop_source_mask, crop_target_mask ])
+	crop_mask = crop_mask.reshape(model_size).clip(0, 1)
+	crop_mask = cv2.erode(crop_mask, cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (kernel_size, kernel_size)), iterations = 2)
+	crop_mask = cv2.GaussianBlur(crop_mask, (0, 0), blur_size)
+	return crop_mask
+
+
+def get_reference_frame(source_face : Face, target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame:
+	return swap_face(target_face, temp_vision_frame)
+
+
+def process_frame(inputs : DeepSwapperInputs) -> VisionFrame:
+	reference_faces = inputs.get('reference_faces')
+	target_vision_frame = inputs.get('target_vision_frame')
+	many_faces = sort_and_filter_faces(get_many_faces([ target_vision_frame ]))
+
+	if state_manager.get_item('face_selector_mode') == 'many':
+		if many_faces:
+			for target_face in many_faces:
+				target_vision_frame = swap_face(target_face, target_vision_frame)
+	if state_manager.get_item('face_selector_mode') == 'one':
+		target_face = get_one_face(many_faces)
+		if target_face:
+			target_vision_frame = swap_face(target_face, target_vision_frame)
+	if state_manager.get_item('face_selector_mode') == 'reference':
+		similar_faces = find_similar_faces(many_faces, reference_faces, state_manager.get_item('reference_face_distance'))
+		if similar_faces:
+			for similar_face in similar_faces:
+				target_vision_frame = swap_face(similar_face, target_vision_frame)
+	return target_vision_frame
+
+
+def process_frames(source_path : List[str], queue_payloads : List[QueuePayload], update_progress : UpdateProgress) -> None:
+	reference_faces = get_reference_faces() if 'reference' in state_manager.get_item('face_selector_mode') else None
+
+	for queue_payload in process_manager.manage(queue_payloads):
+		target_vision_path = queue_payload['frame_path']
+		target_vision_frame = read_image(target_vision_path)
+		output_vision_frame = process_frame(
+		{
+			'reference_faces': reference_faces,
+			'target_vision_frame': target_vision_frame
+		})
+		write_image(target_vision_path, output_vision_frame)
+		update_progress(1)
+
+
+def process_image(source_path : str, target_path : str, output_path : str) -> None:
+	reference_faces = get_reference_faces() if 'reference' in state_manager.get_item('face_selector_mode') else None
+	target_vision_frame = read_static_image(target_path)
+	output_vision_frame = process_frame(
+	{
+		'reference_faces': reference_faces,
+		'target_vision_frame': target_vision_frame
+	})
+	write_image(output_path, output_vision_frame)
+
+
+def process_video(source_paths : List[str], temp_frame_paths : List[str]) -> None:
+	processors.multi_process_frames(None, temp_frame_paths, process_frames)

facefusion/processors/modules/expression_restorer.py

@@ -1,4 +1,5 @@
 from argparse import ArgumentParser
+from functools import lru_cache
 from typing import List, Tuple
 
 import cv2
@@ -9,7 +10,7 @@ import facefusion.jobs.job_store
 import facefusion.processors.core as processors
 from facefusion import config, content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer, inference_manager, logger, process_manager, state_manager, wording
 from facefusion.common_helper import create_int_metavar
-from facefusion.download import conditional_download_hashes, conditional_download_sources
+from facefusion.download import conditional_download_hashes, conditional_download_sources, resolve_download_url
 from facefusion.face_analyser import get_many_faces, get_one_face
 from facefusion.face_helper import paste_back, warp_face_by_face_landmark_5
 from facefusion.face_masker import create_occlusion_mask, create_static_box_mask
@@ -22,53 +23,56 @@ from facefusion.processors.typing import ExpressionRestorerInputs
 from facefusion.processors.typing import LivePortraitExpression, LivePortraitFeatureVolume, LivePortraitMotionPoints, LivePortraitPitch, LivePortraitRoll, LivePortraitScale, LivePortraitTranslation, LivePortraitYaw
 from facefusion.program_helper import find_argument_group
 from facefusion.thread_helper import conditional_thread_semaphore, thread_semaphore
-from facefusion.typing import ApplyStateItem, Args, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
+from facefusion.typing import ApplyStateItem, Args, DownloadScope, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
 from facefusion.vision import get_video_frame, read_image, read_static_image, write_image
 
-MODEL_SET : ModelSet =\
-{
-	'live_portrait':
+
+@lru_cache(maxsize = None)
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
+	return\
 	{
-		'hashes':
+		'live_portrait':
 		{
-			'feature_extractor':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_feature_extractor.hash',
-				'path': resolve_relative_path('../.assets/models/live_portrait_feature_extractor.hash')
+				'feature_extractor':
+				{
+					'url': resolve_download_url('models-3.0.0', 'live_portrait_feature_extractor.hash'),
+					'path': resolve_relative_path('../.assets/models/live_portrait_feature_extractor.hash')
+				},
+				'motion_extractor':
+				{
+					'url': resolve_download_url('models-3.0.0', 'live_portrait_motion_extractor.hash'),
+					'path': resolve_relative_path('../.assets/models/live_portrait_motion_extractor.hash')
+				},
+				'generator':
+				{
+					'url': resolve_download_url('models-3.0.0', 'live_portrait_generator.hash'),
+					'path': resolve_relative_path('../.assets/models/live_portrait_generator.hash')
+				}
 			},
-			'motion_extractor':
+			'sources':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_motion_extractor.hash',
-				'path': resolve_relative_path('../.assets/models/live_portrait_motion_extractor.hash')
+				'feature_extractor':
+				{
+					'url': resolve_download_url('models-3.0.0', 'live_portrait_feature_extractor.onnx'),
+					'path': resolve_relative_path('../.assets/models/live_portrait_feature_extractor.onnx')
+				},
+				'motion_extractor':
+				{
+					'url': resolve_download_url('models-3.0.0', 'live_portrait_motion_extractor.onnx'),
+					'path': resolve_relative_path('../.assets/models/live_portrait_motion_extractor.onnx')
+				},
+				'generator':
+				{
+					'url': resolve_download_url('models-3.0.0', 'live_portrait_generator.onnx'),
+					'path': resolve_relative_path('../.assets/models/live_portrait_generator.onnx')
+				}
 			},
-			'generator':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_generator.hash',
-				'path': resolve_relative_path('../.assets/models/live_portrait_generator.hash')
-			}
-		},
-		'sources':
-		{
-			'feature_extractor':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_feature_extractor.onnx',
-				'path': resolve_relative_path('../.assets/models/live_portrait_feature_extractor.onnx')
-			},
-			'motion_extractor':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_motion_extractor.onnx',
-				'path': resolve_relative_path('../.assets/models/live_portrait_motion_extractor.onnx')
-			},
-			'generator':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_generator.onnx',
-				'path': resolve_relative_path('../.assets/models/live_portrait_generator.onnx')
-			}
-		},
-		'template': 'arcface_128_v2',
-		'size': (512, 512)
+			'template': 'arcface_128_v2',
+			'size': (512, 512)
+		}
 	}
-}
 
 
 def get_inference_pool() -> InferencePool:
@@ -83,7 +87,7 @@ def clear_inference_pool() -> None:
 
 def get_model_options() -> ModelOptions:
 	expression_restorer_model = state_manager.get_item('expression_restorer_model')
-	return MODEL_SET.get(expression_restorer_model)
+	return create_static_model_set('full').get(expression_restorer_model)
 
 
 def register_args(program : ArgumentParser) -> None:
@@ -100,14 +104,16 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
 
 
 def pre_check() -> bool:
-	download_directory_path = resolve_relative_path('../.assets/models')
 	model_hashes = get_model_options().get('hashes')
 	model_sources = get_model_options().get('sources')
 
-	return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources)
+	return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
 
 
 def pre_process(mode : ProcessMode) -> bool:
+	if mode == 'stream':
+		logger.error(wording.get('stream_not_supported') + wording.get('exclamation_mark'), __name__)
+		return False
 	if mode in [ 'output', 'preview' ] and not is_image(state_manager.get_item('target_path')) and not is_video(state_manager.get_item('target_path')):
 		logger.error(wording.get('choose_image_or_video_target') + wording.get('exclamation_mark'), __name__)
 		return False
@@ -222,7 +228,7 @@ def prepare_crop_frame(crop_vision_frame : VisionFrame) -> VisionFrame:
 
 def normalize_crop_frame(crop_vision_frame : VisionFrame) -> VisionFrame:
 	crop_vision_frame = crop_vision_frame.transpose(1, 2, 0).clip(0, 1)
-	crop_vision_frame = (crop_vision_frame * 255.0)
+	crop_vision_frame = crop_vision_frame * 255.0
 	crop_vision_frame = crop_vision_frame.astype(numpy.uint8)[:, :, ::-1]
 	return crop_vision_frame
 

facefusion/processors/modules/face_debugger.py

@@ -17,11 +17,11 @@ from facefusion.filesystem import in_directory, same_file_extension
 from facefusion.processors import choices as processors_choices
 from facefusion.processors.typing import FaceDebuggerInputs
 from facefusion.program_helper import find_argument_group
-from facefusion.typing import ApplyStateItem, Args, Face, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
+from facefusion.typing import ApplyStateItem, Args, Face, InferencePool, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
 from facefusion.vision import read_image, read_static_image, write_image
 
 
-def get_inference_pool() -> None:
+def get_inference_pool() -> InferencePool:
 	pass
 
 

facefusion/processors/modules/face_editor.py

@@ -1,4 +1,5 @@
 from argparse import ArgumentParser
+from functools import lru_cache
 from typing import List, Tuple
 
 import cv2
@@ -9,7 +10,7 @@ import facefusion.jobs.job_store
 import facefusion.processors.core as processors
 from facefusion import config, content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer, inference_manager, logger, process_manager, state_manager, wording
 from facefusion.common_helper import create_float_metavar
-from facefusion.download import conditional_download_hashes, conditional_download_sources
+from facefusion.download import conditional_download_hashes, conditional_download_sources, resolve_download_url
 from facefusion.face_analyser import get_many_faces, get_one_face
 from facefusion.face_helper import paste_back, scale_face_landmark_5, warp_face_by_face_landmark_5
 from facefusion.face_masker import create_static_box_mask
@@ -21,83 +22,86 @@ from facefusion.processors.live_portrait import create_rotation, limit_euler_ang
 from facefusion.processors.typing import FaceEditorInputs, LivePortraitExpression, LivePortraitFeatureVolume, LivePortraitMotionPoints, LivePortraitPitch, LivePortraitRoll, LivePortraitRotation, LivePortraitScale, LivePortraitTranslation, LivePortraitYaw
 from facefusion.program_helper import find_argument_group
 from facefusion.thread_helper import conditional_thread_semaphore, thread_semaphore
-from facefusion.typing import ApplyStateItem, Args, Face, FaceLandmark68, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
+from facefusion.typing import ApplyStateItem, Args, DownloadScope, Face, FaceLandmark68, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
 from facefusion.vision import read_image, read_static_image, write_image
 
-MODEL_SET : ModelSet =\
-{
-	'live_portrait':
+
+@lru_cache(maxsize = None)
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
+	return\
 	{
-		'hashes':
+		'live_portrait':
 		{
-			'feature_extractor':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_feature_extractor.hash',
-				'path': resolve_relative_path('../.assets/models/live_portrait_feature_extractor.hash')
+				'feature_extractor':
+				{
+					'url': resolve_download_url('models-3.0.0', 'live_portrait_feature_extractor.hash'),
+					'path': resolve_relative_path('../.assets/models/live_portrait_feature_extractor.hash')
+				},
+				'motion_extractor':
+				{
+					'url': resolve_download_url('models-3.0.0', 'live_portrait_motion_extractor.hash'),
+					'path': resolve_relative_path('../.assets/models/live_portrait_motion_extractor.hash')
+				},
+				'eye_retargeter':
+				{
+					'url': resolve_download_url('models-3.0.0', 'live_portrait_eye_retargeter.hash'),
+					'path': resolve_relative_path('../.assets/models/live_portrait_eye_retargeter.hash')
+				},
+				'lip_retargeter':
+				{
+					'url': resolve_download_url('models-3.0.0', 'live_portrait_lip_retargeter.hash'),
+					'path': resolve_relative_path('../.assets/models/live_portrait_lip_retargeter.hash')
+				},
+				'stitcher':
+				{
+					'url': resolve_download_url('models-3.0.0', 'live_portrait_stitcher.hash'),
+					'path': resolve_relative_path('../.assets/models/live_portrait_stitcher.hash')
+				},
+				'generator':
+				{
+					'url': resolve_download_url('models-3.0.0', 'live_portrait_generator.hash'),
+					'path': resolve_relative_path('../.assets/models/live_portrait_generator.hash')
+				}
 			},
-			'motion_extractor':
+			'sources':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_motion_extractor.hash',
-				'path': resolve_relative_path('../.assets/models/live_portrait_motion_extractor.hash')
+				'feature_extractor':
+				{
+					'url': resolve_download_url('models-3.0.0', 'live_portrait_feature_extractor.onnx'),
+					'path': resolve_relative_path('../.assets/models/live_portrait_feature_extractor.onnx')
+				},
+				'motion_extractor':
+				{
+					'url': resolve_download_url('models-3.0.0', 'live_portrait_motion_extractor.onnx'),
+					'path': resolve_relative_path('../.assets/models/live_portrait_motion_extractor.onnx')
+				},
+				'eye_retargeter':
+				{
+					'url': resolve_download_url('models-3.0.0', 'live_portrait_eye_retargeter.onnx'),
+					'path': resolve_relative_path('../.assets/models/live_portrait_eye_retargeter.onnx')
+				},
+				'lip_retargeter':
+				{
+					'url': resolve_download_url('models-3.0.0', 'live_portrait_lip_retargeter.onnx'),
+					'path': resolve_relative_path('../.assets/models/live_portrait_lip_retargeter.onnx')
+				},
+				'stitcher':
+				{
+					'url': resolve_download_url('models-3.0.0', 'live_portrait_stitcher.onnx'),
+					'path': resolve_relative_path('../.assets/models/live_portrait_stitcher.onnx')
+				},
+				'generator':
+				{
+					'url': resolve_download_url('models-3.0.0', 'live_portrait_generator.onnx'),
+					'path': resolve_relative_path('../.assets/models/live_portrait_generator.onnx')
+				}
 			},
-			'eye_retargeter':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_eye_retargeter.hash',
-				'path': resolve_relative_path('../.assets/models/live_portrait_eye_retargeter.hash')
-			},
-			'lip_retargeter':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_lip_retargeter.hash',
-				'path': resolve_relative_path('../.assets/models/live_portrait_lip_retargeter.hash')
-			},
-			'stitcher':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_stitcher.hash',
-				'path': resolve_relative_path('../.assets/models/live_portrait_stitcher.hash')
-			},
-			'generator':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_generator.hash',
-				'path': resolve_relative_path('../.assets/models/live_portrait_generator.hash')
-			}
-		},
-		'sources':
-		{
-			'feature_extractor':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_feature_extractor.onnx',
-				'path': resolve_relative_path('../.assets/models/live_portrait_feature_extractor.onnx')
-			},
-			'motion_extractor':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_motion_extractor.onnx',
-				'path': resolve_relative_path('../.assets/models/live_portrait_motion_extractor.onnx')
-			},
-			'eye_retargeter':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_eye_retargeter.onnx',
-				'path': resolve_relative_path('../.assets/models/live_portrait_eye_retargeter.onnx')
-			},
-			'lip_retargeter':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_lip_retargeter.onnx',
-				'path': resolve_relative_path('../.assets/models/live_portrait_lip_retargeter.onnx')
-			},
-			'stitcher':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_stitcher.onnx',
-				'path': resolve_relative_path('../.assets/models/live_portrait_stitcher.onnx')
-			},
-			'generator':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/live_portrait_generator.onnx',
-				'path': resolve_relative_path('../.assets/models/live_portrait_generator.onnx')
-			}
-		},
-		'template': 'ffhq_512',
-		'size': (512, 512)
+			'template': 'ffhq_512',
+			'size': (512, 512)
+		}
 	}
-}
 
 
 def get_inference_pool() -> InferencePool:
@@ -113,7 +117,7 @@ def clear_inference_pool() -> None:
 
 def get_model_options() -> ModelOptions:
 	face_editor_model = state_manager.get_item('face_editor_model')
-	return MODEL_SET.get(face_editor_model)
+	return create_static_model_set('full').get(face_editor_model)
 
 
 def register_args(program : ArgumentParser) -> None:
@@ -156,11 +160,10 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
 
 
 def pre_check() -> bool:
-	download_directory_path = resolve_relative_path('../.assets/models')
 	model_hashes = get_model_options().get('hashes')
 	model_sources = get_model_options().get('sources')
 
-	return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources)
+	return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
 
 
 def pre_process(mode : ProcessMode) -> bool:

facefusion/processors/modules/face_enhancer.py

@@ -1,4 +1,5 @@
 from argparse import ArgumentParser
+from functools import lru_cache
 from typing import List
 
 import cv2
@@ -8,8 +9,8 @@ import facefusion.jobs.job_manager
 import facefusion.jobs.job_store
 import facefusion.processors.core as processors
 from facefusion import config, content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer, inference_manager, logger, process_manager, state_manager, wording
-from facefusion.common_helper import create_int_metavar
-from facefusion.download import conditional_download_hashes, conditional_download_sources
+from facefusion.common_helper import create_float_metavar, create_int_metavar
+from facefusion.download import conditional_download_hashes, conditional_download_sources, resolve_download_url
 from facefusion.face_analyser import get_many_faces, get_one_face
 from facefusion.face_helper import paste_back, warp_face_by_face_landmark_5
 from facefusion.face_masker import create_occlusion_mask, create_static_box_mask
@@ -17,204 +18,207 @@ from facefusion.face_selector import find_similar_faces, sort_and_filter_faces
 from facefusion.face_store import get_reference_faces
 from facefusion.filesystem import in_directory, is_image, is_video, resolve_relative_path, same_file_extension
 from facefusion.processors import choices as processors_choices
-from facefusion.processors.typing import FaceEnhancerInputs
+from facefusion.processors.typing import FaceEnhancerInputs, FaceEnhancerWeight
 from facefusion.program_helper import find_argument_group
 from facefusion.thread_helper import thread_semaphore
-from facefusion.typing import ApplyStateItem, Args, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
+from facefusion.typing import ApplyStateItem, Args, DownloadScope, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
 from facefusion.vision import read_image, read_static_image, write_image
 
-MODEL_SET : ModelSet =\
-{
-	'codeformer':
+
+@lru_cache(maxsize = None)
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
+	return\
 	{
-		'hashes':
+		'codeformer':
 		{
-			'face_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/codeformer.hash',
-				'path': resolve_relative_path('../.assets/models/codeformer.hash')
-			}
+				'face_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'codeformer.hash'),
+					'path': resolve_relative_path('../.assets/models/codeformer.hash')
+				}
+			},
+			'sources':
+			{
+				'face_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'codeformer.onnx'),
+					'path': resolve_relative_path('../.assets/models/codeformer.onnx')
+				}
+			},
+			'template': 'ffhq_512',
+			'size': (512, 512)
 		},
-		'sources':
+		'gfpgan_1.2':
 		{
-			'face_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/codeformer.onnx',
-				'path': resolve_relative_path('../.assets/models/codeformer.onnx')
-			}
+				'face_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'gfpgan_1.2.hash'),
+					'path': resolve_relative_path('../.assets/models/gfpgan_1.2.hash')
+				}
+			},
+			'sources':
+			{
+				'face_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'gfpgan_1.2.onnx'),
+					'path': resolve_relative_path('../.assets/models/gfpgan_1.2.onnx')
+				}
+			},
+			'template': 'ffhq_512',
+			'size': (512, 512)
 		},
-		'template': 'ffhq_512',
-		'size': (512, 512)
-	},
-	'gfpgan_1.2':
-	{
-		'hashes':
+		'gfpgan_1.3':
 		{
-			'face_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/gfpgan_1.2.hash',
-				'path': resolve_relative_path('../.assets/models/gfpgan_1.2.hash')
-			}
+				'face_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'gfpgan_1.3.hash'),
+					'path': resolve_relative_path('../.assets/models/gfpgan_1.3.hash')
+				}
+			},
+			'sources':
+			{
+				'face_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'gfpgan_1.3.onnx'),
+					'path': resolve_relative_path('../.assets/models/gfpgan_1.3.onnx')
+				}
+			},
+			'template': 'ffhq_512',
+			'size': (512, 512)
 		},
-		'sources':
+		'gfpgan_1.4':
 		{
-			'face_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/gfpgan_1.2.onnx',
-				'path': resolve_relative_path('../.assets/models/gfpgan_1.2.onnx')
-			}
+				'face_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'gfpgan_1.4.hash'),
+					'path': resolve_relative_path('../.assets/models/gfpgan_1.4.hash')
+				}
+			},
+			'sources':
+			{
+				'face_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'gfpgan_1.4.onnx'),
+					'path': resolve_relative_path('../.assets/models/gfpgan_1.4.onnx')
+				}
+			},
+			'template': 'ffhq_512',
+			'size': (512, 512)
 		},
-		'template': 'ffhq_512',
-		'size': (512, 512)
-	},
-	'gfpgan_1.3':
-	{
-		'hashes':
+		'gpen_bfr_256':
 		{
-			'face_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/gfpgan_1.3.hash',
-				'path': resolve_relative_path('../.assets/models/gfpgan_1.3.hash')
-			}
+				'face_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'gpen_bfr_256.hash'),
+					'path': resolve_relative_path('../.assets/models/gpen_bfr_256.hash')
+				}
+			},
+			'sources':
+			{
+				'face_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'gpen_bfr_256.onnx'),
+					'path': resolve_relative_path('../.assets/models/gpen_bfr_256.onnx')
+				}
+			},
+			'template': 'arcface_128_v2',
+			'size': (256, 256)
 		},
-		'sources':
+		'gpen_bfr_512':
 		{
-			'face_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/gfpgan_1.3.onnx',
-				'path': resolve_relative_path('../.assets/models/gfpgan_1.3.onnx')
-			}
+				'face_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'gpen_bfr_512.hash'),
+					'path': resolve_relative_path('../.assets/models/gpen_bfr_512.hash')
+				}
+			},
+			'sources':
+			{
+				'face_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'gpen_bfr_512.onnx'),
+					'path': resolve_relative_path('../.assets/models/gpen_bfr_512.onnx')
+				}
+			},
+			'template': 'ffhq_512',
+			'size': (512, 512)
 		},
-		'template': 'ffhq_512',
-		'size': (512, 512)
-	},
-	'gfpgan_1.4':
-	{
-		'hashes':
+		'gpen_bfr_1024':
 		{
-			'face_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/gfpgan_1.4.hash',
-				'path': resolve_relative_path('../.assets/models/gfpgan_1.4.hash')
-			}
+				'face_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'gpen_bfr_1024.hash'),
+					'path': resolve_relative_path('../.assets/models/gpen_bfr_1024.hash')
+				}
+			},
+			'sources':
+			{
+				'face_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'gpen_bfr_1024.onnx'),
+					'path': resolve_relative_path('../.assets/models/gpen_bfr_1024.onnx')
+				}
+			},
+			'template': 'ffhq_512',
+			'size': (1024, 1024)
 		},
-		'sources':
+		'gpen_bfr_2048':
 		{
-			'face_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/gfpgan_1.4.onnx',
-				'path': resolve_relative_path('../.assets/models/gfpgan_1.4.onnx')
-			}
+				'face_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'gpen_bfr_2048.hash'),
+					'path': resolve_relative_path('../.assets/models/gpen_bfr_2048.hash')
+				}
+			},
+			'sources':
+			{
+				'face_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'gpen_bfr_2048.onnx'),
+					'path': resolve_relative_path('../.assets/models/gpen_bfr_2048.onnx')
+				}
+			},
+			'template': 'ffhq_512',
+			'size': (2048, 2048)
 		},
-		'template': 'ffhq_512',
-		'size': (512, 512)
-	},
-	'gpen_bfr_256':
-	{
-		'hashes':
+		'restoreformer_plus_plus':
 		{
-			'face_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/gpen_bfr_256.hash',
-				'path': resolve_relative_path('../.assets/models/gpen_bfr_256.hash')
-			}
-		},
-		'sources':
-		{
-			'face_enhancer':
+				'face_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'restoreformer_plus_plus.hash'),
+					'path': resolve_relative_path('../.assets/models/restoreformer_plus_plus.hash')
+				}
+			},
+			'sources':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/gpen_bfr_256.onnx',
-				'path': resolve_relative_path('../.assets/models/gpen_bfr_256.onnx')
-			}
-		},
-		'template': 'arcface_128_v2',
-		'size': (256, 256)
-	},
-	'gpen_bfr_512':
-	{
-		'hashes':
-		{
-			'face_enhancer':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/gpen_bfr_512.hash',
-				'path': resolve_relative_path('../.assets/models/gpen_bfr_512.hash')
-			}
-		},
-		'sources':
-		{
-			'face_enhancer':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/gpen_bfr_512.onnx',
-				'path': resolve_relative_path('../.assets/models/gpen_bfr_512.onnx')
-			}
-		},
-		'template': 'ffhq_512',
-		'size': (512, 512)
-	},
-	'gpen_bfr_1024':
-	{
-		'hashes':
-		{
-			'face_enhancer':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/gpen_bfr_1024.hash',
-				'path': resolve_relative_path('../.assets/models/gpen_bfr_1024.hash')
-			}
-		},
-		'sources':
-		{
-			'face_enhancer':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/gpen_bfr_1024.onnx',
-				'path': resolve_relative_path('../.assets/models/gpen_bfr_1024.onnx')
-			}
-		},
-		'template': 'ffhq_512',
-		'size': (1024, 1024)
-	},
-	'gpen_bfr_2048':
-	{
-		'hashes':
-		{
-			'face_enhancer':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/gpen_bfr_2048.hash',
-				'path': resolve_relative_path('../.assets/models/gpen_bfr_2048.hash')
-			}
-		},
-		'sources':
-		{
-			'face_enhancer':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/gpen_bfr_2048.onnx',
-				'path': resolve_relative_path('../.assets/models/gpen_bfr_2048.onnx')
-			}
-		},
-		'template': 'ffhq_512',
-		'size': (2048, 2048)
-	},
-	'restoreformer_plus_plus':
-	{
-		'hashes':
-		{
-			'face_enhancer':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/restoreformer_plus_plus.hash',
-				'path': resolve_relative_path('../.assets/models/restoreformer_plus_plus.hash')
-			}
-		},
-		'sources':
-		{
-			'face_enhancer':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/restoreformer_plus_plus.onnx',
-				'path': resolve_relative_path('../.assets/models/restoreformer_plus_plus.onnx')
-			}
-		},
-		'template': 'ffhq_512',
-		'size': (512, 512)
+				'face_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'restoreformer_plus_plus.onnx'),
+					'path': resolve_relative_path('../.assets/models/restoreformer_plus_plus.onnx')
+				}
+			},
+			'template': 'ffhq_512',
+			'size': (512, 512)
+		}
 	}
-}
 
 
 def get_inference_pool() -> InferencePool:
@@ -230,7 +234,7 @@ def clear_inference_pool() -> None:
 
 def get_model_options() -> ModelOptions:
 	face_enhancer_model = state_manager.get_item('face_enhancer_model')
-	return MODEL_SET.get(face_enhancer_model)
+	return create_static_model_set('full').get(face_enhancer_model)
 
 
 def register_args(program : ArgumentParser) -> None:
@@ -238,20 +242,21 @@ def register_args(program : ArgumentParser) -> None:
 	if group_processors:
 		group_processors.add_argument('--face-enhancer-model', help = wording.get('help.face_enhancer_model'), default = config.get_str_value('processors.face_enhancer_model', 'gfpgan_1.4'), choices = processors_choices.face_enhancer_models)
 		group_processors.add_argument('--face-enhancer-blend', help = wording.get('help.face_enhancer_blend'), type = int, default = config.get_int_value('processors.face_enhancer_blend', '80'), choices = processors_choices.face_enhancer_blend_range, metavar = create_int_metavar(processors_choices.face_enhancer_blend_range))
-		facefusion.jobs.job_store.register_step_keys([ 'face_enhancer_model', 'face_enhancer_blend' ])
+		group_processors.add_argument('--face-enhancer-weight', help = wording.get('help.face_enhancer_weight'), type = float, default = config.get_float_value('processors.face_enhancer_weight', '1.0'), choices = processors_choices.face_enhancer_weight_range, metavar = create_float_metavar(processors_choices.face_enhancer_weight_range))
+		facefusion.jobs.job_store.register_step_keys([ 'face_enhancer_model', 'face_enhancer_blend', 'face_enhancer_weight' ])
 
 
 def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
 	apply_state_item('face_enhancer_model', args.get('face_enhancer_model'))
 	apply_state_item('face_enhancer_blend', args.get('face_enhancer_blend'))
+	apply_state_item('face_enhancer_weight', args.get('face_enhancer_weight'))
 
 
 def pre_check() -> bool:
-	download_directory_path = resolve_relative_path('../.assets/models')
 	model_hashes = get_model_options().get('hashes')
 	model_sources = get_model_options().get('sources')
 
-	return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources)
+	return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
 
 
 def pre_process(mode : ProcessMode) -> bool:
@@ -295,7 +300,8 @@ def enhance_face(target_face : Face, temp_vision_frame : VisionFrame) -> VisionF
 		crop_masks.append(occlusion_mask)
 
 	crop_vision_frame = prepare_crop_frame(crop_vision_frame)
-	crop_vision_frame = forward(crop_vision_frame)
+	face_enhancer_weight = numpy.array([ state_manager.get_item('face_enhancer_weight') ]).astype(numpy.double)
+	crop_vision_frame = forward(crop_vision_frame, face_enhancer_weight)
 	crop_vision_frame = normalize_crop_frame(crop_vision_frame)
 	crop_mask = numpy.minimum.reduce(crop_masks).clip(0, 1)
 	paste_vision_frame = paste_back(temp_vision_frame, crop_vision_frame, crop_mask, affine_matrix)
@@ -303,7 +309,7 @@ def enhance_face(target_face : Face, temp_vision_frame : VisionFrame) -> VisionF
 	return temp_vision_frame
 
 
-def forward(crop_vision_frame : VisionFrame) -> VisionFrame:
+def forward(crop_vision_frame : VisionFrame, face_enhancer_weight : FaceEnhancerWeight) -> VisionFrame:
 	face_enhancer = get_inference_pool().get('face_enhancer')
 	face_enhancer_inputs = {}
 
@@ -311,8 +317,7 @@ def forward(crop_vision_frame : VisionFrame) -> VisionFrame:
 		if face_enhancer_input.name == 'input':
 			face_enhancer_inputs[face_enhancer_input.name] = crop_vision_frame
 		if face_enhancer_input.name == 'weight':
-			weight = numpy.array([ 1 ]).astype(numpy.double)
-			face_enhancer_inputs[face_enhancer_input.name] = weight
+			face_enhancer_inputs[face_enhancer_input.name] = face_enhancer_weight
 
 	with thread_semaphore():
 		crop_vision_frame = face_enhancer.run(None, face_enhancer_inputs)[0][0]
@@ -320,6 +325,15 @@ def forward(crop_vision_frame : VisionFrame) -> VisionFrame:
 	return crop_vision_frame
 
 
+def has_weight_input() -> bool:
+	face_enhancer = get_inference_pool().get('face_enhancer')
+
+	for deep_swapper_input in face_enhancer.get_inputs():
+		if deep_swapper_input.name == 'weight':
+			return True
+	return False
+
+
 def prepare_crop_frame(crop_vision_frame : VisionFrame) -> VisionFrame:
 	crop_vision_frame = crop_vision_frame[:, :, ::-1] / 255.0
 	crop_vision_frame = (crop_vision_frame - 0.5) / 0.5

facefusion/processors/modules/face_swapper.py

@@ -1,4 +1,5 @@
 from argparse import ArgumentParser
+from functools import lru_cache
 from typing import List, Tuple
 
 import numpy
@@ -7,293 +8,331 @@ import facefusion.jobs.job_manager
 import facefusion.jobs.job_store
 import facefusion.processors.core as processors
 from facefusion import config, content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer, inference_manager, logger, process_manager, state_manager, wording
+from facefusion.choices import execution_provider_set
 from facefusion.common_helper import get_first
-from facefusion.download import conditional_download_hashes, conditional_download_sources
+from facefusion.download import conditional_download_hashes, conditional_download_sources, resolve_download_url
 from facefusion.execution import has_execution_provider
 from facefusion.face_analyser import get_average_face, get_many_faces, get_one_face
 from facefusion.face_helper import paste_back, warp_face_by_face_landmark_5
 from facefusion.face_masker import create_occlusion_mask, create_region_mask, create_static_box_mask
-from facefusion.face_selector import find_similar_faces, sort_and_filter_faces
+from facefusion.face_selector import find_similar_faces, sort_and_filter_faces, sort_faces_by_order
 from facefusion.face_store import get_reference_faces
 from facefusion.filesystem import filter_image_paths, has_image, in_directory, is_image, is_video, resolve_relative_path, same_file_extension
-from facefusion.inference_manager import get_static_model_initializer
+from facefusion.model_helper import get_static_model_initializer
 from facefusion.processors import choices as processors_choices
 from facefusion.processors.pixel_boost import explode_pixel_boost, implode_pixel_boost
 from facefusion.processors.typing import FaceSwapperInputs
-from facefusion.program_helper import find_argument_group, suggest_face_swapper_pixel_boost_choices
+from facefusion.program_helper import find_argument_group
 from facefusion.thread_helper import conditional_thread_semaphore
-from facefusion.typing import ApplyStateItem, Args, Embedding, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
+from facefusion.typing import ApplyStateItem, Args, DownloadScope, Embedding, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
 from facefusion.vision import read_image, read_static_image, read_static_images, unpack_resolution, write_image
 
-MODEL_SET : ModelSet =\
-{
-	'blendswap_256':
+
+@lru_cache(maxsize = None)
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
+	return\
 	{
-		'hashes':
+		'blendswap_256':
 		{
-			'face_swapper':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/blendswap_256.hash',
-				'path': resolve_relative_path('../.assets/models/blendswap_256.hash')
-			}
-		},
-		'sources':
-		{
-			'face_swapper':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/blendswap_256.onnx',
-				'path': resolve_relative_path('../.assets/models/blendswap_256.onnx')
-			}
-		},
-		'type': 'blendswap',
-		'template': 'ffhq_512',
-		'size': (256, 256),
-		'mean': [ 0.0, 0.0, 0.0 ],
-		'standard_deviation': [ 1.0, 1.0, 1.0 ]
-	},
-	'ghost_1_256':
-	{
-		'hashes':
-		{
-			'face_swapper':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/ghost_1_256.hash',
-				'path': resolve_relative_path('../.assets/models/ghost_1_256.hash')
+				'face_swapper':
+				{
+					'url': resolve_download_url('models-3.0.0', 'blendswap_256.hash'),
+					'path': resolve_relative_path('../.assets/models/blendswap_256.hash')
+				}
 			},
-			'embedding_converter':
+			'sources':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_converter_ghost.hash',
-				'path': resolve_relative_path('../.assets/models/arcface_converter_ghost.hash')
-			}
-		},
-		'sources':
-		{
-			'face_swapper':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/ghost_1_256.onnx',
-				'path': resolve_relative_path('../.assets/models/ghost_1_256.onnx')
+				'face_swapper':
+				{
+					'url': resolve_download_url('models-3.0.0', 'blendswap_256.onnx'),
+					'path': resolve_relative_path('../.assets/models/blendswap_256.onnx')
+				}
 			},
-			'embedding_converter':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_converter_ghost.onnx',
-				'path': resolve_relative_path('../.assets/models/arcface_converter_ghost.onnx')
-			}
+			'type': 'blendswap',
+			'template': 'ffhq_512',
+			'size': (256, 256),
+			'mean': [ 0.0, 0.0, 0.0 ],
+			'standard_deviation': [ 1.0, 1.0, 1.0 ]
 		},
-		'type': 'ghost',
-		'template': 'arcface_112_v1',
-		'size': (256, 256),
-		'mean': [ 0.5, 0.5, 0.5 ],
-		'standard_deviation': [ 0.5, 0.5, 0.5 ]
-	},
-	'ghost_2_256':
-	{
-		'hashes':
+		'ghost_1_256':
 		{
-			'face_swapper':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/ghost_2_256.hash',
-				'path': resolve_relative_path('../.assets/models/ghost_2_256.hash')
+				'face_swapper':
+				{
+					'url': resolve_download_url('models-3.0.0', 'ghost_1_256.hash'),
+					'path': resolve_relative_path('../.assets/models/ghost_1_256.hash')
+				},
+				'embedding_converter':
+				{
+					'url': resolve_download_url('models-3.0.0', 'arcface_converter_ghost.hash'),
+					'path': resolve_relative_path('../.assets/models/arcface_converter_ghost.hash')
+				}
 			},
-			'embedding_converter':
+			'sources':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_converter_ghost.hash',
-				'path': resolve_relative_path('../.assets/models/arcface_converter_ghost.hash')
-			}
-		},
-		'sources':
-		{
-			'face_swapper':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/ghost_2_256.onnx',
-				'path': resolve_relative_path('../.assets/models/ghost_2_256.onnx')
+				'face_swapper':
+				{
+					'url': resolve_download_url('models-3.0.0', 'ghost_1_256.onnx'),
+					'path': resolve_relative_path('../.assets/models/ghost_1_256.onnx')
+				},
+				'embedding_converter':
+				{
+					'url': resolve_download_url('models-3.0.0', 'arcface_converter_ghost.onnx'),
+					'path': resolve_relative_path('../.assets/models/arcface_converter_ghost.onnx')
+				}
 			},
-			'embedding_converter':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_converter_ghost.onnx',
-				'path': resolve_relative_path('../.assets/models/arcface_converter_ghost.onnx')
-			}
+			'type': 'ghost',
+			'template': 'arcface_112_v1',
+			'size': (256, 256),
+			'mean': [ 0.5, 0.5, 0.5 ],
+			'standard_deviation': [ 0.5, 0.5, 0.5 ]
 		},
-		'type': 'ghost',
-		'template': 'arcface_112_v1',
-		'size': (256, 256),
-		'mean': [ 0.5, 0.5, 0.5 ],
-		'standard_deviation': [ 0.5, 0.5, 0.5 ]
-	},
-	'ghost_3_256':
-	{
-		'hashes':
+		'ghost_2_256':
 		{
-			'face_swapper':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/ghost_3_256.hash',
-				'path': resolve_relative_path('../.assets/models/ghost_3_256.hash')
+				'face_swapper':
+				{
+					'url': resolve_download_url('models-3.0.0', 'ghost_2_256.hash'),
+					'path': resolve_relative_path('../.assets/models/ghost_2_256.hash')
+				},
+				'embedding_converter':
+				{
+					'url': resolve_download_url('models-3.0.0', 'arcface_converter_ghost.hash'),
+					'path': resolve_relative_path('../.assets/models/arcface_converter_ghost.hash')
+				}
 			},
-			'embedding_converter':
+			'sources':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_converter_ghost.hash',
-				'path': resolve_relative_path('../.assets/models/arcface_converter_ghost.hash')
-			}
-		},
-		'sources':
-		{
-			'face_swapper':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/ghost_3_256.onnx',
-				'path': resolve_relative_path('../.assets/models/ghost_3_256.onnx')
+				'face_swapper':
+				{
+					'url': resolve_download_url('models-3.0.0', 'ghost_2_256.onnx'),
+					'path': resolve_relative_path('../.assets/models/ghost_2_256.onnx')
+				},
+				'embedding_converter':
+				{
+					'url': resolve_download_url('models-3.0.0', 'arcface_converter_ghost.onnx'),
+					'path': resolve_relative_path('../.assets/models/arcface_converter_ghost.onnx')
+				}
 			},
-			'embedding_converter':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_converter_ghost.onnx',
-				'path': resolve_relative_path('../.assets/models/arcface_converter_ghost.onnx')
-			}
+			'type': 'ghost',
+			'template': 'arcface_112_v1',
+			'size': (256, 256),
+			'mean': [ 0.5, 0.5, 0.5 ],
+			'standard_deviation': [ 0.5, 0.5, 0.5 ]
 		},
-		'type': 'ghost',
-		'template': 'arcface_112_v1',
-		'size': (256, 256),
-		'mean': [ 0.5, 0.5, 0.5 ],
-		'standard_deviation': [ 0.5, 0.5, 0.5 ]
-	},
-	'inswapper_128':
-	{
-		'hashes':
+		'ghost_3_256':
 		{
-			'face_swapper':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/inswapper_128.hash',
-				'path': resolve_relative_path('../.assets/models/inswapper_128.hash')
-			}
-		},
-		'sources':
-		{
-			'face_swapper':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/inswapper_128.onnx',
-				'path': resolve_relative_path('../.assets/models/inswapper_128.onnx')
-			}
-		},
-		'type': 'inswapper',
-		'template': 'arcface_128_v2',
-		'size': (128, 128),
-		'mean': [ 0.0, 0.0, 0.0 ],
-		'standard_deviation': [ 1.0, 1.0, 1.0 ]
-	},
-	'inswapper_128_fp16':
-	{
-		'hashes':
-		{
-			'face_swapper':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/inswapper_128_fp16.hash',
-				'path': resolve_relative_path('../.assets/models/inswapper_128_fp16.hash')
-			}
-		},
-		'sources':
-		{
-			'face_swapper':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/inswapper_128_fp16.onnx',
-				'path': resolve_relative_path('../.assets/models/inswapper_128_fp16.onnx')
-			}
-		},
-		'type': 'inswapper',
-		'template': 'arcface_128_v2',
-		'size': (128, 128),
-		'mean': [ 0.0, 0.0, 0.0 ],
-		'standard_deviation': [ 1.0, 1.0, 1.0 ]
-	},
-	'simswap_256':
-	{
-		'hashes':
-		{
-			'face_swapper':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/simswap_256.hash',
-				'path': resolve_relative_path('../.assets/models/simswap_256.hash')
+				'face_swapper':
+				{
+					'url': resolve_download_url('models-3.0.0', 'ghost_3_256.hash'),
+					'path': resolve_relative_path('../.assets/models/ghost_3_256.hash')
+				},
+				'embedding_converter':
+				{
+					'url': resolve_download_url('models-3.0.0', 'arcface_converter_ghost.hash'),
+					'path': resolve_relative_path('../.assets/models/arcface_converter_ghost.hash')
+				}
 			},
-			'embedding_converter':
+			'sources':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_converter_simswap.hash',
-				'path': resolve_relative_path('../.assets/models/arcface_converter_simswap.hash')
-			}
-		},
-		'sources':
-		{
-			'face_swapper':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/simswap_256.onnx',
-				'path': resolve_relative_path('../.assets/models/simswap_256.onnx')
+				'face_swapper':
+				{
+					'url': resolve_download_url('models-3.0.0', 'ghost_3_256.onnx'),
+					'path': resolve_relative_path('../.assets/models/ghost_3_256.onnx')
+				},
+				'embedding_converter':
+				{
+					'url': resolve_download_url('models-3.0.0', 'arcface_converter_ghost.onnx'),
+					'path': resolve_relative_path('../.assets/models/arcface_converter_ghost.onnx')
+				}
 			},
-			'embedding_converter':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_converter_simswap.onnx',
-				'path': resolve_relative_path('../.assets/models/arcface_converter_simswap.onnx')
-			}
+			'type': 'ghost',
+			'template': 'arcface_112_v1',
+			'size': (256, 256),
+			'mean': [ 0.5, 0.5, 0.5 ],
+			'standard_deviation': [ 0.5, 0.5, 0.5 ]
 		},
-		'type': 'simswap',
-		'template': 'arcface_112_v1',
-		'size': (256, 256),
-		'mean': [ 0.485, 0.456, 0.406 ],
-		'standard_deviation': [ 0.229, 0.224, 0.225 ]
-	},
-	'simswap_unofficial_512':
-	{
-		'hashes':
+		'hififace_unofficial_256':
 		{
-			'face_swapper':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/simswap_unofficial_512.hash',
-				'path': resolve_relative_path('../.assets/models/simswap_unofficial_512.hash')
+				'face_swapper':
+				{
+					'url': resolve_download_url('models-3.1.0', 'hififace_unofficial_256.hash'),
+					'path': resolve_relative_path('../.assets/models/hififace_unofficial_256.hash')
+				},
+				'embedding_converter':
+				{
+					'url': resolve_download_url('models-3.1.0', 'arcface_converter_hififace.hash'),
+					'path': resolve_relative_path('../.assets/models/arcface_converter_hififace.hash')
+				}
 			},
-			'embedding_converter':
+			'sources':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_converter_simswap.hash',
-				'path': resolve_relative_path('../.assets/models/arcface_converter_simswap.hash')
-			}
-		},
-		'sources':
-		{
-			'face_swapper':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/simswap_unofficial_512.onnx',
-				'path': resolve_relative_path('../.assets/models/simswap_unofficial_512.onnx')
+				'face_swapper':
+				{
+					'url': resolve_download_url('models-3.1.0', 'hififace_unofficial_256.onnx'),
+					'path': resolve_relative_path('../.assets/models/hififace_unofficial_256.onnx')
+				},
+				'embedding_converter':
+				{
+					'url': resolve_download_url('models-3.1.0', 'arcface_converter_hififace.onnx'),
+					'path': resolve_relative_path('../.assets/models/arcface_converter_hififace.onnx')
+				}
 			},
-			'embedding_converter':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/arcface_converter_simswap.onnx',
-				'path': resolve_relative_path('../.assets/models/arcface_converter_simswap.onnx')
-			}
+			'type': 'hififace',
+			'template': 'mtcnn_512',
+			'size': (256, 256),
+			'mean': [ 0.5, 0.5, 0.5 ],
+			'standard_deviation': [ 0.5, 0.5, 0.5 ]
 		},
-		'type': 'simswap',
-		'template': 'arcface_112_v1',
-		'size': (512, 512),
-		'mean': [ 0.0, 0.0, 0.0 ],
-		'standard_deviation': [ 1.0, 1.0, 1.0 ]
-	},
-	'uniface_256':
-	{
-		'hashes':
+		'inswapper_128':
 		{
-			'face_swapper':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/uniface_256.hash',
-				'path': resolve_relative_path('../.assets/models/uniface_256.hash')
-			}
+				'face_swapper':
+				{
+					'url': resolve_download_url('models-3.0.0', 'inswapper_128.hash'),
+					'path': resolve_relative_path('../.assets/models/inswapper_128.hash')
+				}
+			},
+			'sources':
+			{
+				'face_swapper':
+				{
+					'url': resolve_download_url('models-3.0.0', 'inswapper_128.onnx'),
+					'path': resolve_relative_path('../.assets/models/inswapper_128.onnx')
+				}
+			},
+			'type': 'inswapper',
+			'template': 'arcface_128_v2',
+			'size': (128, 128),
+			'mean': [ 0.0, 0.0, 0.0 ],
+			'standard_deviation': [ 1.0, 1.0, 1.0 ]
 		},
-		'sources':
+		'inswapper_128_fp16':
 		{
-			'face_swapper':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/uniface_256.onnx',
-				'path': resolve_relative_path('../.assets/models/uniface_256.onnx')
-			}
+				'face_swapper':
+				{
+					'url': resolve_download_url('models-3.0.0', 'inswapper_128_fp16.hash'),
+					'path': resolve_relative_path('../.assets/models/inswapper_128_fp16.hash')
+				}
+			},
+			'sources':
+			{
+				'face_swapper':
+				{
+					'url': resolve_download_url('models-3.0.0', 'inswapper_128_fp16.onnx'),
+					'path': resolve_relative_path('../.assets/models/inswapper_128_fp16.onnx')
+				}
+			},
+			'type': 'inswapper',
+			'template': 'arcface_128_v2',
+			'size': (128, 128),
+			'mean': [ 0.0, 0.0, 0.0 ],
+			'standard_deviation': [ 1.0, 1.0, 1.0 ]
 		},
-		'type': 'uniface',
-		'template': 'ffhq_512',
-		'size': (256, 256),
-		'mean': [ 0.5, 0.5, 0.5 ],
-		'standard_deviation': [ 0.5, 0.5, 0.5 ]
+		'simswap_256':
+		{
+			'hashes':
+			{
+				'face_swapper':
+				{
+					'url': resolve_download_url('models-3.0.0', 'simswap_256.hash'),
+					'path': resolve_relative_path('../.assets/models/simswap_256.hash')
+				},
+				'embedding_converter':
+				{
+					'url': resolve_download_url('models-3.0.0', 'arcface_converter_simswap.hash'),
+					'path': resolve_relative_path('../.assets/models/arcface_converter_simswap.hash')
+				}
+			},
+			'sources':
+			{
+				'face_swapper':
+				{
+					'url': resolve_download_url('models-3.0.0', 'simswap_256.onnx'),
+					'path': resolve_relative_path('../.assets/models/simswap_256.onnx')
+				},
+				'embedding_converter':
+				{
+					'url': resolve_download_url('models-3.0.0', 'arcface_converter_simswap.onnx'),
+					'path': resolve_relative_path('../.assets/models/arcface_converter_simswap.onnx')
+				}
+			},
+			'type': 'simswap',
+			'template': 'arcface_112_v1',
+			'size': (256, 256),
+			'mean': [ 0.485, 0.456, 0.406 ],
+			'standard_deviation': [ 0.229, 0.224, 0.225 ]
+		},
+		'simswap_unofficial_512':
+		{
+			'hashes':
+			{
+				'face_swapper':
+				{
+					'url': resolve_download_url('models-3.0.0', 'simswap_unofficial_512.hash'),
+					'path': resolve_relative_path('../.assets/models/simswap_unofficial_512.hash')
+				},
+				'embedding_converter':
+				{
+					'url': resolve_download_url('models-3.0.0', 'arcface_converter_simswap.hash'),
+					'path': resolve_relative_path('../.assets/models/arcface_converter_simswap.hash')
+				}
+			},
+			'sources':
+			{
+				'face_swapper':
+				{
+					'url': resolve_download_url('models-3.0.0', 'simswap_unofficial_512.onnx'),
+					'path': resolve_relative_path('../.assets/models/simswap_unofficial_512.onnx')
+				},
+				'embedding_converter':
+				{
+					'url': resolve_download_url('models-3.0.0', 'arcface_converter_simswap.onnx'),
+					'path': resolve_relative_path('../.assets/models/arcface_converter_simswap.onnx')
+				}
+			},
+			'type': 'simswap',
+			'template': 'arcface_112_v1',
+			'size': (512, 512),
+			'mean': [ 0.0, 0.0, 0.0 ],
+			'standard_deviation': [ 1.0, 1.0, 1.0 ]
+		},
+		'uniface_256':
+		{
+			'hashes':
+			{
+				'face_swapper':
+				{
+					'url': resolve_download_url('models-3.0.0', 'uniface_256.hash'),
+					'path': resolve_relative_path('../.assets/models/uniface_256.hash')
+				}
+			},
+			'sources':
+			{
+				'face_swapper':
+				{
+					'url': resolve_download_url('models-3.0.0', 'uniface_256.onnx'),
+					'path': resolve_relative_path('../.assets/models/uniface_256.onnx')
+				}
+			},
+			'type': 'uniface',
+			'template': 'ffhq_512',
+			'size': (256, 256),
+			'mean': [ 0.5, 0.5, 0.5 ],
+			'standard_deviation': [ 0.5, 0.5, 0.5 ]
+		}
 	}
-}
 
 
 def get_inference_pool() -> InferencePool:
@@ -309,15 +348,15 @@ def clear_inference_pool() -> None:
 
 def get_model_options() -> ModelOptions:
 	face_swapper_model = state_manager.get_item('face_swapper_model')
-	face_swapper_model = 'inswapper_128' if has_execution_provider('coreml') and face_swapper_model == 'inswapper_128_fp16' else face_swapper_model
-	return MODEL_SET.get(face_swapper_model)
+	return create_static_model_set('full').get(face_swapper_model)
 
 
 def register_args(program : ArgumentParser) -> None:
 	group_processors = find_argument_group(program, 'processors')
 	if group_processors:
 		group_processors.add_argument('--face-swapper-model', help = wording.get('help.face_swapper_model'), default = config.get_str_value('processors.face_swapper_model', 'inswapper_128_fp16'), choices = processors_choices.face_swapper_set.keys())
-		face_swapper_pixel_boost_choices = suggest_face_swapper_pixel_boost_choices(program)
+		known_args, _ = program.parse_known_args()
+		face_swapper_pixel_boost_choices = processors_choices.face_swapper_set.get(known_args.face_swapper_model)
 		group_processors.add_argument('--face-swapper-pixel-boost', help = wording.get('help.face_swapper_pixel_boost'), default = config.get_str_value('processors.face_swapper_pixel_boost', get_first(face_swapper_pixel_boost_choices)), choices = face_swapper_pixel_boost_choices)
 		facefusion.jobs.job_store.register_step_keys([ 'face_swapper_model', 'face_swapper_pixel_boost' ])
 
@@ -328,11 +367,10 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
 
 
 def pre_check() -> bool:
-	download_directory_path = resolve_relative_path('../.assets/models')
 	model_hashes = get_model_options().get('hashes')
 	model_sources = get_model_options().get('sources')
 
-	return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources)
+	return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
 
 
 def pre_process(mode : ProcessMode) -> bool:
@@ -410,9 +448,12 @@ def forward_swap_face(source_face : Face, crop_vision_frame : VisionFrame) -> Vi
 	model_type = get_model_options().get('type')
 	face_swapper_inputs = {}
 
+	if has_execution_provider('coreml') and model_type in [ 'ghost', 'uniface' ]:
+		face_swapper.set_providers([ execution_provider_set.get('cpu') ])
+
 	for face_swapper_input in face_swapper.get_inputs():
 		if face_swapper_input.name == 'source':
-			if model_type == 'blendswap' or model_type == 'uniface':
+			if model_type in [ 'blendswap', 'uniface' ]:
 				face_swapper_inputs[face_swapper_input.name] = prepare_source_frame(source_face)
 			else:
 				face_swapper_inputs[face_swapper_input.name] = prepare_source_embedding(source_face)
@@ -493,7 +534,7 @@ def normalize_crop_frame(crop_vision_frame : VisionFrame) -> VisionFrame:
 	model_standard_deviation = get_model_options().get('standard_deviation')
 
 	crop_vision_frame = crop_vision_frame.transpose(1, 2, 0)
-	if model_type == 'ghost' or model_type == 'uniface':
+	if model_type in [ 'ghost', 'hififace', 'uniface' ]:
 		crop_vision_frame = crop_vision_frame * model_standard_deviation + model_mean
 	crop_vision_frame = crop_vision_frame.clip(0, 1)
 	crop_vision_frame = crop_vision_frame[:, :, ::-1] * 255
@@ -529,7 +570,13 @@ def process_frame(inputs : FaceSwapperInputs) -> VisionFrame:
 def process_frames(source_paths : List[str], queue_payloads : List[QueuePayload], update_progress : UpdateProgress) -> None:
 	reference_faces = get_reference_faces() if 'reference' in state_manager.get_item('face_selector_mode') else None
 	source_frames = read_static_images(source_paths)
-	source_faces = get_many_faces(source_frames)
+	source_faces = []
+
+	for source_frame in source_frames:
+		temp_faces = get_many_faces([ source_frame ])
+		temp_faces = sort_faces_by_order(temp_faces, 'large-small')
+		if temp_faces:
+			source_faces.append(get_first(temp_faces))
 	source_face = get_average_face(source_faces)
 
 	for queue_payload in process_manager.manage(queue_payloads):
@@ -548,7 +595,13 @@ def process_frames(source_paths : List[str], queue_payloads : List[QueuePayload]
 def process_image(source_paths : List[str], target_path : str, output_path : str) -> None:
 	reference_faces = get_reference_faces() if 'reference' in state_manager.get_item('face_selector_mode') else None
 	source_frames = read_static_images(source_paths)
-	source_faces = get_many_faces(source_frames)
+	source_faces = []
+
+	for source_frame in source_frames:
+		temp_faces = get_many_faces([ source_frame ])
+		temp_faces = sort_faces_by_order(temp_faces, 'large-small')
+		if temp_faces:
+			source_faces.append(get_first(temp_faces))
 	source_face = get_average_face(source_faces)
 	target_vision_frame = read_static_image(target_path)
 	output_vision_frame = process_frame(

facefusion/processors/modules/frame_colorizer.py

@@ -1,4 +1,5 @@
 from argparse import ArgumentParser
+from functools import lru_cache
 from typing import List
 
 import cv2
@@ -9,118 +10,121 @@ import facefusion.jobs.job_store
 import facefusion.processors.core as processors
 from facefusion import config, content_analyser, inference_manager, logger, process_manager, state_manager, wording
 from facefusion.common_helper import create_int_metavar
-from facefusion.download import conditional_download_hashes, conditional_download_sources
+from facefusion.download import conditional_download_hashes, conditional_download_sources, resolve_download_url
 from facefusion.filesystem import in_directory, is_image, is_video, resolve_relative_path, same_file_extension
 from facefusion.processors import choices as processors_choices
 from facefusion.processors.typing import FrameColorizerInputs
 from facefusion.program_helper import find_argument_group
 from facefusion.thread_helper import thread_semaphore
-from facefusion.typing import ApplyStateItem, Args, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
+from facefusion.typing import ApplyStateItem, Args, DownloadScope, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
 from facefusion.vision import read_image, read_static_image, unpack_resolution, write_image
 
-MODEL_SET : ModelSet =\
-{
-	'ddcolor':
+
+@lru_cache(maxsize = None)
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
+	return\
 	{
-		'hashes':
+		'ddcolor':
 		{
-			'frame_colorizer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/ddcolor.hash',
-				'path': resolve_relative_path('../.assets/models/ddcolor.hash')
-			}
+				'frame_colorizer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'ddcolor.hash'),
+					'path': resolve_relative_path('../.assets/models/ddcolor.hash')
+				}
+			},
+			'sources':
+			{
+				'frame_colorizer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'ddcolor.onnx'),
+					'path': resolve_relative_path('../.assets/models/ddcolor.onnx')
+				}
+			},
+			'type': 'ddcolor'
 		},
-		'sources':
+		'ddcolor_artistic':
 		{
-			'frame_colorizer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/ddcolor.onnx',
-				'path': resolve_relative_path('../.assets/models/ddcolor.onnx')
-			}
+				'frame_colorizer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'ddcolor_artistic.hash'),
+					'path': resolve_relative_path('../.assets/models/ddcolor_artistic.hash')
+				}
+			},
+			'sources':
+			{
+				'frame_colorizer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'ddcolor_artistic.onnx'),
+					'path': resolve_relative_path('../.assets/models/ddcolor_artistic.onnx')
+				}
+			},
+			'type': 'ddcolor'
 		},
-		'type': 'ddcolor'
-	},
-	'ddcolor_artistic':
-	{
-		'hashes':
+		'deoldify':
 		{
-			'frame_colorizer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/ddcolor_artistic.hash',
-				'path': resolve_relative_path('../.assets/models/ddcolor_artistic.hash')
-			}
+				'frame_colorizer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'deoldify.hash'),
+					'path': resolve_relative_path('../.assets/models/deoldify.hash')
+				}
+			},
+			'sources':
+			{
+				'frame_colorizer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'deoldify.onnx'),
+					'path': resolve_relative_path('../.assets/models/deoldify.onnx')
+				}
+			},
+			'type': 'deoldify'
 		},
-		'sources':
+		'deoldify_artistic':
 		{
-			'frame_colorizer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/ddcolor_artistic.onnx',
-				'path': resolve_relative_path('../.assets/models/ddcolor_artistic.onnx')
-			}
+				'frame_colorizer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'deoldify_artistic.hash'),
+					'path': resolve_relative_path('../.assets/models/deoldify_artistic.hash')
+				}
+			},
+			'sources':
+			{
+				'frame_colorizer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'deoldify_artistic.onnx'),
+					'path': resolve_relative_path('../.assets/models/deoldify_artistic.onnx')
+				}
+			},
+			'type': 'deoldify'
 		},
-		'type': 'ddcolor'
-	},
-	'deoldify':
-	{
-		'hashes':
+		'deoldify_stable':
 		{
-			'frame_colorizer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/deoldify.hash',
-				'path': resolve_relative_path('../.assets/models/deoldify.hash')
-			}
-		},
-		'sources':
-		{
-			'frame_colorizer':
+				'frame_colorizer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'deoldify_stable.hash'),
+					'path': resolve_relative_path('../.assets/models/deoldify_stable.hash')
+				}
+			},
+			'sources':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/deoldify.onnx',
-				'path': resolve_relative_path('../.assets/models/deoldify.onnx')
-			}
-		},
-		'type': 'deoldify'
-	},
-	'deoldify_artistic':
-	{
-		'hashes':
-		{
-			'frame_colorizer':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/deoldify_artistic.hash',
-				'path': resolve_relative_path('../.assets/models/deoldify_artistic.hash')
-			}
-		},
-		'sources':
-		{
-			'frame_colorizer':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/deoldify_artistic.onnx',
-				'path': resolve_relative_path('../.assets/models/deoldify_artistic.onnx')
-			}
-		},
-		'type': 'deoldify'
-	},
-	'deoldify_stable':
-	{
-		'hashes':
-		{
-			'frame_colorizer':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/deoldify_stable.hash',
-				'path': resolve_relative_path('../.assets/models/deoldify_stable.hash')
-			}
-		},
-		'sources':
-		{
-			'frame_colorizer':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/deoldify_stable.onnx',
-				'path': resolve_relative_path('../.assets/models/deoldify_stable.onnx')
-			}
-		},
-		'type': 'deoldify'
+				'frame_colorizer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'deoldify_stable.onnx'),
+					'path': resolve_relative_path('../.assets/models/deoldify_stable.onnx')
+				}
+			},
+			'type': 'deoldify'
+		}
 	}
-}
 
 
 def get_inference_pool() -> InferencePool:
@@ -136,7 +140,7 @@ def clear_inference_pool() -> None:
 
 def get_model_options() -> ModelOptions:
 	frame_colorizer_model = state_manager.get_item('frame_colorizer_model')
-	return MODEL_SET.get(frame_colorizer_model)
+	return create_static_model_set('full').get(frame_colorizer_model)
 
 
 def register_args(program : ArgumentParser) -> None:
@@ -155,11 +159,10 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
 
 
 def pre_check() -> bool:
-	download_directory_path = resolve_relative_path('../.assets/models')
 	model_hashes = get_model_options().get('hashes')
 	model_sources = get_model_options().get('sources')
 
-	return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources)
+	return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
 
 
 def pre_process(mode : ProcessMode) -> bool:

facefusion/processors/modules/frame_enhancer.py

@@ -1,4 +1,5 @@
 from argparse import ArgumentParser
+from functools import lru_cache
 from typing import List
 
 import cv2
@@ -9,270 +10,378 @@ import facefusion.jobs.job_store
 import facefusion.processors.core as processors
 from facefusion import config, content_analyser, inference_manager, logger, process_manager, state_manager, wording
 from facefusion.common_helper import create_int_metavar
-from facefusion.download import conditional_download_hashes, conditional_download_sources
+from facefusion.download import conditional_download_hashes, conditional_download_sources, resolve_download_url
 from facefusion.filesystem import in_directory, is_image, is_video, resolve_relative_path, same_file_extension
 from facefusion.processors import choices as processors_choices
 from facefusion.processors.typing import FrameEnhancerInputs
 from facefusion.program_helper import find_argument_group
 from facefusion.thread_helper import conditional_thread_semaphore
-from facefusion.typing import ApplyStateItem, Args, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
+from facefusion.typing import ApplyStateItem, Args, DownloadScope, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
 from facefusion.vision import create_tile_frames, merge_tile_frames, read_image, read_static_image, write_image
 
-MODEL_SET : ModelSet =\
-{
-	'clear_reality_x4':
+
+@lru_cache(maxsize = None)
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
+	return\
 	{
-		'hashes':
+		'clear_reality_x4':
 		{
-			'frame_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/clear_reality_x4.hash',
-				'path': resolve_relative_path('../.assets/models/clear_reality_x4.hash')
-			}
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'clear_reality_x4.hash'),
+					'path': resolve_relative_path('../.assets/models/clear_reality_x4.hash')
+				}
+			},
+			'sources':
+			{
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'clear_reality_x4.onnx'),
+					'path': resolve_relative_path('../.assets/models/clear_reality_x4.onnx')
+				}
+			},
+			'size': (128, 8, 4),
+			'scale': 4
 		},
-		'sources':
+		'lsdir_x4':
 		{
-			'frame_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/clear_reality_x4.onnx',
-				'path': resolve_relative_path('../.assets/models/clear_reality_x4.onnx')
-			}
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'lsdir_x4.hash'),
+					'path': resolve_relative_path('../.assets/models/lsdir_x4.hash')
+				}
+			},
+			'sources':
+			{
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'lsdir_x4.onnx'),
+					'path': resolve_relative_path('../.assets/models/lsdir_x4.onnx')
+				}
+			},
+			'size': (128, 8, 4),
+			'scale': 4
 		},
-		'size': (128, 8, 4),
-		'scale': 4
-	},
-	'lsdir_x4':
-	{
-		'hashes':
+		'nomos8k_sc_x4':
 		{
-			'frame_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/lsdir_x4.hash',
-				'path': resolve_relative_path('../.assets/models/lsdir_x4.hash')
-			}
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'nomos8k_sc_x4.hash'),
+					'path': resolve_relative_path('../.assets/models/nomos8k_sc_x4.hash')
+				}
+			},
+			'sources':
+			{
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'nomos8k_sc_x4.onnx'),
+					'path': resolve_relative_path('../.assets/models/nomos8k_sc_x4.onnx')
+				}
+			},
+			'size': (128, 8, 4),
+			'scale': 4
 		},
-		'sources':
+		'real_esrgan_x2':
 		{
-			'frame_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/lsdir_x4.onnx',
-				'path': resolve_relative_path('../.assets/models/lsdir_x4.onnx')
-			}
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'real_esrgan_x2.hash'),
+					'path': resolve_relative_path('../.assets/models/real_esrgan_x2.hash')
+				}
+			},
+			'sources':
+			{
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'real_esrgan_x2.onnx'),
+					'path': resolve_relative_path('../.assets/models/real_esrgan_x2.onnx')
+				}
+			},
+			'size': (256, 16, 8),
+			'scale': 2
 		},
-		'size': (128, 8, 4),
-		'scale': 4
-	},
-	'nomos8k_sc_x4':
-	{
-		'hashes':
+		'real_esrgan_x2_fp16':
 		{
-			'frame_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/nomos8k_sc_x4.hash',
-				'path': resolve_relative_path('../.assets/models/nomos8k_sc_x4.hash')
-			}
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'real_esrgan_x2_fp16.hash'),
+					'path': resolve_relative_path('../.assets/models/real_esrgan_x2_fp16.hash')
+				}
+			},
+			'sources':
+			{
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'real_esrgan_x2_fp16.onnx'),
+					'path': resolve_relative_path('../.assets/models/real_esrgan_x2_fp16.onnx')
+				}
+			},
+			'size': (256, 16, 8),
+			'scale': 2
 		},
-		'sources':
+		'real_esrgan_x4':
 		{
-			'frame_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/nomos8k_sc_x4.onnx',
-				'path': resolve_relative_path('../.assets/models/nomos8k_sc_x4.onnx')
-			}
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'real_esrgan_x4.hash'),
+					'path': resolve_relative_path('../.assets/models/real_esrgan_x4.hash')
+				}
+			},
+			'sources':
+			{
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'real_esrgan_x4.onnx'),
+					'path': resolve_relative_path('../.assets/models/real_esrgan_x4.onnx')
+				}
+			},
+			'size': (256, 16, 8),
+			'scale': 4
 		},
-		'size': (128, 8, 4),
-		'scale': 4
-	},
-	'real_esrgan_x2':
-	{
-		'hashes':
+		'real_esrgan_x4_fp16':
 		{
-			'frame_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/real_esrgan_x2.hash',
-				'path': resolve_relative_path('../.assets/models/real_esrgan_x2.hash')
-			}
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'real_esrgan_x4_fp16.hash'),
+					'path': resolve_relative_path('../.assets/models/real_esrgan_x4_fp16.hash')
+				}
+			},
+			'sources':
+			{
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'real_esrgan_x4_fp16.onnx'),
+					'path': resolve_relative_path('../.assets/models/real_esrgan_x4_fp16.onnx')
+				}
+			},
+			'size': (256, 16, 8),
+			'scale': 4
 		},
-		'sources':
+		'real_esrgan_x8':
 		{
-			'frame_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/real_esrgan_x2.onnx',
-				'path': resolve_relative_path('../.assets/models/real_esrgan_x2.onnx')
-			}
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'real_esrgan_x8.hash'),
+					'path': resolve_relative_path('../.assets/models/real_esrgan_x8.hash')
+				}
+			},
+			'sources':
+			{
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'real_esrgan_x8.onnx'),
+					'path': resolve_relative_path('../.assets/models/real_esrgan_x8.onnx')
+				}
+			},
+			'size': (256, 16, 8),
+			'scale': 8
 		},
-		'size': (256, 16, 8),
-		'scale': 2
-	},
-	'real_esrgan_x2_fp16':
-	{
-		'hashes':
+		'real_esrgan_x8_fp16':
 		{
-			'frame_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/real_esrgan_x2_fp16.hash',
-				'path': resolve_relative_path('../.assets/models/real_esrgan_x2_fp16.hash')
-			}
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'real_esrgan_x8_fp16.hash'),
+					'path': resolve_relative_path('../.assets/models/real_esrgan_x8_fp16.hash')
+				}
+			},
+			'sources':
+			{
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'real_esrgan_x8_fp16.onnx'),
+					'path': resolve_relative_path('../.assets/models/real_esrgan_x8_fp16.onnx')
+				}
+			},
+			'size': (256, 16, 8),
+			'scale': 8
 		},
-		'sources':
+		'real_hatgan_x4':
 		{
-			'frame_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/real_esrgan_x2_fp16.onnx',
-				'path': resolve_relative_path('../.assets/models/real_esrgan_x2_fp16.onnx')
-			}
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'real_hatgan_x4.hash'),
+					'path': resolve_relative_path('../.assets/models/real_hatgan_x4.hash')
+				}
+			},
+			'sources':
+			{
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'real_hatgan_x4.onnx'),
+					'path': resolve_relative_path('../.assets/models/real_hatgan_x4.onnx')
+				}
+			},
+			'size': (256, 16, 8),
+			'scale': 4
 		},
-		'size': (256, 16, 8),
-		'scale': 2
-	},
-	'real_esrgan_x4':
-	{
-		'hashes':
+		'real_web_photo_x4':
 		{
-			'frame_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/real_esrgan_x4.hash',
-				'path': resolve_relative_path('../.assets/models/real_esrgan_x4.hash')
-			}
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.1.0', 'real_web_photo_x4.hash'),
+					'path': resolve_relative_path('../.assets/models/real_web_photo_x4.hash')
+				}
+			},
+			'sources':
+			{
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.1.0', 'real_web_photo_x4.onnx'),
+					'path': resolve_relative_path('../.assets/models/real_web_photo_x4.onnx')
+				}
+			},
+			'size': (64, 4, 2),
+			'scale': 4
 		},
-		'sources':
+		'realistic_rescaler_x4':
 		{
-			'frame_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/real_esrgan_x4.onnx',
-				'path': resolve_relative_path('../.assets/models/real_esrgan_x4.onnx')
-			}
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.1.0', 'realistic_rescaler_x4.hash'),
+					'path': resolve_relative_path('../.assets/models/realistic_rescaler_x4.hash')
+				}
+			},
+			'sources':
+			{
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.1.0', 'realistic_rescaler_x4.onnx'),
+					'path': resolve_relative_path('../.assets/models/realistic_rescaler_x4.onnx')
+				}
+			},
+			'size': (128, 8, 4),
+			'scale': 4
 		},
-		'size': (256, 16, 8),
-		'scale': 4
-	},
-	'real_esrgan_x4_fp16':
-	{
-		'hashes':
+		'remacri_x4':
 		{
-			'frame_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/real_esrgan_x4_fp16.hash',
-				'path': resolve_relative_path('../.assets/models/real_esrgan_x4_fp16.hash')
-			}
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.1.0', 'remacri_x4.hash'),
+					'path': resolve_relative_path('../.assets/models/remacri_x4.hash')
+				}
+			},
+			'sources':
+			{
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.1.0', 'remacri_x4.onnx'),
+					'path': resolve_relative_path('../.assets/models/remacri_x4.onnx')
+				}
+			},
+			'size': (128, 8, 4),
+			'scale': 4
 		},
-		'sources':
+		'siax_x4':
 		{
-			'frame_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/real_esrgan_x4_fp16.onnx',
-				'path': resolve_relative_path('../.assets/models/real_esrgan_x4_fp16.onnx')
-			}
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.1.0', 'siax_x4.hash'),
+					'path': resolve_relative_path('../.assets/models/siax_x4.hash')
+				}
+			},
+			'sources':
+			{
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.1.0', 'siax_x4.onnx'),
+					'path': resolve_relative_path('../.assets/models/siax_x4.onnx')
+				}
+			},
+			'size': (128, 8, 4),
+			'scale': 4
 		},
-		'size': (256, 16, 8),
-		'scale': 4
-	},
-	'real_esrgan_x8':
-	{
-		'hashes':
+		'span_kendata_x4':
 		{
-			'frame_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/real_esrgan_x8.hash',
-				'path': resolve_relative_path('../.assets/models/real_esrgan_x8.hash')
-			}
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'span_kendata_x4.hash'),
+					'path': resolve_relative_path('../.assets/models/span_kendata_x4.hash')
+				}
+			},
+			'sources':
+			{
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'span_kendata_x4.onnx'),
+					'path': resolve_relative_path('../.assets/models/span_kendata_x4.onnx')
+				}
+			},
+			'size': (128, 8, 4),
+			'scale': 4
 		},
-		'sources':
+		'swin2_sr_x4':
 		{
-			'frame_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/real_esrgan_x8.onnx',
-				'path': resolve_relative_path('../.assets/models/real_esrgan_x8.onnx')
-			}
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.1.0', 'swin2_sr_x4.hash'),
+					'path': resolve_relative_path('../.assets/models/swin2_sr_x4.hash')
+				}
+			},
+			'sources':
+			{
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.1.0', 'swin2_sr_x4.onnx'),
+					'path': resolve_relative_path('../.assets/models/swin2_sr_x4.onnx')
+				}
+			},
+			'size': (128, 8, 4),
+			'scale': 4
 		},
-		'size': (256, 16, 8),
-		'scale': 8
-	},
-	'real_esrgan_x8_fp16':
-	{
-		'hashes':
+		'ultra_sharp_x4':
 		{
-			'frame_enhancer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/real_esrgan_x8_fp16.hash',
-				'path': resolve_relative_path('../.assets/models/real_esrgan_x8_fp16.hash')
-			}
-		},
-		'sources':
-		{
-			'frame_enhancer':
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'ultra_sharp_x4.hash'),
+					'path': resolve_relative_path('../.assets/models/ultra_sharp_x4.hash')
+				}
+			},
+			'sources':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/real_esrgan_x8_fp16.onnx',
-				'path': resolve_relative_path('../.assets/models/real_esrgan_x8_fp16.onnx')
-			}
-		},
-		'size': (256, 16, 8),
-		'scale': 8
-	},
-	'real_hatgan_x4':
-	{
-		'hashes':
-		{
-			'frame_enhancer':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/real_hatgan_x4.hash',
-				'path': resolve_relative_path('../.assets/models/real_hatgan_x4.hash')
-			}
-		},
-		'sources':
-		{
-			'frame_enhancer':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/real_hatgan_x4.onnx',
-				'path': resolve_relative_path('../.assets/models/real_hatgan_x4.onnx')
-			}
-		},
-		'size': (256, 16, 8),
-		'scale': 4
-	},
-	'span_kendata_x4':
-	{
-		'hashes':
-		{
-			'frame_enhancer':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/span_kendata_x4.hash',
-				'path': resolve_relative_path('../.assets/models/span_kendata_x4.hash')
-			}
-		},
-		'sources':
-		{
-			'frame_enhancer':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/span_kendata_x4.onnx',
-				'path': resolve_relative_path('../.assets/models/span_kendata_x4.onnx')
-			}
-		},
-		'size': (128, 8, 4),
-		'scale': 4
-	},
-	'ultra_sharp_x4':
-	{
-		'hashes':
-		{
-			'frame_enhancer':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/ultra_sharp_x4.hash',
-				'path': resolve_relative_path('../.assets/models/ultra_sharp_x4.hash')
-			}
-		},
-		'sources':
-		{
-			'frame_enhancer':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/ultra_sharp_x4.onnx',
-				'path': resolve_relative_path('../.assets/models/ultra_sharp_x4.onnx')
-			}
-		},
-		'size': (128, 8, 4),
-		'scale': 4
+				'frame_enhancer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'ultra_sharp_x4.onnx'),
+					'path': resolve_relative_path('../.assets/models/ultra_sharp_x4.onnx')
+				}
+			},
+			'size': (128, 8, 4),
+			'scale': 4
+		}
 	}
-}
 
 
 def get_inference_pool() -> InferencePool:
@@ -288,7 +397,7 @@ def clear_inference_pool() -> None:
 
 def get_model_options() -> ModelOptions:
 	frame_enhancer_model = state_manager.get_item('frame_enhancer_model')
-	return MODEL_SET.get(frame_enhancer_model)
+	return create_static_model_set('full').get(frame_enhancer_model)
 
 
 def register_args(program : ArgumentParser) -> None:
@@ -305,11 +414,10 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
 
 
 def pre_check() -> bool:
-	download_directory_path = resolve_relative_path('../.assets/models')
 	model_hashes = get_model_options().get('hashes')
 	model_sources = get_model_options().get('sources')
 
-	return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources)
+	return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
 
 
 def pre_process(mode : ProcessMode) -> bool:

facefusion/processors/modules/lip_syncer.py

@@ -1,4 +1,5 @@
 from argparse import ArgumentParser
+from functools import lru_cache
 from typing import List
 
 import cv2
@@ -10,7 +11,7 @@ import facefusion.processors.core as processors
 from facefusion import config, content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer, inference_manager, logger, process_manager, state_manager, voice_extractor, wording
 from facefusion.audio import create_empty_audio_frame, get_voice_frame, read_static_voice
 from facefusion.common_helper import get_first
-from facefusion.download import conditional_download_hashes, conditional_download_sources
+from facefusion.download import conditional_download_hashes, conditional_download_sources, resolve_download_url
 from facefusion.face_analyser import get_many_faces, get_one_face
 from facefusion.face_helper import create_bounding_box, paste_back, warp_face_by_bounding_box, warp_face_by_face_landmark_5
 from facefusion.face_masker import create_mouth_mask, create_occlusion_mask, create_static_box_mask
@@ -21,52 +22,55 @@ from facefusion.processors import choices as processors_choices
 from facefusion.processors.typing import LipSyncerInputs
 from facefusion.program_helper import find_argument_group
 from facefusion.thread_helper import conditional_thread_semaphore
-from facefusion.typing import ApplyStateItem, Args, AudioFrame, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
+from facefusion.typing import ApplyStateItem, Args, AudioFrame, DownloadScope, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
 from facefusion.vision import read_image, read_static_image, restrict_video_fps, write_image
 
-MODEL_SET : ModelSet =\
-{
-	'wav2lip_96':
+
+@lru_cache(maxsize = None)
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
+	return\
 	{
-		'hashes':
+		'wav2lip_96':
 		{
-			'lip_syncer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/wav2lip_96.hash',
-				'path': resolve_relative_path('../.assets/models/wav2lip_96.hash')
-			}
+				'lip_syncer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'wav2lip_96.hash'),
+					'path': resolve_relative_path('../.assets/models/wav2lip_96.hash')
+				}
+			},
+			'sources':
+			{
+				'lip_syncer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'wav2lip_96.onnx'),
+					'path': resolve_relative_path('../.assets/models/wav2lip_96.onnx')
+				}
+			},
+			'size': (96, 96)
 		},
-		'sources':
+		'wav2lip_gan_96':
 		{
-			'lip_syncer':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/wav2lip_96.onnx',
-				'path': resolve_relative_path('../.assets/models/wav2lip_96.onnx')
-			}
-		},
-		'size': (96, 96)
-	},
-	'wav2lip_gan_96':
-	{
-		'hashes':
-		{
-			'lip_syncer':
+				'lip_syncer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'wav2lip_gan_96.hash'),
+					'path': resolve_relative_path('../.assets/models/wav2lip_gan_96.hash')
+				}
+			},
+			'sources':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/wav2lip_gan_96.hash',
-				'path': resolve_relative_path('../.assets/models/wav2lip_gan_96.hash')
-			}
-		},
-		'sources':
-		{
-			'lip_syncer':
-			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/wav2lip_gan_96.onnx',
-				'path': resolve_relative_path('../.assets/models/wav2lip_gan_96.onnx')
-			}
-		},
-		'size': (96, 96)
+				'lip_syncer':
+				{
+					'url': resolve_download_url('models-3.0.0', 'wav2lip_gan_96.onnx'),
+					'path': resolve_relative_path('../.assets/models/wav2lip_gan_96.onnx')
+				}
+			},
+			'size': (96, 96)
+		}
 	}
-}
 
 
 def get_inference_pool() -> InferencePool:
@@ -82,7 +86,7 @@ def clear_inference_pool() -> None:
 
 def get_model_options() -> ModelOptions:
 	lip_syncer_model = state_manager.get_item('lip_syncer_model')
-	return MODEL_SET.get(lip_syncer_model)
+	return create_static_model_set('full').get(lip_syncer_model)
 
 
 def register_args(program : ArgumentParser) -> None:
@@ -97,11 +101,10 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
 
 
 def pre_check() -> bool:
-	download_directory_path = resolve_relative_path('../.assets/models')
 	model_hashes = get_model_options().get('hashes')
 	model_sources = get_model_options().get('sources')
 
-	return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources)
+	return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
 
 
 def pre_process(mode : ProcessMode) -> bool:

facefusion/processors/typing.py

@@ -5,13 +5,162 @@ from numpy._typing import NDArray
 from facefusion.typing import AppContext, AudioFrame, Face, FaceSet, VisionFrame
 
 AgeModifierModel = Literal['styleganex_age']
+DeepSwapperModel = Literal\
+[
+	'druuzil/adrianne_palicki_384',
+	'druuzil/agnetha_falskog_224',
+	'druuzil/alan_ritchson_320',
+	'druuzil/alicia_vikander_320',
+	'druuzil/amber_midthunder_320',
+	'druuzil/andras_arato_384',
+	'druuzil/andrew_tate_320',
+	'druuzil/anne_hathaway_320',
+	'druuzil/anya_chalotra_320',
+	'druuzil/arnold_schwarzenegger_320',
+	'druuzil/benjamin_affleck_320',
+	'druuzil/benjamin_stiller_384',
+	'druuzil/bradley_pitt_224',
+	'druuzil/bryan_cranston_320',
+	'druuzil/catherine_blanchett_352',
+	'druuzil/christian_bale_320',
+	'druuzil/christopher_hemsworth_320',
+	'druuzil/christoph_waltz_384',
+	'druuzil/cillian_murphy_320',
+	'druuzil/cobie_smulders_256',
+	'druuzil/dwayne_johnson_384',
+	'druuzil/edward_norton_320',
+	'druuzil/elisabeth_shue_320',
+	'druuzil/elizabeth_olsen_384',
+	'druuzil/elon_musk_320',
+	'druuzil/emily_blunt_320',
+	'druuzil/emma_stone_384',
+	'druuzil/emma_watson_320',
+	'druuzil/erin_moriarty_384',
+	'druuzil/eva_green_320',
+	'druuzil/ewan_mcgregor_320',
+	'druuzil/florence_pugh_320',
+	'druuzil/freya_allan_320',
+	'druuzil/gary_cole_224',
+	'druuzil/gigi_hadid_224',
+	'druuzil/harrison_ford_384',
+	'druuzil/hayden_christensen_320',
+	'druuzil/heath_ledger_320',
+	'druuzil/henry_cavill_448',
+	'druuzil/hugh_jackman_384',
+	'druuzil/idris_elba_320',
+	'druuzil/jack_nicholson_320',
+	'druuzil/james_mcavoy_320',
+	'druuzil/james_varney_320',
+	'druuzil/jason_momoa_320',
+	'druuzil/jason_statham_320',
+	'druuzil/jennifer_connelly_384',
+	'druuzil/jimmy_donaldson_320',
+	'druuzil/jordan_peterson_384',
+	'druuzil/karl_urban_224',
+	'druuzil/kate_beckinsale_384',
+	'druuzil/laurence_fishburne_384',
+	'druuzil/lili_reinhart_320',
+	'druuzil/mads_mikkelsen_384',
+	'druuzil/mary_winstead_320',
+	'druuzil/melina_juergens_320',
+	'druuzil/michael_fassbender_320',
+	'druuzil/michael_fox_320',
+	'druuzil/millie_bobby_brown_320',
+	'druuzil/morgan_freeman_320',
+	'druuzil/patrick_stewart_320',
+	'druuzil/rebecca_ferguson_320',
+	'druuzil/scarlett_johansson_320',
+	'druuzil/seth_macfarlane_384',
+	'druuzil/thomas_cruise_320',
+	'druuzil/thomas_hanks_384',
+	'edel/emma_roberts_224',
+	'edel/ivanka_trump_224',
+	'edel/lize_dzjabrailova_224',
+	'edel/sidney_sweeney_224',
+	'edel/winona_ryder_224',
+	'iperov/alexandra_daddario_224',
+	'iperov/alexei_navalny_224',
+	'iperov/amber_heard_224',
+	'iperov/dilraba_dilmurat_224',
+	'iperov/elon_musk_224',
+	'iperov/emilia_clarke_224',
+	'iperov/emma_watson_224',
+	'iperov/erin_moriarty_224',
+	'iperov/jackie_chan_224',
+	'iperov/james_carrey_224',
+	'iperov/jason_statham_320',
+	'iperov/keanu_reeves_320',
+	'iperov/margot_robbie_224',
+	'iperov/natalie_dormer_224',
+	'iperov/nicolas_coppola_224',
+	'iperov/robert_downey_224',
+	'iperov/rowan_atkinson_224',
+	'iperov/ryan_reynolds_224',
+	'iperov/scarlett_johansson_224',
+	'iperov/sylvester_stallone_224',
+	'iperov/thomas_cruise_224',
+	'iperov/thomas_holland_224',
+	'iperov/vin_diesel_224',
+	'iperov/vladimir_putin_224',
+	'jen/angelica_trae_288',
+	'jen/ella_freya_224',
+	'jen/emma_myers_320',
+	'jen/evie_pickerill_224',
+	'jen/kang_hyewon_320',
+	'jen/maddie_mead_224',
+	'jen/nicole_turnbull_288',
+	'mats/alica_schmidt_320',
+	'mats/ashley_alexiss_224',
+	'mats/billie_eilish_224',
+	'mats/brie_larson_224',
+	'mats/cara_delevingne_224',
+	'mats/carolin_kebekus_224',
+	'mats/chelsea_clinton_224',
+	'mats/claire_boucher_224',
+	'mats/corinna_kopf_224',
+	'mats/florence_pugh_224',
+	'mats/hillary_clinton_224',
+	'mats/jenna_fischer_224',
+	'mats/kim_jisoo_320',
+	'mats/mica_suarez_320',
+	'mats/shailene_woodley_224',
+	'mats/shraddha_kapoor_320',
+	'mats/yu_jimin_352',
+	'rumateus/alison_brie_224',
+	'rumateus/amber_heard_224',
+	'rumateus/angelina_jolie_224',
+	'rumateus/aubrey_plaza_224',
+	'rumateus/bridget_regan_224',
+	'rumateus/cobie_smulders_224',
+	'rumateus/deborah_woll_224',
+	'rumateus/dua_lipa_224',
+	'rumateus/emma_stone_224',
+	'rumateus/hailee_steinfeld_224',
+	'rumateus/hilary_duff_224',
+	'rumateus/jessica_alba_224',
+	'rumateus/jessica_biel_224',
+	'rumateus/john_cena_224',
+	'rumateus/kim_kardashian_224',
+	'rumateus/kristen_bell_224',
+	'rumateus/lucy_liu_224',
+	'rumateus/margot_robbie_224',
+	'rumateus/megan_fox_224',
+	'rumateus/meghan_markle_224',
+	'rumateus/millie_bobby_brown_224',
+	'rumateus/natalie_portman_224',
+	'rumateus/nicki_minaj_224',
+	'rumateus/olivia_wilde_224',
+	'rumateus/shay_mitchell_224',
+	'rumateus/sophie_turner_224',
+	'rumateus/taylor_swift_224'
+]
 ExpressionRestorerModel = Literal['live_portrait']
 FaceDebuggerItem = Literal['bounding-box', 'face-landmark-5', 'face-landmark-5/68', 'face-landmark-68', 'face-landmark-68/5', 'face-mask', 'face-detector-score', 'face-landmarker-score', 'age', 'gender', 'race']
 FaceEditorModel = Literal['live_portrait']
 FaceEnhancerModel = Literal['codeformer', 'gfpgan_1.2', 'gfpgan_1.3', 'gfpgan_1.4', 'gpen_bfr_256', 'gpen_bfr_512', 'gpen_bfr_1024', 'gpen_bfr_2048', 'restoreformer_plus_plus']
-FaceSwapperModel = Literal['blendswap_256', 'ghost_1_256', 'ghost_2_256', 'ghost_3_256', 'inswapper_128', 'inswapper_128_fp16', 'simswap_256', 'simswap_unofficial_512', 'uniface_256']
+FaceSwapperModel = Literal['blendswap_256', 'ghost_1_256', 'ghost_2_256', 'ghost_3_256', 'hififace_unofficial_256', 'inswapper_128', 'inswapper_128_fp16', 'simswap_256', 'simswap_unofficial_512', 'uniface_256']
 FrameColorizerModel = Literal['ddcolor', 'ddcolor_artistic', 'deoldify', 'deoldify_artistic', 'deoldify_stable']
-FrameEnhancerModel = Literal['clear_reality_x4', 'lsdir_x4', 'nomos8k_sc_x4', 'real_esrgan_x2', 'real_esrgan_x2_fp16', 'real_esrgan_x4', 'real_esrgan_x4_fp16', 'real_hatgan_x4', 'real_esrgan_x8', 'real_esrgan_x8_fp16', 'span_kendata_x4', 'ultra_sharp_x4']
+FrameEnhancerModel = Literal['clear_reality_x4', 'lsdir_x4', 'nomos8k_sc_x4', 'real_esrgan_x2', 'real_esrgan_x2_fp16', 'real_esrgan_x4', 'real_esrgan_x4_fp16', 'real_esrgan_x8', 'real_esrgan_x8_fp16', 'real_hatgan_x4', 'real_web_photo_x4', 'realistic_rescaler_x4', 'remacri_x4', 'siax_x4', 'span_kendata_x4', 'swin2_sr_x4', 'ultra_sharp_x4']
 LipSyncerModel = Literal['wav2lip_96', 'wav2lip_gan_96']
 
 FaceSwapperSet = Dict[FaceSwapperModel, List[str]]
@@ -21,6 +170,11 @@ AgeModifierInputs = TypedDict('AgeModifierInputs',
 	'reference_faces' : FaceSet,
 	'target_vision_frame' : VisionFrame
 })
+DeepSwapperInputs = TypedDict('DeepSwapperInputs',
+{
+	'reference_faces' : FaceSet,
+	'target_vision_frame' : VisionFrame
+})
 ExpressionRestorerInputs = TypedDict('ExpressionRestorerInputs',
 {
 	'reference_faces' : FaceSet,
@@ -67,6 +221,8 @@ ProcessorStateKey = Literal\
 [
 	'age_modifier_model',
 	'age_modifier_direction',
+	'deep_swapper_model',
+	'deep_swapper_morph',
 	'expression_restorer_model',
 	'expression_restorer_factor',
 	'face_debugger_items',
@@ -87,6 +243,7 @@ ProcessorStateKey = Literal\
 	'face_editor_head_roll',
 	'face_enhancer_model',
 	'face_enhancer_blend',
+	'face_enhancer_weight',
 	'face_swapper_model',
 	'face_swapper_pixel_boost',
 	'frame_colorizer_model',
@@ -100,6 +257,8 @@ ProcessorState = TypedDict('ProcessorState',
 {
 	'age_modifier_model' : AgeModifierModel,
 	'age_modifier_direction' : int,
+	'deep_swapper_model' : DeepSwapperModel,
+	'deep_swapper_morph' : int,
 	'expression_restorer_model' : ExpressionRestorerModel,
 	'expression_restorer_factor' : int,
 	'face_debugger_items' : List[FaceDebuggerItem],
@@ -120,6 +279,7 @@ ProcessorState = TypedDict('ProcessorState',
 	'face_editor_head_roll' : float,
 	'face_enhancer_model' : FaceEnhancerModel,
 	'face_enhancer_blend' : int,
+	'face_enhancer_weight' : float,
 	'face_swapper_model' : FaceSwapperModel,
 	'face_swapper_pixel_boost' : str,
 	'frame_colorizer_model' : FrameColorizerModel,
@@ -131,6 +291,9 @@ ProcessorState = TypedDict('ProcessorState',
 })
 ProcessorStateSet = Dict[AppContext, ProcessorState]
 
+AgeModifierDirection = NDArray[Any]
+DeepSwapperMorph = NDArray[Any]
+FaceEnhancerWeight = NDArray[Any]
 LivePortraitPitch = float
 LivePortraitYaw = float
 LivePortraitRoll = float

facefusion/program.py

@@ -1,13 +1,13 @@
+import tempfile
 from argparse import ArgumentParser, HelpFormatter
 
 import facefusion.choices
 from facefusion import config, metadata, state_manager, wording
-from facefusion.common_helper import create_float_metavar, create_int_metavar
-from facefusion.execution import get_execution_provider_choices
+from facefusion.common_helper import create_float_metavar, create_int_metavar, get_last
+from facefusion.execution import get_execution_provider_set
 from facefusion.filesystem import list_directory
 from facefusion.jobs import job_store
 from facefusion.processors.core import get_processors_modules
-from facefusion.program_helper import remove_args, suggest_face_detector_choices
 
 
 def create_help_formatter_small(prog : str) -> HelpFormatter:
@@ -18,38 +18,86 @@ def create_help_formatter_large(prog : str) -> HelpFormatter:
 	return HelpFormatter(prog, max_help_position = 300)
 
 
-def create_config_program() -> ArgumentParser:
+def create_config_path_program() -> ArgumentParser:
 	program = ArgumentParser(add_help = False)
 	group_paths = program.add_argument_group('paths')
-	group_paths.add_argument('-c', '--config-path', help = wording.get('help.config_path'), default = 'facefusion.ini')
-	job_store.register_job_keys([ 'config-path' ])
+	group_paths.add_argument('--config-path', help = wording.get('help.config_path'), default = 'facefusion.ini')
+	job_store.register_job_keys([ 'config_path' ])
 	apply_config_path(program)
 	return program
 
 
+def create_temp_path_program() -> ArgumentParser:
+	program = ArgumentParser(add_help = False)
+	group_paths = program.add_argument_group('paths')
+	group_paths.add_argument('--temp-path', help = wording.get('help.temp_path'), default = config.get_str_value('paths.temp_path', tempfile.gettempdir()))
+	job_store.register_job_keys([ 'temp_path' ])
+	return program
+
+
 def create_jobs_path_program() -> ArgumentParser:
 	program = ArgumentParser(add_help = False)
 	group_paths = program.add_argument_group('paths')
-	group_paths.add_argument('-j', '--jobs-path', help = wording.get('help.jobs_path'), default = config.get_str_value('paths.jobs_path', '.jobs'))
+	group_paths.add_argument('--jobs-path', help = wording.get('help.jobs_path'), default = config.get_str_value('paths.jobs_path', '.jobs'))
 	job_store.register_job_keys([ 'jobs_path' ])
 	return program
 
 
-def create_paths_program() -> ArgumentParser:
+def create_source_paths_program() -> ArgumentParser:
+	program = ArgumentParser(add_help = False)
+	group_paths = program.add_argument_group('paths')
+	group_paths.add_argument('-s', '--source-paths', help = wording.get('help.source_paths'), default = config.get_str_list('paths.source_paths'), nargs = '+')
+	job_store.register_step_keys([ 'source_paths' ])
+	return program
+
+
+def create_target_path_program() -> ArgumentParser:
 	program = ArgumentParser(add_help = False)
 	group_paths = program.add_argument_group('paths')
-	group_paths.add_argument('-s', '--source-paths', help = wording.get('help.source_paths'), action = 'append', default = config.get_str_list('paths.source_paths'))
 	group_paths.add_argument('-t', '--target-path', help = wording.get('help.target_path'), default = config.get_str_value('paths.target_path'))
+	job_store.register_step_keys([ 'target_path' ])
+	return program
+
+
+def create_output_path_program() -> ArgumentParser:
+	program = ArgumentParser(add_help = False)
+	group_paths = program.add_argument_group('paths')
 	group_paths.add_argument('-o', '--output-path', help = wording.get('help.output_path'), default = config.get_str_value('paths.output_path'))
-	job_store.register_step_keys([ 'source_paths', 'target_path', 'output_path' ])
+	job_store.register_step_keys([ 'output_path' ])
+	return program
+
+
+def create_source_pattern_program() -> ArgumentParser:
+	program = ArgumentParser(add_help = False)
+	group_patterns = program.add_argument_group('patterns')
+	group_patterns.add_argument('-s', '--source-pattern', help = wording.get('help.source_pattern'), default = config.get_str_value('patterns.source_pattern'))
+	job_store.register_job_keys([ 'source_pattern' ])
+	return program
+
+
+def create_target_pattern_program() -> ArgumentParser:
+	program = ArgumentParser(add_help = False)
+	group_patterns = program.add_argument_group('patterns')
+	group_patterns.add_argument('-t', '--target-pattern', help = wording.get('help.target_pattern'), default = config.get_str_value('patterns.target_pattern'))
+	job_store.register_job_keys([ 'target_pattern' ])
+	return program
+
+
+def create_output_pattern_program() -> ArgumentParser:
+	program = ArgumentParser(add_help = False)
+	group_patterns = program.add_argument_group('patterns')
+	group_patterns.add_argument('-o', '--output-pattern', help = wording.get('help.output_pattern'), default = config.get_str_value('patterns.output_pattern'))
+	job_store.register_job_keys([ 'output_pattern' ])
 	return program
 
 
 def create_face_detector_program() -> ArgumentParser:
 	program = ArgumentParser(add_help = False)
 	group_face_detector = program.add_argument_group('face detector')
-	group_face_detector.add_argument('--face-detector-model', help = wording.get('help.face_detector_model'), default = config.get_str_value('face_detector.face_detector_model', 'yoloface'), choices = facefusion.choices.face_detector_set.keys())
-	group_face_detector.add_argument('--face-detector-size', help = wording.get('help.face_detector_size'), default = config.get_str_value('face_detector.face_detector_size', '640x640'), choices = suggest_face_detector_choices(program))
+	group_face_detector.add_argument('--face-detector-model', help = wording.get('help.face_detector_model'), default = config.get_str_value('face_detector.face_detector_model', 'yoloface'), choices = list(facefusion.choices.face_detector_set.keys()))
+	known_args, _ = program.parse_known_args()
+	face_detector_size_choices = facefusion.choices.face_detector_set.get(known_args.face_detector_model)
+	group_face_detector.add_argument('--face-detector-size', help = wording.get('help.face_detector_size'), default = config.get_str_value('face_detector.face_detector_size', get_last(face_detector_size_choices)), choices = face_detector_size_choices)
 	group_face_detector.add_argument('--face-detector-angles', help = wording.get('help.face_detector_angles'), type = int, default = config.get_int_list('face_detector.face_detector_angles', '0'), choices = facefusion.choices.face_detector_angles, nargs = '+', metavar = 'FACE_DETECTOR_ANGLES')
 	group_face_detector.add_argument('--face-detector-score', help = wording.get('help.face_detector_score'), type = float, default = config.get_float_value('face_detector.face_detector_score', '0.5'), choices = facefusion.choices.face_detector_score_range, metavar = create_float_metavar(facefusion.choices.face_detector_score_range))
 	job_store.register_step_keys([ 'face_detector_model', 'face_detector_angles', 'face_detector_size', 'face_detector_score' ])
@@ -142,16 +190,31 @@ def create_uis_program() -> ArgumentParser:
 
 def create_execution_program() -> ArgumentParser:
 	program = ArgumentParser(add_help = False)
-	execution_providers = get_execution_provider_choices()
 	group_execution = program.add_argument_group('execution')
 	group_execution.add_argument('--execution-device-id', help = wording.get('help.execution_device_id'), default = config.get_str_value('execution.execution_device_id', '0'))
-	group_execution.add_argument('--execution-providers', help = wording.get('help.execution_providers').format(choices = ', '.join(execution_providers)), default = config.get_str_list('execution.execution_providers', 'cpu'), choices = execution_providers, nargs = '+', metavar = 'EXECUTION_PROVIDERS')
+	group_execution.add_argument('--execution-providers', help = wording.get('help.execution_providers').format(choices = ', '.join(list(get_execution_provider_set().keys()))), default = config.get_str_list('execution.execution_providers', 'cpu'), choices = list(get_execution_provider_set().keys()), nargs = '+', metavar = 'EXECUTION_PROVIDERS')
 	group_execution.add_argument('--execution-thread-count', help = wording.get('help.execution_thread_count'), type = int, default = config.get_int_value('execution.execution_thread_count', '4'), choices = facefusion.choices.execution_thread_count_range, metavar = create_int_metavar(facefusion.choices.execution_thread_count_range))
 	group_execution.add_argument('--execution-queue-count', help = wording.get('help.execution_queue_count'), type = int, default = config.get_int_value('execution.execution_queue_count', '1'), choices = facefusion.choices.execution_queue_count_range, metavar = create_int_metavar(facefusion.choices.execution_queue_count_range))
 	job_store.register_job_keys([ 'execution_device_id', 'execution_providers', 'execution_thread_count', 'execution_queue_count' ])
 	return program
 
 
+def create_download_providers_program() -> ArgumentParser:
+	program = ArgumentParser(add_help = False)
+	group_download = program.add_argument_group('download')
+	group_download.add_argument('--download-providers', help = wording.get('help.download_providers').format(choices = ', '.join(list(facefusion.choices.download_provider_set.keys()))), default = config.get_str_list('download.download_providers', 'github'), choices = list(facefusion.choices.download_provider_set.keys()), nargs = '+', metavar = 'DOWNLOAD_PROVIDERS')
+	job_store.register_job_keys([ 'download_providers' ])
+	return program
+
+
+def create_download_scope_program() -> ArgumentParser:
+	program = ArgumentParser(add_help = False)
+	group_download = program.add_argument_group('download')
+	group_download.add_argument('--download-scope', help = wording.get('help.download_scope'), default = config.get_str_value('download.download_scope', 'lite'), choices = list(facefusion.choices.download_scopes))
+	job_store.register_job_keys([ 'download_scope' ])
+	return program
+
+
 def create_memory_program() -> ArgumentParser:
 	program = ArgumentParser(add_help = False)
 	group_memory = program.add_argument_group('memory')
@@ -161,18 +224,10 @@ def create_memory_program() -> ArgumentParser:
 	return program
 
 
-def create_skip_download_program() -> ArgumentParser:
+def create_misc_program() -> ArgumentParser:
 	program = ArgumentParser(add_help = False)
 	group_misc = program.add_argument_group('misc')
-	group_misc.add_argument('--skip-download', help = wording.get('help.skip_download'), action = 'store_true', default = config.get_bool_value('misc.skip_download'))
-	job_store.register_job_keys([ 'skip_download' ])
-	return program
-
-
-def create_log_level_program() -> ArgumentParser:
-	program = ArgumentParser(add_help = False)
-	group_misc = program.add_argument_group('misc')
-	group_misc.add_argument('--log-level', help = wording.get('help.log_level'), default = config.get_str_value('misc.log_level', 'info'), choices = facefusion.choices.log_level_set.keys())
+	group_misc.add_argument('--log-level', help = wording.get('help.log_level'), default = config.get_str_value('misc.log_level', 'info'), choices = list(facefusion.choices.log_level_set.keys()))
 	job_store.register_job_keys([ 'log_level' ])
 	return program
 
@@ -197,11 +252,11 @@ def create_step_index_program() -> ArgumentParser:
 
 
 def collect_step_program() -> ArgumentParser:
-	return ArgumentParser(parents= [ create_config_program(), create_jobs_path_program(), create_paths_program(), create_face_detector_program(), create_face_landmarker_program(), create_face_selector_program(), create_face_masker_program(), create_frame_extraction_program(), create_output_creation_program(), create_processors_program() ], add_help = False)
+	return ArgumentParser(parents= [ create_face_detector_program(), create_face_landmarker_program(), create_face_selector_program(), create_face_masker_program(), create_frame_extraction_program(), create_output_creation_program(), create_processors_program() ], add_help = False)
 
 
 def collect_job_program() -> ArgumentParser:
-	return ArgumentParser(parents= [ create_execution_program(), create_memory_program(), create_skip_download_program(), create_log_level_program() ], add_help = False)
+	return ArgumentParser(parents= [ create_execution_program(), create_download_providers_program(), create_memory_program(), create_misc_program() ], add_help = False)
 
 
 def create_program() -> ArgumentParser:
@@ -210,25 +265,26 @@ def create_program() -> ArgumentParser:
 	program.add_argument('-v', '--version', version = metadata.get('name') + ' ' + metadata.get('version'), action = 'version')
 	sub_program = program.add_subparsers(dest = 'command')
 	# general
-	sub_program.add_parser('run', help = wording.get('help.run'), parents = [ collect_step_program(), create_uis_program(), collect_job_program() ], formatter_class = create_help_formatter_large)
-	sub_program.add_parser('headless-run', help = wording.get('help.headless_run'), parents = [ collect_step_program(), collect_job_program() ], formatter_class = create_help_formatter_large)
-	sub_program.add_parser('force-download', help = wording.get('help.force_download'), parents = [ create_log_level_program() ], formatter_class = create_help_formatter_large)
+	sub_program.add_parser('run', help = wording.get('help.run'), parents = [ create_config_path_program(), create_temp_path_program(), create_jobs_path_program(), create_source_paths_program(), create_target_path_program(), create_output_path_program(), collect_step_program(), create_uis_program(), collect_job_program() ], formatter_class = create_help_formatter_large)
+	sub_program.add_parser('headless-run', help = wording.get('help.headless_run'), parents = [ create_config_path_program(), create_temp_path_program(), create_jobs_path_program(), create_source_paths_program(), create_target_path_program(), create_output_path_program(), collect_step_program(), collect_job_program() ], formatter_class = create_help_formatter_large)
+	sub_program.add_parser('batch-run', help = wording.get('help.batch_run'), parents = [ create_config_path_program(), create_temp_path_program(), create_jobs_path_program(), create_source_pattern_program(), create_target_pattern_program(), create_output_pattern_program(), collect_step_program(), collect_job_program() ], formatter_class = create_help_formatter_large)
+	sub_program.add_parser('force-download', help = wording.get('help.force_download'), parents = [ create_download_providers_program(), create_download_scope_program(), create_misc_program() ], formatter_class = create_help_formatter_large)
 	# job manager
-	sub_program.add_parser('job-list', help = wording.get('help.job_list'), parents = [ create_job_status_program(), create_jobs_path_program(), create_log_level_program() ], formatter_class = create_help_formatter_large)
-	sub_program.add_parser('job-create', help = wording.get('help.job_create'), parents = [ create_job_id_program(), create_jobs_path_program(), create_log_level_program() ], formatter_class = create_help_formatter_large)
-	sub_program.add_parser('job-submit', help = wording.get('help.job_submit'), parents = [ create_job_id_program(), create_jobs_path_program(), create_log_level_program() ], formatter_class = create_help_formatter_large)
-	sub_program.add_parser('job-submit-all', help = wording.get('help.job_submit_all'), parents = [ create_jobs_path_program(), create_log_level_program() ], formatter_class = create_help_formatter_large)
-	sub_program.add_parser('job-delete', help = wording.get('help.job_delete'), parents = [ create_job_id_program(), create_jobs_path_program(), create_log_level_program() ], formatter_class = create_help_formatter_large)
-	sub_program.add_parser('job-delete-all', help = wording.get('help.job_delete_all'), parents = [ create_jobs_path_program(), create_log_level_program() ], formatter_class = create_help_formatter_large)
-	sub_program.add_parser('job-add-step', help = wording.get('help.job_add_step'), parents = [ create_job_id_program(), collect_step_program(), create_log_level_program() ], formatter_class = create_help_formatter_large)
-	sub_program.add_parser('job-remix-step', help = wording.get('help.job_remix_step'), parents = [ create_job_id_program(), create_step_index_program(), remove_args(collect_step_program(), [ 'target_path' ]), create_log_level_program() ], formatter_class = create_help_formatter_large)
-	sub_program.add_parser('job-insert-step', help = wording.get('help.job_insert_step'), parents = [ create_job_id_program(), create_step_index_program(), collect_step_program(), create_log_level_program() ], formatter_class = create_help_formatter_large)
-	sub_program.add_parser('job-remove-step', help = wording.get('help.job_remove_step'), parents = [ create_job_id_program(), create_step_index_program(), create_jobs_path_program(), create_log_level_program() ], formatter_class = create_help_formatter_large)
+	sub_program.add_parser('job-list', help = wording.get('help.job_list'), parents = [ create_job_status_program(), create_jobs_path_program(), create_misc_program() ], formatter_class = create_help_formatter_large)
+	sub_program.add_parser('job-create', help = wording.get('help.job_create'), parents = [ create_job_id_program(), create_jobs_path_program(), create_misc_program() ], formatter_class = create_help_formatter_large)
+	sub_program.add_parser('job-submit', help = wording.get('help.job_submit'), parents = [ create_job_id_program(), create_jobs_path_program(), create_misc_program() ], formatter_class = create_help_formatter_large)
+	sub_program.add_parser('job-submit-all', help = wording.get('help.job_submit_all'), parents = [ create_jobs_path_program(), create_misc_program() ], formatter_class = create_help_formatter_large)
+	sub_program.add_parser('job-delete', help = wording.get('help.job_delete'), parents = [ create_job_id_program(), create_jobs_path_program(), create_misc_program() ], formatter_class = create_help_formatter_large)
+	sub_program.add_parser('job-delete-all', help = wording.get('help.job_delete_all'), parents = [ create_jobs_path_program(), create_misc_program() ], formatter_class = create_help_formatter_large)
+	sub_program.add_parser('job-add-step', help = wording.get('help.job_add_step'), parents = [ create_job_id_program(), create_config_path_program(), create_jobs_path_program(), create_source_paths_program(), create_target_path_program(), create_output_path_program(), collect_step_program(), create_misc_program() ], formatter_class = create_help_formatter_large)
+	sub_program.add_parser('job-remix-step', help = wording.get('help.job_remix_step'), parents = [ create_job_id_program(), create_step_index_program(), create_config_path_program(), create_jobs_path_program(), create_source_paths_program(), create_output_path_program(), collect_step_program(), create_misc_program() ], formatter_class = create_help_formatter_large)
+	sub_program.add_parser('job-insert-step', help = wording.get('help.job_insert_step'), parents = [ create_job_id_program(), create_step_index_program(), create_config_path_program(), create_jobs_path_program(), create_source_paths_program(), create_target_path_program(), create_output_path_program(), collect_step_program(), create_misc_program() ], formatter_class = create_help_formatter_large)
+	sub_program.add_parser('job-remove-step', help = wording.get('help.job_remove_step'), parents = [ create_job_id_program(), create_step_index_program(), create_jobs_path_program(), create_misc_program() ], formatter_class = create_help_formatter_large)
 	# job runner
-	sub_program.add_parser('job-run', help = wording.get('help.job_run'), parents = [ create_job_id_program(), create_config_program(), create_jobs_path_program(), collect_job_program() ], formatter_class = create_help_formatter_large)
-	sub_program.add_parser('job-run-all', help = wording.get('help.job_run_all'), parents = [ create_config_program(), create_jobs_path_program(), collect_job_program() ], formatter_class = create_help_formatter_large)
-	sub_program.add_parser('job-retry', help = wording.get('help.job_retry'), parents = [ create_job_id_program(), create_config_program(), create_jobs_path_program(), collect_job_program() ], formatter_class = create_help_formatter_large)
-	sub_program.add_parser('job-retry-all', help = wording.get('help.job_retry_all'), parents = [ create_config_program(), create_jobs_path_program(), collect_job_program() ], formatter_class = create_help_formatter_large)
+	sub_program.add_parser('job-run', help = wording.get('help.job_run'), parents = [ create_job_id_program(), create_config_path_program(), create_temp_path_program(), create_jobs_path_program(), collect_job_program() ], formatter_class = create_help_formatter_large)
+	sub_program.add_parser('job-run-all', help = wording.get('help.job_run_all'), parents = [ create_config_path_program(), create_temp_path_program(), create_jobs_path_program(), collect_job_program() ], formatter_class = create_help_formatter_large)
+	sub_program.add_parser('job-retry', help = wording.get('help.job_retry'), parents = [ create_job_id_program(), create_config_path_program(), create_temp_path_program(), create_jobs_path_program(), collect_job_program() ], formatter_class = create_help_formatter_large)
+	sub_program.add_parser('job-retry-all', help = wording.get('help.job_retry_all'), parents = [ create_config_path_program(), create_temp_path_program(), create_jobs_path_program(), collect_job_program() ], formatter_class = create_help_formatter_large)
 	return ArgumentParser(parents = [ program ], formatter_class = create_help_formatter_small, add_help = True)
 
 

facefusion/program_helper.py

@@ -1,8 +1,5 @@
 from argparse import ArgumentParser, _ArgumentGroup, _SubParsersAction
-from typing import List, Optional
-
-import facefusion.choices
-from facefusion.processors import choices as processors_choices
+from typing import Optional
 
 
 def find_argument_group(program : ArgumentParser, group_name : str) -> Optional[_ArgumentGroup]:
@@ -32,21 +29,3 @@ def validate_actions(program : ArgumentParser) -> bool:
 			elif action.default not in action.choices:
 				return False
 	return True
-
-
-def remove_args(program : ArgumentParser, remove_names : List[str]) -> ArgumentParser:
-	actions = [ action for action in program._actions if action.dest in remove_names ]
-
-	for action in actions:
-		program._actions.remove(action)
-	return program
-
-
-def suggest_face_detector_choices(program : ArgumentParser) -> List[str]:
-	known_args, _ = program.parse_known_args()
-	return facefusion.choices.face_detector_set.get(known_args.face_detector_model) #type:ignore[call-overload]
-
-
-def suggest_face_swapper_pixel_boost_choices(program : ArgumentParser) -> List[str]:
-	known_args, _ = program.parse_known_args()
-	return processors_choices.face_swapper_set.get(known_args.face_swapper_model) #type:ignore[call-overload]

facefusion/static/index.html

@@ -0,0 +1,242 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Demo</title>
+	<style>
+		.preview, meter {
+			width: 100%;
+		}
+		meter { border-radius: 0}
+        img, textarea {
+            width: 100%;
+        }
+        input[type="range"] {
+            width: 100%;
+            margin-top: 1em;
+        }
+	</style>
+</head>
+<body>
+	<div style="display:flex">
+		<div class="preview">
+			<h1>Preview</h1>
+			<div class="image-container">
+				<img id="image" alt="Frame Image">
+			</div>
+			<input type="range" id="slider" value="0">
+			<p>Frame: <span id="frameValue">0</span></p>
+			<button id="playBtn">Play</button>
+    		<button id="stopBtn" disabled>Stop</button>
+			<input type="checkbox" id="useWebSocket" /> Use WebSocket for Preview
+		</div>
+		<div>
+			<h1>Debug</h1>
+			<p>Video Memory <meter id="video_memory" min="0" max="100" value="0"></meter></p>
+			<p>GPU Utilization <meter id="gpu_utilization" min="0" max="100" value="0"></meter></p>
+			<textarea id="debug" rows="1" cols="80" readonly></textarea>
+			<textarea id="devices" rows="4" cols="80" readonly></textarea>
+			<textarea id="state" rows="30" cols="80" readonly></textarea>
+			<textarea id="log" rows="10" cols="80" readonly></textarea>
+			<textarea id="fps" rows="2" cols="80" readonly></textarea>
+		</div>
+	</div>
+ 	<script>
+		function createWebSocketConnection(url, debug, container) {
+			const socket = new WebSocket(url);
+
+			socket.onopen = () => {
+				debug.value = `WebSocket connection established for URL: ${url}`;
+			};
+
+			socket.onmessage = event => {
+				debug.value = `WebSocket Event: ${event.type}`;
+				container.value = event.data;
+			};
+
+			socket.onerror = error => {
+				debug.value = `WebSocket Error: ${error}`;
+			};
+
+			socket.onclose = () => {
+				debug.value = `WebSocket connection closed for URL: ${url} -> Reloading Page`;
+				setTimeout(() => location.reload(), 1000);
+			};
+
+			return socket;
+		}
+
+		devicesSocket = createWebSocketConnection('ws://127.0.0.1:8000/execution/devices', debug, devices);
+		createWebSocketConnection('ws://127.0.0.1:8000/state', debug, state);
+
+		devicesSocket.addEventListener('message', event => {
+			const data = JSON.parse(event.data)[0]
+			const freeMemory = data.video_memory.free.value;
+			const totalMemory = data.video_memory.total.value;
+			const usedMemory = totalMemory - freeMemory;
+			const usedMemoryPercentage = (usedMemory / totalMemory) * 100;
+
+			video_memory.value = usedMemoryPercentage;
+			gpu_utilization.value = data.utilization.gpu.value
+		})
+    </script>
+	<script>
+		const slider = document.getElementById('slider');
+		const image = document.getElementById('image');
+		const frameValue = document.getElementById('frameValue');
+		const playBtn = document.getElementById('playBtn');
+		const stopBtn = document.getElementById('stopBtn');
+		const logTextarea = document.getElementById('log');
+		const useWebSocketCheckbox = document.getElementById('useWebSocket');
+
+		let totalFrames = 0;
+		let currentFrame = 0;
+		let totalFps = 0;
+		let requestCount = 0;
+		let isPlaying = false;
+		let socket;
+
+		// Fetch the total frame count and set up the slider
+		async function fetchSliderTotal() {
+			try {
+				const start = performance.now();
+				const response = await fetch('http://127.0.0.1:8000/ui/preview_slider');
+				const end = performance.now();
+
+				logRequest('GET', 'http://127.0.0.1:8000/ui/preview_slider', start, end);
+
+				if (response.ok) {
+					const data = await response.json();
+					totalFrames = data.video_frame_total;
+					slider.max = totalFrames;
+					slider.value = 0;
+					frameValue.textContent = 0;
+					image.src = `http://127.0.0.1:8000/preview?frame_number=0`;
+				} else {
+					console.error('Failed to fetch total frame count');
+				}
+			} catch (error) {
+				console.error('Error fetching total frame count:', error);
+			}
+		}
+
+		// Function to log request details to the textarea
+		function logRequest(method, url, startTime, endTime) {
+			const duration = (endTime - startTime).toFixed(2);
+			const logMessage = `${method} ${url} | Duration: ${duration}ms\n`;
+
+			// Append to the log textarea
+			logTextarea.value += logMessage;
+			logTextarea.scrollTop = logTextarea.scrollHeight; // Auto scroll to the bottom
+		}
+
+		function logFps(startTime, endTime) {
+			const duration = (endTime - startTime).toFixed(2);
+			const durationInSeconds = duration / 1000;  // Convert ms to seconds
+			const fps = (1 / durationInSeconds).toFixed(2);  // FPS for this request
+
+			// Update total FPS and request count
+			totalFps += parseFloat(fps);
+			requestCount++;
+
+			// Calculate average FPS
+			const averageFps = (totalFps / requestCount).toFixed(2);
+
+			// Update the textarea with id 'fps' to show the average FPS
+			const fpsTextarea = document.getElementById('fps');
+			fpsTextarea.value = `Average FPS: ${averageFps}\n`;
+
+			// Optionally, you can append the current FPS to the textarea as well:
+			fpsTextarea.value += `Current FPS: ${fps}\n`;
+		}
+
+		// Function to update the image based on the slider's value or WebSocket message
+		function updateImage() {
+			const frameNumber = slider.value;
+
+
+			// If WebSocket is enabled, use WebSocket to fetch the image
+			if (useWebSocketCheckbox.checked) {
+				image.onload = null
+				if (!socket) {
+					socket = new WebSocket('ws://127.0.0.1:8000/preview');
+				}
+				const start = performance.now();
+				socket.send(JSON.stringify({ frame_number: frameNumber }));
+				socket.onmessage = function (event) {
+						const end = performance.now();
+						logRequest('WEBSOCKET', 'ws://127.0.0.1:8000/preview', start, end);
+						logFps(start, end)
+
+						// Create a Blob URL from the WebSocket message (assumed to be a Blob)
+						const imageUrl = URL.createObjectURL(event.data);
+
+						// Set the image source to the Blob URL
+						image.src = imageUrl;
+						frameValue.textContent = frameNumber;
+
+						// Continue if playing
+						if (isPlaying && currentFrame < totalFrames) {
+							currentFrame++;
+							slider.value = currentFrame;
+							updateImage(); // Continue to next frame
+						}
+					};
+			} else {
+				socket = null
+				// Use default fetch for the image
+				const start = performance.now();
+				image.src = `http://127.0.0.1:8000/preview?frame_number=${frameNumber}`;
+				image.onload = function () {
+					const end = performance.now();
+					logRequest('GET', image.src, start, end);
+					logFps(start, end)
+					frameValue.textContent = frameNumber;
+
+					// Continue if playing
+					if (isPlaying && currentFrame < totalFrames) {
+						currentFrame++;
+						slider.value = currentFrame;
+						updateImage(); // Continue to next frame
+					}
+				};
+			}
+		}
+
+		// Function to start the play action (without setInterval, only on image load)
+		function startPlay() {
+			playBtn.disabled = true;
+			stopBtn.disabled = false;
+			isPlaying = true;
+			currentFrame = parseInt(slider.value, 10);
+
+			// Start loading the first image
+			updateImage();
+		}
+
+		// Function to stop the play action
+		function stopPlay() {
+			isPlaying = false;
+			playBtn.disabled = false;
+			stopBtn.disabled = true;
+			if (socket) {
+				socket.close(); // Close WebSocket when stopping
+			}
+		}
+
+		// Event listeners for Play/Stop buttons
+		playBtn.addEventListener('click', startPlay);
+		stopBtn.addEventListener('click', stopPlay);
+
+		// Slider manual update
+		slider.addEventListener('change', function () {
+			currentFrame = slider.value;
+			updateImage();
+		});
+
+		// Fetch the total number of frames when the page loads
+		window.onload = fetchSliderTotal;
+	</script>
+</body>
+</html>

facefusion/temp_helper.py

@@ -1,10 +1,8 @@
-import glob
 import os
-import tempfile
 from typing import List
 
 from facefusion import state_manager
-from facefusion.filesystem import create_directory, move_file, remove_directory
+from facefusion.filesystem import create_directory, move_file, remove_directory, resolve_file_pattern
 
 
 def get_temp_file_path(file_path : str) -> str:
@@ -18,34 +16,9 @@ def move_temp_file(file_path : str, move_path : str) -> bool:
 	return move_file(temp_file_path, move_path)
 
 
-def get_temp_frame_paths(target_path : str) -> List[str]:
-	temp_frames_pattern = get_temp_frames_pattern(target_path, '*')
-	return sorted(glob.glob(temp_frames_pattern))
-
-
-def get_temp_frames_pattern(target_path : str, temp_frame_prefix : str) -> str:
-	temp_directory_path = get_temp_directory_path(target_path)
-	return os.path.join(temp_directory_path, temp_frame_prefix + '.' + state_manager.get_item('temp_frame_format'))
-
-
-def get_base_directory_path() -> str:
-	return os.path.join(tempfile.gettempdir(), 'facefusion')
-
-
-def create_base_directory() -> bool:
-	base_directory_path = get_base_directory_path()
-	return create_directory(base_directory_path)
-
-
-def clear_base_directory() -> bool:
-	base_directory_path = get_base_directory_path()
-	return remove_directory(base_directory_path)
-
-
 def get_temp_directory_path(file_path : str) -> str:
 	temp_file_name, _ = os.path.splitext(os.path.basename(file_path))
-	base_directory_path = get_base_directory_path()
-	return os.path.join(base_directory_path, temp_file_name)
+	return os.path.join(state_manager.get_item('temp_path'), 'facefusion', temp_file_name)
 
 
 def create_temp_directory(file_path : str) -> bool:
@@ -58,3 +31,13 @@ def clear_temp_directory(file_path : str) -> bool:
 		temp_directory_path = get_temp_directory_path(file_path)
 		return remove_directory(temp_directory_path)
 	return True
+
+
+def get_temp_frame_paths(target_path : str) -> List[str]:
+	temp_frames_pattern = get_temp_frames_pattern(target_path, '*')
+	return resolve_file_pattern(temp_frames_pattern)
+
+
+def get_temp_frames_pattern(target_path : str, temp_frame_prefix : str) -> str:
+	temp_directory_path = get_temp_directory_path(target_path)
+	return os.path.join(temp_directory_path, temp_frame_prefix + '.' + state_manager.get_item('temp_frame_format'))

facefusion/typing.py

@@ -67,6 +67,7 @@ Mel = NDArray[Any]
 MelFilterBank = NDArray[Any]
 
 Fps = float
+Duration = float
 Padding = Tuple[int, int, int, int]
 Orientation = Literal['landscape', 'portrait']
 Resolution = Tuple[int, int]
@@ -84,7 +85,7 @@ ProcessStep = Callable[[str, int, Args], bool]
 
 Content = Dict[str, Any]
 
-WarpTemplate = Literal['arcface_112_v1', 'arcface_112_v2', 'arcface_128_v2', 'ffhq_512']
+WarpTemplate = Literal['arcface_112_v1', 'arcface_112_v2', 'arcface_128_v2', 'dfl_whole_face', 'ffhq_512', 'mtcnn_512', 'styleganex_384']
 WarpTemplateSet = Dict[WarpTemplate, NDArray[Any]]
 ProcessMode = Literal['output', 'preview', 'stream']
 
@@ -95,7 +96,6 @@ LogLevelSet = Dict[LogLevel, int]
 TableHeaders = List[str]
 TableContents = List[List[Any]]
 
-VideoMemoryStrategy = Literal['strict', 'moderate', 'tolerant']
 FaceDetectorModel = Literal['many', 'retinaface', 'scrfd', 'yoloface']
 FaceLandmarkerModel = Literal['many', '2dfan4', 'peppa_wutz']
 FaceDetectorSet = Dict[FaceDetectorModel, List[str]]
@@ -103,18 +103,11 @@ FaceSelectorMode = Literal['many', 'one', 'reference']
 FaceSelectorOrder = Literal['left-right', 'right-left', 'top-bottom', 'bottom-top', 'small-large', 'large-small', 'best-worst', 'worst-best']
 FaceMaskType = Literal['box', 'occlusion', 'region']
 FaceMaskRegion = Literal['skin', 'left-eyebrow', 'right-eyebrow', 'left-eye', 'right-eye', 'glasses', 'nose', 'mouth', 'upper-lip', 'lower-lip']
-TempFrameFormat = Literal['jpg', 'png', 'bmp']
+TempFrameFormat = Literal['bmp', 'jpg', 'png']
 OutputAudioEncoder = Literal['aac', 'libmp3lame', 'libopus', 'libvorbis']
-OutputVideoEncoder = Literal['libx264', 'libx265', 'libvpx-vp9', 'h264_nvenc', 'hevc_nvenc', 'h264_amf', 'hevc_amf', 'h264_videotoolbox', 'hevc_videotoolbox']
+OutputVideoEncoder = Literal['libx264', 'libx265', 'libvpx-vp9', 'h264_nvenc', 'hevc_nvenc', 'h264_amf', 'hevc_amf','h264_qsv', 'hevc_qsv', 'h264_videotoolbox', 'hevc_videotoolbox']
 OutputVideoPreset = Literal['ultrafast', 'superfast', 'veryfast', 'faster', 'fast', 'medium', 'slow', 'slower', 'veryslow']
 
-Download = TypedDict('Download',
-{
-	'url' : str,
-	'path' : str
-})
-DownloadSet = Dict[str, Download]
-
 ModelOptions = Dict[str, Any]
 ModelSet = Dict[str, ModelOptions]
 ModelInitializer = NDArray[Any]
@@ -122,7 +115,6 @@ ModelInitializer = NDArray[Any]
 ExecutionProviderKey = Literal['cpu', 'coreml', 'cuda', 'directml', 'openvino', 'rocm', 'tensorrt']
 ExecutionProviderValue = Literal['CPUExecutionProvider', 'CoreMLExecutionProvider', 'CUDAExecutionProvider', 'DmlExecutionProvider', 'OpenVINOExecutionProvider', 'ROCMExecutionProvider', 'TensorrtExecutionProvider']
 ExecutionProviderSet = Dict[ExecutionProviderKey, ExecutionProviderValue]
-
 ValueAndUnit = TypedDict('ValueAndUnit',
 {
 	'value' : int,
@@ -140,13 +132,18 @@ ExecutionDeviceProduct = TypedDict('ExecutionDeviceProduct',
 })
 ExecutionDeviceVideoMemory = TypedDict('ExecutionDeviceVideoMemory',
 {
-	'total' : ValueAndUnit,
-	'free' : ValueAndUnit
+	'total' : Optional[ValueAndUnit],
+	'free' : Optional[ValueAndUnit]
+})
+ExecutionDeviceTemperature = TypedDict('ExecutionDeviceTemperature',
+{
+	'gpu' : Optional[ValueAndUnit],
+	'memory' : Optional[ValueAndUnit]
 })
 ExecutionDeviceUtilization = TypedDict('ExecutionDeviceUtilization',
 {
-	'gpu' : ValueAndUnit,
-	'memory' : ValueAndUnit
+	'gpu' : Optional[ValueAndUnit],
+	'memory' : Optional[ValueAndUnit]
 })
 ExecutionDevice = TypedDict('ExecutionDevice',
 {
@@ -154,9 +151,22 @@ ExecutionDevice = TypedDict('ExecutionDevice',
 	'framework' : ExecutionDeviceFramework,
 	'product' : ExecutionDeviceProduct,
 	'video_memory' : ExecutionDeviceVideoMemory,
+	'temperature': ExecutionDeviceTemperature,
 	'utilization' : ExecutionDeviceUtilization
 })
 
+DownloadProviderKey = Literal['github', 'huggingface']
+DownloadProviderSet = Dict[DownloadProviderKey, str]
+DownloadScope = Literal['lite', 'full']
+Download = TypedDict('Download',
+{
+	'url' : str,
+	'path' : str
+})
+DownloadSet = Dict[str, Download]
+
+VideoMemoryStrategy = Literal['strict', 'moderate', 'tolerant']
+
 AppContext = Literal['cli', 'ui']
 
 InferencePool = Dict[str, InferenceSession]
@@ -191,10 +201,14 @@ StateKey = Literal\
 [
 	'command',
 	'config_path',
+	'temp_path',
 	'jobs_path',
 	'source_paths',
 	'target_path',
 	'output_path',
+	'source_pattern',
+	'target_pattern',
+	'output_pattern',
 	'face_detector_model',
 	'face_detector_size',
 	'face_detector_angles',
@@ -235,9 +249,10 @@ StateKey = Literal\
 	'execution_providers',
 	'execution_thread_count',
 	'execution_queue_count',
+	'download_providers',
+	'download_scope',
 	'video_memory_strategy',
 	'system_memory_limit',
-	'skip_download',
 	'log_level',
 	'job_id',
 	'job_status',
@@ -247,10 +262,14 @@ State = TypedDict('State',
 {
 	'command' : str,
 	'config_path' : str,
+	'temp_path' : str,
 	'jobs_path' : str,
 	'source_paths' : List[str],
 	'target_path' : str,
 	'output_path' : str,
+	'source_pattern' : str,
+	'target_pattern' : str,
+	'output_pattern' : str,
 	'face_detector_model' : FaceDetectorModel,
 	'face_detector_size' : str,
 	'face_detector_angles' : List[Angle],
@@ -291,9 +310,10 @@ State = TypedDict('State',
 	'execution_providers' : List[ExecutionProviderKey],
 	'execution_thread_count' : int,
 	'execution_queue_count' : int,
+	'download_providers' : List[DownloadProviderKey],
+	'download_scope' : DownloadScope,
 	'video_memory_strategy' : VideoMemoryStrategy,
 	'system_memory_limit' : int,
-	'skip_download' : bool,
 	'log_level' : LogLevel,
 	'job_id' : str,
 	'job_status' : JobStatus,

facefusion/uis/assets/overrides.css

@@ -6,7 +6,29 @@
 
 :root:root:root:root input[type="number"]
 {
-	max-width: 6rem;
+	appearance: textfield;
+	border-radius: unset;
+	text-align: center;
+	order: 1;
+	padding: unset
+}
+
+:root:root:root:root input[type="number"]::-webkit-inner-spin-button
+{
+	appearance: none;
+}
+
+:root:root:root:root input[type="number"]:focus
+{
+	outline: unset;
+}
+
+:root:root:root:root .reset-button
+{
+	background: var(--background-fill-secondary);
+	border: unset;
+	font-size: unset;
+	padding: unset;
 }
 
 :root:root:root:root [type="checkbox"],
@@ -17,39 +39,25 @@
 	width: 1.125rem;
 }
 
-:root:root:root:root input[type="range"],
-:root:root:root:root .range-slider div
+:root:root:root:root input[type="range"]
 {
-	height: 0.5rem;
-	border-radius: 0.5rem;
+	background: transparent;
 }
 
 :root:root:root:root input[type="range"]::-moz-range-thumb,
 :root:root:root:root input[type="range"]::-webkit-slider-thumb
 {
 	background: var(--neutral-300);
-	border: unset;
+	box-shadow: unset;
 	border-radius: 50%;
 	height: 1.125rem;
 	width: 1.125rem;
 }
 
-:root:root:root:root input[type="range"]::-webkit-slider-thumb
+:root:root:root:root .thumbnail-item
 {
-	margin-top: 0.375rem;
-}
-
-:root:root:root:root .range-slider input[type="range"]::-webkit-slider-thumb
-{
-	margin-top: 0.125rem;
-}
-
-:root:root:root:root .range-slider div,
-:root:root:root:root .range-slider input[type="range"]
-{
-	bottom: 50%;
-	margin-top: -0.25rem;
-	top: 50%;
+	border: unset;
+	box-shadow: unset;
 }
 
 :root:root:root:root .grid-wrap.fixed-height
@@ -57,27 +65,40 @@
 	min-height: unset;
 }
 
-:root:root:root:root .generating,
-:root:root:root:root .thumbnail-item
+:root:root:root:root .tabs button:hover
 {
-	border: unset;
+	background: unset;
 }
 
+:root:root:root:root .tab-container
+{
+	height: 2.5rem;
+}
+
+:root:root:root:root .tabitem
+{
+	padding: 0.75rem 0 0 0
+}
+
+:root:root:root:root .tab-container:after,
+:root:root:root:root .tabs button:after
+{
+	border-width: 0.125rem;
+}
+
+:root:root:root:root .tab-container:after
+{
+	border-color: var(--block-background-fill)
+}
+
+:root:root:root:root .slider_input_container > span,
 :root:root:root:root .feather-upload,
+:root:root:root:root .toast-wrap,
 :root:root:root:root footer
 {
 	display: none;
 }
 
-:root:root:root:root .tab-nav > button
-{
-	border: unset;
-	box-shadow: 0 0.125rem;
-	font-size: 1.125em;
-	margin: 0.5rem 0.75rem;
-	padding: unset;
-}
-
 :root:root:root:root .image-frame
 {
 	width: 100%;
@@ -94,3 +115,11 @@
 	top: 0;
 	z-index: 100;
 }
+
+:root:root:root:root .block .error
+{
+	border: 0.125rem solid;
+	padding: 0.375rem 0.75rem;
+	font-size: 0.75rem;
+	text-transform: uppercase;
+}

facefusion/uis/choices.py

@@ -5,7 +5,7 @@ from facefusion.uis.typing import JobManagerAction, JobRunnerAction, WebcamMode
 job_manager_actions : List[JobManagerAction] = [ 'job-create', 'job-submit', 'job-delete', 'job-add-step', 'job-remix-step', 'job-insert-step', 'job-remove-step' ]
 job_runner_actions : List[JobRunnerAction] = [ 'job-run', 'job-run-all', 'job-retry', 'job-retry-all' ]
 
-common_options : List[str] = [ 'keep-temp', 'skip-audio', 'skip-download' ]
+common_options : List[str] = [ 'keep-temp', 'skip-audio' ]
 
 webcam_modes : List[WebcamMode] = [ 'inline', 'udp', 'v4l2' ]
 webcam_resolutions : List[str] = [ '320x240', '640x480', '800x600', '1024x768', '1280x720', '1280x960', '1920x1080', '2560x1440', '3840x2160' ]

facefusion/uis/components/age_modifier_options.py

@@ -17,11 +17,12 @@ def render() -> None:
 	global AGE_MODIFIER_MODEL_DROPDOWN
 	global AGE_MODIFIER_DIRECTION_SLIDER
 
+	has_age_modifier = 'age_modifier' in state_manager.get_item('processors')
 	AGE_MODIFIER_MODEL_DROPDOWN = gradio.Dropdown(
 		label = wording.get('uis.age_modifier_model_dropdown'),
 		choices = processors_choices.age_modifier_models,
 		value = state_manager.get_item('age_modifier_model'),
-		visible = 'age_modifier' in state_manager.get_item('processors')
+		visible = has_age_modifier
 	)
 	AGE_MODIFIER_DIRECTION_SLIDER = gradio.Slider(
 		label = wording.get('uis.age_modifier_direction_slider'),
@@ -29,7 +30,7 @@ def render() -> None:
 		step = calc_float_step(processors_choices.age_modifier_direction_range),
 		minimum = processors_choices.age_modifier_direction_range[0],
 		maximum = processors_choices.age_modifier_direction_range[-1],
-		visible = 'age_modifier' in state_manager.get_item('processors')
+		visible = has_age_modifier
 	)
 	register_ui_component('age_modifier_model_dropdown', AGE_MODIFIER_MODEL_DROPDOWN)
 	register_ui_component('age_modifier_direction_slider', AGE_MODIFIER_DIRECTION_SLIDER)

facefusion/uis/components/benchmark_options.py

@@ -16,8 +16,8 @@ def render() -> None:
 
 	BENCHMARK_RUNS_CHECKBOX_GROUP = gradio.CheckboxGroup(
 		label = wording.get('uis.benchmark_runs_checkbox_group'),
-		value = list(BENCHMARKS.keys()),
-		choices = list(BENCHMARKS.keys())
+		choices = list(BENCHMARKS.keys()),
+		value = list(BENCHMARKS.keys())
 	)
 	BENCHMARK_CYCLES_SLIDER = gradio.Slider(
 		label = wording.get('uis.benchmark_cycles_slider'),

facefusion/uis/components/common_options.py

@@ -13,8 +13,6 @@ def render() -> None:
 
 	common_options = []
 
-	if state_manager.get_item('skip_download'):
-		common_options.append('skip-download')
 	if state_manager.get_item('keep_temp'):
 		common_options.append('keep-temp')
 	if state_manager.get_item('skip_audio'):
@@ -32,9 +30,7 @@ def listen() -> None:
 
 
 def update(common_options : List[str]) -> None:
-	skip_temp = 'skip-download' in common_options
 	keep_temp = 'keep-temp' in common_options
 	skip_audio = 'skip-audio' in common_options
-	state_manager.set_item('skip_download', skip_temp)
 	state_manager.set_item('keep_temp', keep_temp)
 	state_manager.set_item('skip_audio', skip_audio)

facefusion/uis/components/deep_swapper_options.py

@@ -0,0 +1,65 @@
+from typing import List, Optional, Tuple
+
+import gradio
+
+from facefusion import state_manager, wording
+from facefusion.common_helper import calc_int_step
+from facefusion.processors import choices as processors_choices
+from facefusion.processors.core import load_processor_module
+from facefusion.processors.modules.deep_swapper import has_morph_input
+from facefusion.processors.typing import DeepSwapperModel
+from facefusion.uis.core import get_ui_component, register_ui_component
+
+DEEP_SWAPPER_MODEL_DROPDOWN : Optional[gradio.Dropdown] = None
+DEEP_SWAPPER_MORPH_SLIDER : Optional[gradio.Slider] = None
+
+
+def render() -> None:
+	global DEEP_SWAPPER_MODEL_DROPDOWN
+	global DEEP_SWAPPER_MORPH_SLIDER
+
+	has_deep_swapper = 'deep_swapper' in state_manager.get_item('processors')
+	DEEP_SWAPPER_MODEL_DROPDOWN = gradio.Dropdown(
+		label = wording.get('uis.deep_swapper_model_dropdown'),
+		choices = processors_choices.deep_swapper_models,
+		value = state_manager.get_item('deep_swapper_model'),
+		visible = has_deep_swapper
+	)
+	DEEP_SWAPPER_MORPH_SLIDER = gradio.Slider(
+		label = wording.get('uis.deep_swapper_morph_slider'),
+		value = state_manager.get_item('deep_swapper_morph'),
+		step = calc_int_step(processors_choices.deep_swapper_morph_range),
+		minimum = processors_choices.deep_swapper_morph_range[0],
+		maximum = processors_choices.deep_swapper_morph_range[-1],
+		visible = has_deep_swapper and has_morph_input()
+	)
+	register_ui_component('deep_swapper_model_dropdown', DEEP_SWAPPER_MODEL_DROPDOWN)
+	register_ui_component('deep_swapper_morph_slider', DEEP_SWAPPER_MORPH_SLIDER)
+
+
+def listen() -> None:
+	DEEP_SWAPPER_MODEL_DROPDOWN.change(update_deep_swapper_model, inputs = DEEP_SWAPPER_MODEL_DROPDOWN, outputs = [ DEEP_SWAPPER_MODEL_DROPDOWN, DEEP_SWAPPER_MORPH_SLIDER ])
+	DEEP_SWAPPER_MORPH_SLIDER.release(update_deep_swapper_morph, inputs = DEEP_SWAPPER_MORPH_SLIDER)
+
+	processors_checkbox_group = get_ui_component('processors_checkbox_group')
+	if processors_checkbox_group:
+		processors_checkbox_group.change(remote_update, inputs = processors_checkbox_group, outputs = [ DEEP_SWAPPER_MODEL_DROPDOWN, DEEP_SWAPPER_MORPH_SLIDER ])
+
+
+def remote_update(processors : List[str]) -> Tuple[gradio.Dropdown, gradio.Slider]:
+	has_deep_swapper = 'deep_swapper' in processors
+	return gradio.Dropdown(visible = has_deep_swapper), gradio.Slider(visible = has_deep_swapper and has_morph_input())
+
+
+def update_deep_swapper_model(deep_swapper_model : DeepSwapperModel) -> Tuple[gradio.Dropdown, gradio.Slider]:
+	deep_swapper_module = load_processor_module('deep_swapper')
+	deep_swapper_module.clear_inference_pool()
+	state_manager.set_item('deep_swapper_model', deep_swapper_model)
+
+	if deep_swapper_module.pre_check():
+		return gradio.Dropdown(value = state_manager.get_item('deep_swapper_model')), gradio.Slider(visible = has_morph_input())
+	return gradio.Dropdown(), gradio.Slider()
+
+
+def update_deep_swapper_morph(deep_swapper_morph : int) -> None:
+	state_manager.set_item('deep_swapper_morph', deep_swapper_morph)

facefusion/uis/components/download.py

@@ -0,0 +1,48 @@
+from typing import List, Optional
+
+import gradio
+
+from facefusion import content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer, state_manager, voice_extractor, wording
+from facefusion.choices import download_provider_set
+from facefusion.filesystem import list_directory
+from facefusion.processors.core import get_processors_modules
+from facefusion.typing import DownloadProviderKey
+
+DOWNLOAD_PROVIDERS_CHECKBOX_GROUP : Optional[gradio.CheckboxGroup] = None
+
+
+def render() -> None:
+	global DOWNLOAD_PROVIDERS_CHECKBOX_GROUP
+
+	DOWNLOAD_PROVIDERS_CHECKBOX_GROUP = gradio.CheckboxGroup(
+		label = wording.get('uis.download_providers_checkbox_group'),
+		choices = list(download_provider_set.keys()),
+		value = state_manager.get_item('download_providers')
+	)
+
+
+def listen() -> None:
+	DOWNLOAD_PROVIDERS_CHECKBOX_GROUP.change(update_download_providers, inputs = DOWNLOAD_PROVIDERS_CHECKBOX_GROUP, outputs = DOWNLOAD_PROVIDERS_CHECKBOX_GROUP)
+
+
+def update_download_providers(download_providers : List[DownloadProviderKey]) -> gradio.CheckboxGroup:
+	common_modules =\
+	[
+		content_analyser,
+		face_classifier,
+		face_detector,
+		face_landmarker,
+		face_recognizer,
+		face_masker,
+		voice_extractor
+	]
+	available_processors = list_directory('facefusion/processors/modules')
+	processor_modules = get_processors_modules(available_processors)
+
+	for module in common_modules + processor_modules:
+		if hasattr(module, 'create_static_model_set'):
+			module.create_static_model_set.cache_clear()
+
+	download_providers = download_providers or list(download_provider_set.keys())
+	state_manager.set_item('download_providers', download_providers)
+	return gradio.CheckboxGroup(value = state_manager.get_item('download_providers'))

facefusion/uis/components/execution.py

@@ -3,8 +3,9 @@ from typing import List, Optional
 import gradio
 
 from facefusion import content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer, state_manager, voice_extractor, wording
-from facefusion.execution import get_execution_provider_choices
-from facefusion.processors.core import clear_processors_modules
+from facefusion.execution import get_execution_provider_set
+from facefusion.filesystem import list_directory
+from facefusion.processors.core import get_processors_modules
 from facefusion.typing import ExecutionProviderKey
 
 EXECUTION_PROVIDERS_CHECKBOX_GROUP : Optional[gradio.CheckboxGroup] = None
@@ -15,7 +16,7 @@ def render() -> None:
 
 	EXECUTION_PROVIDERS_CHECKBOX_GROUP = gradio.CheckboxGroup(
 		label = wording.get('uis.execution_providers_checkbox_group'),
-		choices = get_execution_provider_choices(),
+		choices = list(get_execution_provider_set().keys()),
 		value = state_manager.get_item('execution_providers')
 	)
 
@@ -25,14 +26,23 @@ def listen() -> None:
 
 
 def update_execution_providers(execution_providers : List[ExecutionProviderKey]) -> gradio.CheckboxGroup:
-	content_analyser.clear_inference_pool()
-	face_classifier.clear_inference_pool()
-	face_detector.clear_inference_pool()
-	face_landmarker.clear_inference_pool()
-	face_masker.clear_inference_pool()
-	face_recognizer.clear_inference_pool()
-	voice_extractor.clear_inference_pool()
-	clear_processors_modules(state_manager.get_item('processors'))
-	execution_providers = execution_providers or get_execution_provider_choices()
+	common_modules =\
+	[
+		content_analyser,
+		face_classifier,
+		face_detector,
+		face_landmarker,
+		face_masker,
+		face_recognizer,
+		voice_extractor
+	]
+	available_processors = list_directory('facefusion/processors/modules')
+	processor_modules = get_processors_modules(available_processors)
+
+	for module in common_modules + processor_modules:
+		if hasattr(module, 'clear_inference_pool'):
+			module.clear_inference_pool()
+
+	execution_providers = execution_providers or list(get_execution_provider_set())
 	state_manager.set_item('execution_providers', execution_providers)
 	return gradio.CheckboxGroup(value = state_manager.get_item('execution_providers'))

facefusion/uis/components/expression_restorer_options.py

@@ -17,11 +17,12 @@ def render() -> None:
 	global EXPRESSION_RESTORER_MODEL_DROPDOWN
 	global EXPRESSION_RESTORER_FACTOR_SLIDER
 
+	has_expression_restorer = 'expression_restorer' in state_manager.get_item('processors')
 	EXPRESSION_RESTORER_MODEL_DROPDOWN = gradio.Dropdown(
 		label = wording.get('uis.expression_restorer_model_dropdown'),
 		choices = processors_choices.expression_restorer_models,
 		value = state_manager.get_item('expression_restorer_model'),
-		visible = 'expression_restorer' in state_manager.get_item('processors')
+		visible = has_expression_restorer
 	)
 	EXPRESSION_RESTORER_FACTOR_SLIDER = gradio.Slider(
 		label = wording.get('uis.expression_restorer_factor_slider'),
@@ -29,7 +30,7 @@ def render() -> None:
 		step = calc_float_step(processors_choices.expression_restorer_factor_range),
 		minimum = processors_choices.expression_restorer_factor_range[0],
 		maximum = processors_choices.expression_restorer_factor_range[-1],
-		visible = 'expression_restorer' in state_manager.get_item('processors'),
+		visible = has_expression_restorer
 	)
 	register_ui_component('expression_restorer_model_dropdown', EXPRESSION_RESTORER_MODEL_DROPDOWN)
 	register_ui_component('expression_restorer_factor_slider', EXPRESSION_RESTORER_FACTOR_SLIDER)

facefusion/uis/components/face_debugger_options.py

@@ -13,11 +13,12 @@ FACE_DEBUGGER_ITEMS_CHECKBOX_GROUP : Optional[gradio.CheckboxGroup] = None
 def render() -> None:
 	global FACE_DEBUGGER_ITEMS_CHECKBOX_GROUP
 
+	has_face_debugger = 'face_debugger' in state_manager.get_item('processors')
 	FACE_DEBUGGER_ITEMS_CHECKBOX_GROUP = gradio.CheckboxGroup(
 		label = wording.get('uis.face_debugger_items_checkbox_group'),
 		choices = processors_choices.face_debugger_items,
 		value = state_manager.get_item('face_debugger_items'),
-		visible = 'face_debugger' in state_manager.get_item('processors')
+		visible = has_face_debugger
 	)
 	register_ui_component('face_debugger_items_checkbox_group', FACE_DEBUGGER_ITEMS_CHECKBOX_GROUP)
 

facefusion/uis/components/face_detector.py

@@ -3,7 +3,7 @@ from typing import Optional, Sequence, Tuple
 import gradio
 
 import facefusion.choices
-from facefusion import choices, face_detector, state_manager, wording
+from facefusion import face_detector, state_manager, wording
 from facefusion.common_helper import calc_float_step, get_last
 from facefusion.typing import Angle, FaceDetectorModel, Score
 from facefusion.uis.core import register_ui_component
@@ -31,7 +31,7 @@ def render() -> None:
 	with gradio.Row():
 		FACE_DETECTOR_MODEL_DROPDOWN = gradio.Dropdown(
 			label = wording.get('uis.face_detector_model_dropdown'),
-			choices = facefusion.choices.face_detector_set.keys(),
+			choices = list(facefusion.choices.face_detector_set.keys()),
 			value = state_manager.get_item('face_detector_model')
 		)
 		FACE_DETECTOR_SIZE_DROPDOWN = gradio.Dropdown(**face_detector_size_dropdown_options)
@@ -65,7 +65,7 @@ def update_face_detector_model(face_detector_model : FaceDetectorModel) -> Tuple
 	state_manager.set_item('face_detector_model', face_detector_model)
 
 	if face_detector.pre_check():
-		face_detector_size_choices = choices.face_detector_set.get(state_manager.get_item('face_detector_model'))
+		face_detector_size_choices = facefusion.choices.face_detector_set.get(state_manager.get_item('face_detector_model'))
 		state_manager.set_item('face_detector_size', get_last(face_detector_size_choices))
 		return gradio.Dropdown(value = state_manager.get_item('face_detector_model')), gradio.Dropdown(value = state_manager.get_item('face_detector_size'), choices = face_detector_size_choices)
 	return gradio.Dropdown(), gradio.Dropdown()

facefusion/uis/components/face_editor_options.py

@@ -43,11 +43,12 @@ def render() -> None:
 	global FACE_EDITOR_HEAD_YAW_SLIDER
 	global FACE_EDITOR_HEAD_ROLL_SLIDER
 
+	has_face_editor = 'face_editor' in state_manager.get_item('processors')
 	FACE_EDITOR_MODEL_DROPDOWN = gradio.Dropdown(
 		label = wording.get('uis.face_editor_model_dropdown'),
 		choices = processors_choices.face_editor_models,
 		value = state_manager.get_item('face_editor_model'),
-		visible = 'face_editor' in state_manager.get_item('processors')
+		visible = has_face_editor
 	)
 	FACE_EDITOR_EYEBROW_DIRECTION_SLIDER = gradio.Slider(
 		label = wording.get('uis.face_editor_eyebrow_direction_slider'),
@@ -55,7 +56,7 @@ def render() -> None:
 		step = calc_float_step(processors_choices.face_editor_eyebrow_direction_range),
 		minimum = processors_choices.face_editor_eyebrow_direction_range[0],
 		maximum = processors_choices.face_editor_eyebrow_direction_range[-1],
-		visible = 'face_editor' in state_manager.get_item('processors'),
+		visible = has_face_editor
 	)
 	FACE_EDITOR_EYE_GAZE_HORIZONTAL_SLIDER = gradio.Slider(
 		label = wording.get('uis.face_editor_eye_gaze_horizontal_slider'),
@@ -63,7 +64,7 @@ def render() -> None:
 		step = calc_float_step(processors_choices.face_editor_eye_gaze_horizontal_range),
 		minimum = processors_choices.face_editor_eye_gaze_horizontal_range[0],
 		maximum = processors_choices.face_editor_eye_gaze_horizontal_range[-1],
-		visible = 'face_editor' in state_manager.get_item('processors'),
+		visible = has_face_editor
 	)
 	FACE_EDITOR_EYE_GAZE_VERTICAL_SLIDER = gradio.Slider(
 		label = wording.get('uis.face_editor_eye_gaze_vertical_slider'),
@@ -71,7 +72,7 @@ def render() -> None:
 		step = calc_float_step(processors_choices.face_editor_eye_gaze_vertical_range),
 		minimum = processors_choices.face_editor_eye_gaze_vertical_range[0],
 		maximum = processors_choices.face_editor_eye_gaze_vertical_range[-1],
-		visible = 'face_editor' in state_manager.get_item('processors'),
+		visible = has_face_editor
 	)
 	FACE_EDITOR_EYE_OPEN_RATIO_SLIDER = gradio.Slider(
 		label = wording.get('uis.face_editor_eye_open_ratio_slider'),
@@ -79,7 +80,7 @@ def render() -> None:
 		step = calc_float_step(processors_choices.face_editor_eye_open_ratio_range),
 		minimum = processors_choices.face_editor_eye_open_ratio_range[0],
 		maximum = processors_choices.face_editor_eye_open_ratio_range[-1],
-		visible = 'face_editor' in state_manager.get_item('processors'),
+		visible = has_face_editor
 	)
 	FACE_EDITOR_LIP_OPEN_RATIO_SLIDER = gradio.Slider(
 		label = wording.get('uis.face_editor_lip_open_ratio_slider'),
@@ -87,7 +88,7 @@ def render() -> None:
 		step = calc_float_step(processors_choices.face_editor_lip_open_ratio_range),
 		minimum = processors_choices.face_editor_lip_open_ratio_range[0],
 		maximum = processors_choices.face_editor_lip_open_ratio_range[-1],
-		visible = 'face_editor' in state_manager.get_item('processors'),
+		visible = has_face_editor
 	)
 	FACE_EDITOR_MOUTH_GRIM_SLIDER = gradio.Slider(
 		label = wording.get('uis.face_editor_mouth_grim_slider'),
@@ -95,7 +96,7 @@ def render() -> None:
 		step = calc_float_step(processors_choices.face_editor_mouth_grim_range),
 		minimum = processors_choices.face_editor_mouth_grim_range[0],
 		maximum = processors_choices.face_editor_mouth_grim_range[-1],
-		visible = 'face_editor' in state_manager.get_item('processors'),
+		visible = has_face_editor
 	)
 	FACE_EDITOR_MOUTH_POUT_SLIDER = gradio.Slider(
 		label = wording.get('uis.face_editor_mouth_pout_slider'),
@@ -103,7 +104,7 @@ def render() -> None:
 		step = calc_float_step(processors_choices.face_editor_mouth_pout_range),
 		minimum = processors_choices.face_editor_mouth_pout_range[0],
 		maximum = processors_choices.face_editor_mouth_pout_range[-1],
-		visible = 'face_editor' in state_manager.get_item('processors'),
+		visible = has_face_editor
 	)
 	FACE_EDITOR_MOUTH_PURSE_SLIDER = gradio.Slider(
 		label = wording.get('uis.face_editor_mouth_purse_slider'),
@@ -111,7 +112,7 @@ def render() -> None:
 		step = calc_float_step(processors_choices.face_editor_mouth_purse_range),
 		minimum = processors_choices.face_editor_mouth_purse_range[0],
 		maximum = processors_choices.face_editor_mouth_purse_range[-1],
-		visible = 'face_editor' in state_manager.get_item('processors'),
+		visible = has_face_editor
 	)
 	FACE_EDITOR_MOUTH_SMILE_SLIDER = gradio.Slider(
 		label = wording.get('uis.face_editor_mouth_smile_slider'),
@@ -119,7 +120,7 @@ def render() -> None:
 		step = calc_float_step(processors_choices.face_editor_mouth_smile_range),
 		minimum = processors_choices.face_editor_mouth_smile_range[0],
 		maximum = processors_choices.face_editor_mouth_smile_range[-1],
-		visible = 'face_editor' in state_manager.get_item('processors'),
+		visible = has_face_editor
 	)
 	FACE_EDITOR_MOUTH_POSITION_HORIZONTAL_SLIDER = gradio.Slider(
 		label = wording.get('uis.face_editor_mouth_position_horizontal_slider'),
@@ -127,7 +128,7 @@ def render() -> None:
 		step = calc_float_step(processors_choices.face_editor_mouth_position_horizontal_range),
 		minimum = processors_choices.face_editor_mouth_position_horizontal_range[0],
 		maximum = processors_choices.face_editor_mouth_position_horizontal_range[-1],
-		visible = 'face_editor' in state_manager.get_item('processors'),
+		visible = has_face_editor
 	)
 	FACE_EDITOR_MOUTH_POSITION_VERTICAL_SLIDER = gradio.Slider(
 		label = wording.get('uis.face_editor_mouth_position_vertical_slider'),
@@ -135,7 +136,7 @@ def render() -> None:
 		step = calc_float_step(processors_choices.face_editor_mouth_position_vertical_range),
 		minimum = processors_choices.face_editor_mouth_position_vertical_range[0],
 		maximum = processors_choices.face_editor_mouth_position_vertical_range[-1],
-		visible = 'face_editor' in state_manager.get_item('processors'),
+		visible = has_face_editor
 	)
 	FACE_EDITOR_HEAD_PITCH_SLIDER = gradio.Slider(
 		label = wording.get('uis.face_editor_head_pitch_slider'),
@@ -143,7 +144,7 @@ def render() -> None:
 		step = calc_float_step(processors_choices.face_editor_head_pitch_range),
 		minimum = processors_choices.face_editor_head_pitch_range[0],
 		maximum = processors_choices.face_editor_head_pitch_range[-1],
-		visible = 'face_editor' in state_manager.get_item('processors'),
+		visible = has_face_editor
 	)
 	FACE_EDITOR_HEAD_YAW_SLIDER = gradio.Slider(
 		label = wording.get('uis.face_editor_head_yaw_slider'),
@@ -151,7 +152,7 @@ def render() -> None:
 		step = calc_float_step(processors_choices.face_editor_head_yaw_range),
 		minimum = processors_choices.face_editor_head_yaw_range[0],
 		maximum = processors_choices.face_editor_head_yaw_range[-1],
-		visible = 'face_editor' in state_manager.get_item('processors'),
+		visible = has_face_editor
 	)
 	FACE_EDITOR_HEAD_ROLL_SLIDER = gradio.Slider(
 		label = wording.get('uis.face_editor_head_roll_slider'),
@@ -159,7 +160,7 @@ def render() -> None:
 		step = calc_float_step(processors_choices.face_editor_head_roll_range),
 		minimum = processors_choices.face_editor_head_roll_range[0],
 		maximum = processors_choices.face_editor_head_roll_range[-1],
-		visible = 'face_editor' in state_manager.get_item('processors'),
+		visible = has_face_editor
 	)
 	register_ui_component('face_editor_model_dropdown', FACE_EDITOR_MODEL_DROPDOWN)
 	register_ui_component('face_editor_eyebrow_direction_slider', FACE_EDITOR_EYEBROW_DIRECTION_SLIDER)

facefusion/uis/components/face_enhancer_options.py

@@ -3,25 +3,29 @@ from typing import List, Optional, Tuple
 import gradio
 
 from facefusion import state_manager, wording
-from facefusion.common_helper import calc_int_step
+from facefusion.common_helper import calc_float_step, calc_int_step
 from facefusion.processors import choices as processors_choices
 from facefusion.processors.core import load_processor_module
+from facefusion.processors.modules.face_enhancer import has_weight_input
 from facefusion.processors.typing import FaceEnhancerModel
 from facefusion.uis.core import get_ui_component, register_ui_component
 
 FACE_ENHANCER_MODEL_DROPDOWN : Optional[gradio.Dropdown] = None
 FACE_ENHANCER_BLEND_SLIDER : Optional[gradio.Slider] = None
+FACE_ENHANCER_WEIGHT_SLIDER : Optional[gradio.Slider] = None
 
 
 def render() -> None:
 	global FACE_ENHANCER_MODEL_DROPDOWN
 	global FACE_ENHANCER_BLEND_SLIDER
+	global FACE_ENHANCER_WEIGHT_SLIDER
 
+	has_face_enhancer = 'face_enhancer' in state_manager.get_item('processors')
 	FACE_ENHANCER_MODEL_DROPDOWN = gradio.Dropdown(
 		label = wording.get('uis.face_enhancer_model_dropdown'),
 		choices = processors_choices.face_enhancer_models,
 		value = state_manager.get_item('face_enhancer_model'),
-		visible = 'face_enhancer' in state_manager.get_item('processors')
+		visible = has_face_enhancer
 	)
 	FACE_ENHANCER_BLEND_SLIDER = gradio.Slider(
 		label = wording.get('uis.face_enhancer_blend_slider'),
@@ -29,35 +33,50 @@ def render() -> None:
 		step = calc_int_step(processors_choices.face_enhancer_blend_range),
 		minimum = processors_choices.face_enhancer_blend_range[0],
 		maximum = processors_choices.face_enhancer_blend_range[-1],
-		visible = 'face_enhancer' in state_manager.get_item('processors')
+		visible = has_face_enhancer
+	)
+	FACE_ENHANCER_WEIGHT_SLIDER = gradio.Slider(
+		label = wording.get('uis.face_enhancer_weight_slider'),
+		value = state_manager.get_item('face_enhancer_weight'),
+		step = calc_float_step(processors_choices.face_enhancer_weight_range),
+		minimum = processors_choices.face_enhancer_weight_range[0],
+		maximum = processors_choices.face_enhancer_weight_range[-1],
+		visible = has_face_enhancer and has_weight_input()
 	)
 	register_ui_component('face_enhancer_model_dropdown', FACE_ENHANCER_MODEL_DROPDOWN)
 	register_ui_component('face_enhancer_blend_slider', FACE_ENHANCER_BLEND_SLIDER)
+	register_ui_component('face_enhancer_weight_slider', FACE_ENHANCER_WEIGHT_SLIDER)
 
 
 def listen() -> None:
-	FACE_ENHANCER_MODEL_DROPDOWN.change(update_face_enhancer_model, inputs = FACE_ENHANCER_MODEL_DROPDOWN, outputs = FACE_ENHANCER_MODEL_DROPDOWN)
+	FACE_ENHANCER_MODEL_DROPDOWN.change(update_face_enhancer_model, inputs = FACE_ENHANCER_MODEL_DROPDOWN, outputs = [ FACE_ENHANCER_MODEL_DROPDOWN, FACE_ENHANCER_WEIGHT_SLIDER ])
 	FACE_ENHANCER_BLEND_SLIDER.release(update_face_enhancer_blend, inputs = FACE_ENHANCER_BLEND_SLIDER)
+	FACE_ENHANCER_WEIGHT_SLIDER.release(update_face_enhancer_weight, inputs = FACE_ENHANCER_WEIGHT_SLIDER)
 
 	processors_checkbox_group = get_ui_component('processors_checkbox_group')
 	if processors_checkbox_group:
-		processors_checkbox_group.change(remote_update, inputs = processors_checkbox_group, outputs = [ FACE_ENHANCER_MODEL_DROPDOWN, FACE_ENHANCER_BLEND_SLIDER ])
+		processors_checkbox_group.change(remote_update, inputs = processors_checkbox_group, outputs = [ FACE_ENHANCER_MODEL_DROPDOWN, FACE_ENHANCER_BLEND_SLIDER, FACE_ENHANCER_WEIGHT_SLIDER ])
 
 
-def remote_update(processors : List[str]) -> Tuple[gradio.Dropdown, gradio.Slider]:
+def remote_update(processors : List[str]) -> Tuple[gradio.Dropdown, gradio.Slider, gradio.Slider]:
 	has_face_enhancer = 'face_enhancer' in processors
-	return gradio.Dropdown(visible = has_face_enhancer), gradio.Slider(visible = has_face_enhancer)
+	return gradio.Dropdown(visible = has_face_enhancer), gradio.Slider(visible = has_face_enhancer), gradio.Slider(visible = has_face_enhancer and has_weight_input())
 
 
-def update_face_enhancer_model(face_enhancer_model : FaceEnhancerModel) -> gradio.Dropdown:
+def update_face_enhancer_model(face_enhancer_model : FaceEnhancerModel) -> Tuple[gradio.Dropdown, gradio.Slider]:
 	face_enhancer_module = load_processor_module('face_enhancer')
 	face_enhancer_module.clear_inference_pool()
 	state_manager.set_item('face_enhancer_model', face_enhancer_model)
 
 	if face_enhancer_module.pre_check():
-		return gradio.Dropdown(value = state_manager.get_item('face_enhancer_model'))
-	return gradio.Dropdown()
+		return gradio.Dropdown(value = state_manager.get_item('face_enhancer_model')), gradio.Slider(visible = has_weight_input())
+	return gradio.Dropdown(), gradio.Slider()
 
 
 def update_face_enhancer_blend(face_enhancer_blend : float) -> None:
 	state_manager.set_item('face_enhancer_blend', int(face_enhancer_blend))
+
+
+def update_face_enhancer_weight(face_enhancer_weight : float) -> None:
+	state_manager.set_item('face_enhancer_weight', face_enhancer_weight)
+

facefusion/uis/components/face_swapper_options.py

@@ -17,17 +17,18 @@ def render() -> None:
 	global FACE_SWAPPER_MODEL_DROPDOWN
 	global FACE_SWAPPER_PIXEL_BOOST_DROPDOWN
 
+	has_face_swapper = 'face_swapper' in state_manager.get_item('processors')
 	FACE_SWAPPER_MODEL_DROPDOWN = gradio.Dropdown(
 		label = wording.get('uis.face_swapper_model_dropdown'),
-		choices = processors_choices.face_swapper_set.keys(),
+		choices = list(processors_choices.face_swapper_set.keys()),
 		value = state_manager.get_item('face_swapper_model'),
-		visible = 'face_swapper' in state_manager.get_item('processors')
+		visible = has_face_swapper
 	)
 	FACE_SWAPPER_PIXEL_BOOST_DROPDOWN = gradio.Dropdown(
 		label = wording.get('uis.face_swapper_pixel_boost_dropdown'),
 		choices = processors_choices.face_swapper_set.get(state_manager.get_item('face_swapper_model')),
 		value = state_manager.get_item('face_swapper_pixel_boost'),
-		visible = 'face_swapper' in state_manager.get_item('processors')
+		visible = has_face_swapper
 	)
 	register_ui_component('face_swapper_model_dropdown', FACE_SWAPPER_MODEL_DROPDOWN)
 	register_ui_component('face_swapper_pixel_boost_dropdown', FACE_SWAPPER_PIXEL_BOOST_DROPDOWN)

facefusion/uis/components/frame_colorizer_options.py

@@ -19,17 +19,18 @@ def render() -> None:
 	global FRAME_COLORIZER_SIZE_DROPDOWN
 	global FRAME_COLORIZER_BLEND_SLIDER
 
+	has_frame_colorizer = 'frame_colorizer' in state_manager.get_item('processors')
 	FRAME_COLORIZER_MODEL_DROPDOWN = gradio.Dropdown(
 		label = wording.get('uis.frame_colorizer_model_dropdown'),
 		choices = processors_choices.frame_colorizer_models,
 		value = state_manager.get_item('frame_colorizer_model'),
-		visible = 'frame_colorizer' in state_manager.get_item('processors')
+		visible = has_frame_colorizer
 	)
 	FRAME_COLORIZER_SIZE_DROPDOWN = gradio.Dropdown(
 		label = wording.get('uis.frame_colorizer_size_dropdown'),
 		choices = processors_choices.frame_colorizer_sizes,
 		value = state_manager.get_item('frame_colorizer_size'),
-		visible = 'frame_colorizer' in state_manager.get_item('processors')
+		visible = has_frame_colorizer
 	)
 	FRAME_COLORIZER_BLEND_SLIDER = gradio.Slider(
 		label = wording.get('uis.frame_colorizer_blend_slider'),
@@ -37,7 +38,7 @@ def render() -> None:
 		step = calc_int_step(processors_choices.frame_colorizer_blend_range),
 		minimum = processors_choices.frame_colorizer_blend_range[0],
 		maximum = processors_choices.frame_colorizer_blend_range[-1],
-		visible = 'frame_colorizer' in state_manager.get_item('processors')
+		visible = has_frame_colorizer
 	)
 	register_ui_component('frame_colorizer_model_dropdown', FRAME_COLORIZER_MODEL_DROPDOWN)
 	register_ui_component('frame_colorizer_size_dropdown', FRAME_COLORIZER_SIZE_DROPDOWN)

facefusion/uis/components/frame_enhancer_options.py

@@ -17,11 +17,12 @@ def render() -> None:
 	global FRAME_ENHANCER_MODEL_DROPDOWN
 	global FRAME_ENHANCER_BLEND_SLIDER
 
+	has_frame_enhancer = 'frame_enhancer' in state_manager.get_item('processors')
 	FRAME_ENHANCER_MODEL_DROPDOWN = gradio.Dropdown(
 		label = wording.get('uis.frame_enhancer_model_dropdown'),
 		choices = processors_choices.frame_enhancer_models,
 		value = state_manager.get_item('frame_enhancer_model'),
-		visible = 'frame_enhancer' in state_manager.get_item('processors')
+		visible = has_frame_enhancer
 	)
 	FRAME_ENHANCER_BLEND_SLIDER = gradio.Slider(
 		label = wording.get('uis.frame_enhancer_blend_slider'),
@@ -29,7 +30,7 @@ def render() -> None:
 		step = calc_int_step(processors_choices.frame_enhancer_blend_range),
 		minimum = processors_choices.frame_enhancer_blend_range[0],
 		maximum = processors_choices.frame_enhancer_blend_range[-1],
-		visible = 'frame_enhancer' in state_manager.get_item('processors')
+		visible = has_frame_enhancer
 	)
 	register_ui_component('frame_enhancer_model_dropdown', FRAME_ENHANCER_MODEL_DROPDOWN)
 	register_ui_component('frame_enhancer_blend_slider', FRAME_ENHANCER_BLEND_SLIDER)

facefusion/uis/components/lip_syncer_options.py

@@ -14,11 +14,12 @@ LIP_SYNCER_MODEL_DROPDOWN : Optional[gradio.Dropdown] = None
 def render() -> None:
 	global LIP_SYNCER_MODEL_DROPDOWN
 
+	has_lip_syncer = 'lip_syncer' in state_manager.get_item('processors')
 	LIP_SYNCER_MODEL_DROPDOWN = gradio.Dropdown(
 		label = wording.get('uis.lip_syncer_model_dropdown'),
 		choices = processors_choices.lip_syncer_models,
 		value = state_manager.get_item('lip_syncer_model'),
-		visible = 'lip_syncer' in state_manager.get_item('processors')
+		visible = has_lip_syncer
 	)
 	register_ui_component('lip_syncer_model_dropdown', LIP_SYNCER_MODEL_DROPDOWN)
 

facefusion/uis/components/preview.py

@@ -11,6 +11,7 @@ from facefusion.common_helper import get_first
 from facefusion.content_analyser import analyse_frame
 from facefusion.core import conditional_append_reference_faces
 from facefusion.face_analyser import get_average_face, get_many_faces
+from facefusion.face_selector import sort_faces_by_order
 from facefusion.face_store import clear_reference_faces, clear_static_faces, get_reference_faces
 from facefusion.filesystem import filter_audio_paths, is_image, is_video
 from facefusion.processors.core import get_processors_modules
@@ -74,7 +75,7 @@ def render() -> None:
 
 def listen() -> None:
 	PREVIEW_FRAME_SLIDER.release(update_preview_image, inputs = PREVIEW_FRAME_SLIDER, outputs = PREVIEW_IMAGE, show_progress = 'hidden')
-	PREVIEW_FRAME_SLIDER.change(slide_preview_image, inputs = PREVIEW_FRAME_SLIDER, outputs = PREVIEW_IMAGE, show_progress = 'hidden')
+	PREVIEW_FRAME_SLIDER.change(slide_preview_image, inputs = PREVIEW_FRAME_SLIDER, outputs = PREVIEW_IMAGE, show_progress = 'hidden', trigger_mode = 'once')
 
 	reference_face_position_gallery = get_ui_component('reference_face_position_gallery')
 	if reference_face_position_gallery:
@@ -110,6 +111,7 @@ def listen() -> None:
 	for ui_component in get_ui_components(
 	[
 		'age_modifier_direction_slider',
+		'deep_swapper_morph_slider',
 		'expression_restorer_factor_slider',
 		'face_editor_eyebrow_direction_slider',
 		'face_editor_eye_gaze_horizontal_slider',
@@ -126,6 +128,7 @@ def listen() -> None:
 		'face_editor_head_yaw_slider',
 		'face_editor_head_roll_slider',
 		'face_enhancer_blend_slider',
+		'face_enhancer_weight_slider',
 		'frame_colorizer_blend_slider',
 		'frame_enhancer_blend_slider',
 		'reference_face_distance_slider',
@@ -142,6 +145,7 @@ def listen() -> None:
 	for ui_component in get_ui_components(
 	[
 		'age_modifier_model_dropdown',
+		'deep_swapper_model_dropdown',
 		'expression_restorer_model_dropdown',
 		'processors_checkbox_group',
 		'face_editor_model_dropdown',
@@ -190,7 +194,13 @@ def update_preview_image(frame_number : int = 0) -> gradio.Image:
 	conditional_append_reference_faces()
 	reference_faces = get_reference_faces() if 'reference' in state_manager.get_item('face_selector_mode') else None
 	source_frames = read_static_images(state_manager.get_item('source_paths'))
-	source_faces = get_many_faces(source_frames)
+	source_faces = []
+
+	for source_frame in source_frames:
+		temp_faces = get_many_faces([ source_frame ])
+		temp_faces = sort_faces_by_order(temp_faces, 'large-small')
+		if temp_faces:
+			source_faces.append(get_first(temp_faces))
 	source_face = get_average_face(source_faces)
 	source_audio_path = get_first(filter_audio_paths(state_manager.get_item('source_paths')))
 	source_audio_frame = create_empty_audio_frame()

facefusion/uis/components/processors.py

@@ -4,7 +4,7 @@ import gradio
 
 from facefusion import state_manager, wording
 from facefusion.filesystem import list_directory
-from facefusion.processors.core import clear_processors_modules, get_processors_modules
+from facefusion.processors.core import get_processors_modules
 from facefusion.uis.core import register_ui_component
 
 PROCESSORS_CHECKBOX_GROUP : Optional[gradio.CheckboxGroup] = None
@@ -26,12 +26,15 @@ def listen() -> None:
 
 
 def update_processors(processors : List[str]) -> gradio.CheckboxGroup:
-	clear_processors_modules(state_manager.get_item('processors'))
-	state_manager.set_item('processors', processors)
-
 	for processor_module in get_processors_modules(state_manager.get_item('processors')):
+		if hasattr(processor_module, 'clear_inference_pool'):
+			processor_module.clear_inference_pool()
+
+	for processor_module in get_processors_modules(processors):
 		if not processor_module.pre_check():
 			return gradio.CheckboxGroup()
+
+	state_manager.set_item('processors', processors)
 	return gradio.CheckboxGroup(value = state_manager.get_item('processors'), choices = sort_processors(state_manager.get_item('processors')))
 
 

facefusion/uis/components/terminal.py

@@ -24,7 +24,7 @@ def render() -> None:
 
 	LOG_LEVEL_DROPDOWN = gradio.Dropdown(
 		label = wording.get('uis.log_level_dropdown'),
-		choices = log_level_set.keys(),
+		choices = list(log_level_set.keys()),
 		value = state_manager.get_item('log_level')
 	)
 	TERMINAL_TEXTBOX = gradio.Textbox(

facefusion/uis/components/webcam.py

@@ -43,7 +43,7 @@ def get_webcam_capture() -> Optional[cv2.VideoCapture]:
 def clear_webcam_capture() -> None:
 	global WEBCAM_CAPTURE
 
-	if WEBCAM_CAPTURE:
+	if WEBCAM_CAPTURE and WEBCAM_CAPTURE.isOpened():
 		WEBCAM_CAPTURE.release()
 	WEBCAM_CAPTURE = None
 
@@ -89,11 +89,13 @@ def start(webcam_mode : WebcamMode, webcam_resolution : str, webcam_fps : Fps) -
 		stream = open_stream(webcam_mode, webcam_resolution, webcam_fps) #type:ignore[arg-type]
 	webcam_width, webcam_height = unpack_resolution(webcam_resolution)
 	webcam_capture = get_webcam_capture()
+
 	if webcam_capture and webcam_capture.isOpened():
 		webcam_capture.set(cv2.CAP_PROP_FOURCC, cv2.VideoWriter_fourcc(*'MJPG')) #type:ignore[attr-defined]
 		webcam_capture.set(cv2.CAP_PROP_FRAME_WIDTH, webcam_width)
 		webcam_capture.set(cv2.CAP_PROP_FRAME_HEIGHT, webcam_height)
 		webcam_capture.set(cv2.CAP_PROP_FPS, webcam_fps)
+
 		for capture_frame in multi_process_capture(source_face, webcam_capture, webcam_fps):
 			if webcam_mode == 'inline':
 				yield normalize_frame_color(capture_frame)
@@ -107,19 +109,15 @@ def start(webcam_mode : WebcamMode, webcam_resolution : str, webcam_fps : Fps) -
 
 def multi_process_capture(source_face : Face, webcam_capture : cv2.VideoCapture, webcam_fps : Fps) -> Generator[VisionFrame, None, None]:
 	deque_capture_frames: Deque[VisionFrame] = deque()
-	with tqdm(desc = wording.get('processing'), unit = 'frame', ascii = ' =', disable = state_manager.get_item('log_level') in [ 'warn', 'error' ]) as progress:
-		progress.set_postfix(
-		{
-			'execution_providers': state_manager.get_item('execution_providers'),
-			'execution_thread_count': state_manager.get_item('execution_thread_count')
-		})
+
+	with tqdm(desc = wording.get('streaming'), unit = 'frame', disable = state_manager.get_item('log_level') in [ 'warn', 'error' ]) as progress:
 		with ThreadPoolExecutor(max_workers = state_manager.get_item('execution_thread_count')) as executor:
 			futures = []
 
 			while webcam_capture and webcam_capture.isOpened():
 				_, capture_frame = webcam_capture.read()
 				if analyse_stream(capture_frame, webcam_fps):
-					return
+					yield None
 				future = executor.submit(process_stream_frame, source_face, capture_frame)
 				futures.append(future)
 
@@ -140,6 +138,7 @@ def stop() -> gradio.Image:
 
 def process_stream_frame(source_face : Face, target_vision_frame : VisionFrame) -> VisionFrame:
 	source_audio_frame = create_empty_audio_frame()
+
 	for processor_module in get_processors_modules(state_manager.get_item('processors')):
 		logger.disable()
 		if processor_module.pre_process('stream'):
@@ -155,6 +154,7 @@ def process_stream_frame(source_face : Face, target_vision_frame : VisionFrame)
 
 def open_stream(stream_mode : StreamMode, stream_resolution : str, stream_fps : Fps) -> subprocess.Popen[bytes]:
 	commands = [ '-f', 'rawvideo', '-pix_fmt', 'bgr24', '-s', stream_resolution, '-r', str(stream_fps), '-i', '-']
+
 	if stream_mode == 'udp':
 		commands.extend([ '-b:v', '2000k', '-f', 'mpegts', 'udp://localhost:27000?pkt_size=1316' ])
 	if stream_mode == 'v4l2':

facefusion/uis/core.py

@@ -10,16 +10,8 @@ from gradio.themes import Size
 from facefusion import logger, metadata, state_manager, wording
 from facefusion.exit_helper import hard_exit
 from facefusion.filesystem import resolve_relative_path
-from facefusion.uis import overrides
 from facefusion.uis.typing import Component, ComponentName
 
-os.environ['GRADIO_ANALYTICS_ENABLED'] = '0'
-
-warnings.filterwarnings('ignore', category = UserWarning, module = 'gradio')
-
-gradio.processing_utils.encode_array_to_base64 = overrides.encode_array_to_base64
-gradio.processing_utils.encode_pil_to_base64 = overrides.encode_pil_to_base64
-
 UI_COMPONENTS: Dict[ComponentName, Component] = {}
 UI_LAYOUT_MODULES : List[ModuleType] = []
 UI_LAYOUT_METHODS =\
@@ -77,6 +69,13 @@ def register_ui_component(component_name : ComponentName, component: Component)
 	UI_COMPONENTS[component_name] = component
 
 
+def init() -> None:
+	os.environ['GRADIO_ANALYTICS_ENABLED'] = '0'
+	os.environ['GRADIO_TEMP_DIR'] = os.path.join(state_manager.get_item('temp_path'), 'gradio')
+
+	warnings.filterwarnings('ignore', category = UserWarning, module = 'gradio')
+
+
 def launch() -> None:
 	ui_layouts_total = len(state_manager.get_item('ui_layouts'))
 	with gradio.Blocks(theme = get_theme(), css = get_css(), title = metadata.get('name') + ' ' + metadata.get('version'), fill_width = True) as ui:
@@ -99,7 +98,20 @@ def launch() -> None:
 def get_theme() -> gradio.Theme:
 	return gradio.themes.Base(
 		primary_hue = gradio.themes.colors.red,
-		secondary_hue = gradio.themes.colors.neutral,
+		secondary_hue = gradio.themes.Color(
+			name = 'neutral',
+			c50 = '#fafafa',
+			c100 = '#f5f5f5',
+			c200 = '#e5e5e5',
+			c300 = '#d4d4d4',
+			c400 = '#a3a3a3',
+			c500 = '#737373',
+			c600 = '#525252',
+			c700 = '#404040',
+			c800 = '#262626',
+			c900 = '#212121',
+			c950 = '#171717',
+		),
 		radius_size = Size(
 			xxs = '0.375rem',
 			xs = '0.375rem',
@@ -111,11 +123,18 @@ def get_theme() -> gradio.Theme:
 		),
 		font = gradio.themes.GoogleFont('Open Sans')
 	).set(
+		color_accent = 'transparent',
+		color_accent_soft = 'transparent',
+		color_accent_soft_dark = 'transparent',
 		background_fill_primary = '*neutral_100',
+		background_fill_primary_dark = '*neutral_950',
+		background_fill_secondary = '*neutral_50',
+		background_fill_secondary_dark = '*neutral_800',
 		block_background_fill = 'white',
+		block_background_fill_dark = '*neutral_900',
 		block_border_width = '0',
 		block_label_background_fill = '*neutral_100',
-		block_label_background_fill_dark = '*neutral_700',
+		block_label_background_fill_dark = '*neutral_800',
 		block_label_border_width = 'none',
 		block_label_margin = '0.5rem',
 		block_label_radius = '*radius_md',
@@ -124,39 +143,48 @@ def get_theme() -> gradio.Theme:
 		block_label_text_color_dark = 'white',
 		block_label_text_weight = '600',
 		block_title_background_fill = '*neutral_100',
-		block_title_background_fill_dark = '*neutral_700',
+		block_title_background_fill_dark = '*neutral_800',
 		block_title_padding = '*block_label_padding',
 		block_title_radius = '*block_label_radius',
 		block_title_text_color = '*neutral_700',
 		block_title_text_size = '*text_sm',
 		block_title_text_weight = '600',
 		block_padding = '0.5rem',
+		border_color_accent = 'transparent',
+		border_color_accent_dark = 'transparent',
+		border_color_accent_subdued = 'transparent',
+		border_color_accent_subdued_dark = 'transparent',
 		border_color_primary = 'transparent',
 		border_color_primary_dark = 'transparent',
 		button_large_padding = '2rem 0.5rem',
 		button_large_text_weight = 'normal',
 		button_primary_background_fill = '*primary_500',
+		button_primary_background_fill_dark = '*primary_600',
 		button_primary_text_color = 'white',
 		button_secondary_background_fill = 'white',
-		button_secondary_border_color = 'transparent',
-		button_secondary_border_color_dark = 'transparent',
-		button_secondary_border_color_hover = 'transparent',
-		button_secondary_border_color_hover_dark = 'transparent',
+		button_secondary_background_fill_dark = '*neutral_800',
+		button_secondary_background_fill_hover = 'white',
+		button_secondary_background_fill_hover_dark = '*neutral_800',
 		button_secondary_text_color = '*neutral_800',
 		button_small_padding = '0.75rem',
+		button_small_text_size = '0.875rem',
 		checkbox_background_color = '*neutral_200',
+		checkbox_background_color_dark = '*neutral_900',
 		checkbox_background_color_selected = '*primary_600',
 		checkbox_background_color_selected_dark = '*primary_700',
-		checkbox_border_color_focus = '*primary_500',
-		checkbox_border_color_focus_dark = '*primary_600',
-		checkbox_border_color_selected = '*primary_600',
-		checkbox_border_color_selected_dark = '*primary_700',
 		checkbox_label_background_fill = '*neutral_50',
+		checkbox_label_background_fill_dark = '*neutral_800',
 		checkbox_label_background_fill_hover = '*neutral_50',
+		checkbox_label_background_fill_hover_dark = '*neutral_800',
 		checkbox_label_background_fill_selected = '*primary_500',
 		checkbox_label_background_fill_selected_dark = '*primary_600',
 		checkbox_label_text_color_selected = 'white',
+		error_background_fill = 'white',
+		error_background_fill_dark = '*neutral_900',
+		error_text_color = '*primary_500',
+		error_text_color_dark = '*primary_600',
 		input_background_fill = '*neutral_50',
+		input_background_fill_dark = '*neutral_800',
 		shadow_drop = 'none',
 		slider_color = '*primary_500',
 		slider_color_dark = '*primary_600'

facefusion/uis/layouts/benchmark.py

@@ -1,26 +1,24 @@
 import gradio
 
 from facefusion import state_manager
-from facefusion.download import conditional_download
-from facefusion.uis.components import about, age_modifier_options, benchmark, benchmark_options, execution, execution_queue_count, execution_thread_count, expression_restorer_options, face_debugger_options, face_editor_options, face_enhancer_options, face_swapper_options, frame_colorizer_options, frame_enhancer_options, lip_syncer_options, memory, processors
+from facefusion.download import conditional_download, resolve_download_url
+from facefusion.uis.components import about, age_modifier_options, benchmark, benchmark_options, deep_swapper_options, download, execution, execution_queue_count, execution_thread_count, expression_restorer_options, face_debugger_options, face_editor_options, face_enhancer_options, face_swapper_options, frame_colorizer_options, frame_enhancer_options, lip_syncer_options, memory, processors
 
 
 def pre_check() -> bool:
-	if not state_manager.get_item('skip_download'):
-		conditional_download('.assets/examples',
-		[
-			'https://github.com/facefusion/facefusion-assets/releases/download/examples-3.0.0/source.jpg',
-			'https://github.com/facefusion/facefusion-assets/releases/download/examples-3.0.0/source.mp3',
-			'https://github.com/facefusion/facefusion-assets/releases/download/examples-3.0.0/target-240p.mp4',
-			'https://github.com/facefusion/facefusion-assets/releases/download/examples-3.0.0/target-360p.mp4',
-			'https://github.com/facefusion/facefusion-assets/releases/download/examples-3.0.0/target-540p.mp4',
-			'https://github.com/facefusion/facefusion-assets/releases/download/examples-3.0.0/target-720p.mp4',
-			'https://github.com/facefusion/facefusion-assets/releases/download/examples-3.0.0/target-1080p.mp4',
-			'https://github.com/facefusion/facefusion-assets/releases/download/examples-3.0.0/target-1440p.mp4',
-			'https://github.com/facefusion/facefusion-assets/releases/download/examples-3.0.0/target-2160p.mp4'
-		])
-		return True
-	return False
+	conditional_download('.assets/examples',
+	[
+		resolve_download_url('examples-3.0.0', 'source.jpg'),
+		resolve_download_url('examples-3.0.0', 'source.mp3'),
+		resolve_download_url('examples-3.0.0', 'target-240p.mp4'),
+		resolve_download_url('examples-3.0.0', 'target-360p.mp4'),
+		resolve_download_url('examples-3.0.0', 'target-540p.mp4'),
+		resolve_download_url('examples-3.0.0', 'target-720p.mp4'),
+		resolve_download_url('examples-3.0.0', 'target-1080p.mp4'),
+		resolve_download_url('examples-3.0.0', 'target-1440p.mp4'),
+		resolve_download_url('examples-3.0.0', 'target-2160p.mp4')
+	])
+	return True
 
 
 def render() -> gradio.Blocks:
@@ -33,6 +31,8 @@ def render() -> gradio.Blocks:
 					processors.render()
 				with gradio.Blocks():
 					age_modifier_options.render()
+				with gradio.Blocks():
+					deep_swapper_options.render()
 				with gradio.Blocks():
 					expression_restorer_options.render()
 				with gradio.Blocks():
@@ -54,6 +54,9 @@ def render() -> gradio.Blocks:
 					execution_thread_count.render()
 					execution_queue_count.render()
 				with gradio.Blocks():
+					download.render()
+				with gradio.Blocks():
+					state_manager.set_item('video_memory_strategy', 'tolerant')
 					memory.render()
 				with gradio.Blocks():
 					benchmark_options.render()
@@ -66,7 +69,9 @@ def render() -> gradio.Blocks:
 def listen() -> None:
 	processors.listen()
 	age_modifier_options.listen()
+	deep_swapper_options.listen()
 	expression_restorer_options.listen()
+	download.listen()
 	face_debugger_options.listen()
 	face_editor_options.listen()
 	face_enhancer_options.listen()

facefusion/uis/layouts/default.py

@@ -1,7 +1,7 @@
 import gradio
 
 from facefusion import state_manager
-from facefusion.uis.components import about, age_modifier_options, common_options, execution, execution_queue_count, execution_thread_count, expression_restorer_options, face_debugger_options, face_detector, face_editor_options, face_enhancer_options, face_landmarker, face_masker, face_selector, face_swapper_options, frame_colorizer_options, frame_enhancer_options, instant_runner, job_manager, job_runner, lip_syncer_options, memory, output, output_options, preview, processors, source, target, temp_frame, terminal, trim_frame, ui_workflow
+from facefusion.uis.components import about, age_modifier_options, common_options, deep_swapper_options, download, execution, execution_queue_count, execution_thread_count, expression_restorer_options, face_debugger_options, face_detector, face_editor_options, face_enhancer_options, face_landmarker, face_masker, face_selector, face_swapper_options, frame_colorizer_options, frame_enhancer_options, instant_runner, job_manager, job_runner, lip_syncer_options, memory, output, output_options, preview, processors, source, target, temp_frame, terminal, trim_frame, ui_workflow
 
 
 def pre_check() -> bool:
@@ -18,6 +18,8 @@ def render() -> gradio.Blocks:
 					processors.render()
 				with gradio.Blocks():
 					age_modifier_options.render()
+				with gradio.Blocks():
+					deep_swapper_options.render()
 				with gradio.Blocks():
 					expression_restorer_options.render()
 				with gradio.Blocks():
@@ -38,6 +40,8 @@ def render() -> gradio.Blocks:
 					execution.render()
 					execution_thread_count.render()
 					execution_queue_count.render()
+				with gradio.Blocks():
+					download.render()
 				with gradio.Blocks():
 					memory.render()
 				with gradio.Blocks():
@@ -79,6 +83,7 @@ def render() -> gradio.Blocks:
 def listen() -> None:
 	processors.listen()
 	age_modifier_options.listen()
+	deep_swapper_options.listen()
 	expression_restorer_options.listen()
 	face_debugger_options.listen()
 	face_editor_options.listen()
@@ -90,6 +95,7 @@ def listen() -> None:
 	execution.listen()
 	execution_thread_count.listen()
 	execution_queue_count.listen()
+	download.listen()
 	memory.listen()
 	temp_frame.listen()
 	output_options.listen()

facefusion/uis/layouts/webcam.py

@@ -1,7 +1,7 @@
 import gradio
 
 from facefusion import state_manager
-from facefusion.uis.components import about, age_modifier_options, execution, execution_thread_count, face_debugger_options, face_enhancer_options, face_swapper_options, frame_colorizer_options, frame_enhancer_options, lip_syncer_options, processors, source, webcam, webcam_options
+from facefusion.uis.components import about, age_modifier_options, deep_swapper_options, download, execution, execution_thread_count, expression_restorer_options, face_debugger_options, face_editor_options, face_enhancer_options, face_swapper_options, frame_colorizer_options, frame_enhancer_options, lip_syncer_options, processors, source, webcam, webcam_options
 
 
 def pre_check() -> bool:
@@ -18,8 +18,14 @@ def render() -> gradio.Blocks:
 					processors.render()
 				with gradio.Blocks():
 					age_modifier_options.render()
+				with gradio.Blocks():
+					deep_swapper_options.render()
+				with gradio.Blocks():
+					expression_restorer_options.render()
 				with gradio.Blocks():
 					face_debugger_options.render()
+				with gradio.Blocks():
+					face_editor_options.render()
 				with gradio.Blocks():
 					face_enhancer_options.render()
 				with gradio.Blocks():
@@ -33,6 +39,8 @@ def render() -> gradio.Blocks:
 				with gradio.Blocks():
 					execution.render()
 					execution_thread_count.render()
+				with gradio.Blocks():
+					download.render()
 				with gradio.Blocks():
 					webcam_options.render()
 				with gradio.Blocks():
@@ -46,7 +54,11 @@ def render() -> gradio.Blocks:
 def listen() -> None:
 	processors.listen()
 	age_modifier_options.listen()
+	deep_swapper_options.listen()
+	expression_restorer_options.listen()
+	download.listen()
 	face_debugger_options.listen()
+	face_editor_options.listen()
 	face_enhancer_options.listen()
 	face_swapper_options.listen()
 	frame_colorizer_options.listen()

facefusion/uis/overrides.py

@@ -1,15 +0,0 @@
-import base64
-from typing import Any
-
-import cv2
-import numpy
-from numpy._typing import NDArray
-
-
-def encode_array_to_base64(array : NDArray[Any]) -> str:
-	_, buffer = cv2.imencode('.jpg', array[:, :, ::-1])
-	return 'data:image/jpeg;base64,' + base64.b64encode(buffer.tobytes()).decode('utf-8')
-
-
-def encode_pil_to_base64(image : Any) -> str:
-	return encode_array_to_base64(numpy.asarray(image)[:, :, ::-1])

facefusion/uis/typing.py

@@ -9,6 +9,8 @@ ComponentName = Literal\
 	'age_modifier_model_dropdown',
 	'benchmark_cycles_slider',
 	'benchmark_runs_checkbox_group',
+	'deep_swapper_model_dropdown',
+	'deep_swapper_morph_slider',
 	'expression_restorer_factor_slider',
 	'expression_restorer_model_dropdown',
 	'face_debugger_items_checkbox_group',
@@ -33,6 +35,7 @@ ComponentName = Literal\
 	'face_editor_mouth_smile_slider',
 	'face_enhancer_blend_slider',
 	'face_enhancer_model_dropdown',
+	'face_enhancer_weight_slider',
 	'face_landmarker_model_dropdown',
 	'face_landmarker_score_slider',
 	'face_mask_blur_slider',

facefusion/uis/ui_helper.py

@@ -21,6 +21,6 @@ def convert_str_none(value : str) -> Optional[str]:
 def suggest_output_path(output_directory_path : str, target_path : str) -> Optional[str]:
 	if is_image(target_path) or is_video(target_path):
 		_, target_extension = os.path.splitext(target_path)
-		output_name = hashlib.sha1(str(state_manager.get_state()).encode('utf-8')).hexdigest()[:8]
+		output_name = hashlib.sha1(str(state_manager.get_state()).encode()).hexdigest()[:8]
 		return os.path.join(output_directory_path, output_name + target_extension)
 	return None

facefusion/vision.py

@@ -8,7 +8,7 @@ from cv2.typing import Size
 from facefusion.choices import image_template_sizes, video_template_sizes
 from facefusion.common_helper import is_windows
 from facefusion.filesystem import is_image, is_video, sanitize_path_for_windows
-from facefusion.typing import Fps, Orientation, Resolution, VisionFrame
+from facefusion.typing import Duration, Fps, Orientation, Resolution, VisionFrame
 
 
 @lru_cache(maxsize = 128)
@@ -119,6 +119,14 @@ def restrict_video_fps(video_path : str, fps : Fps) -> Fps:
 	return fps
 
 
+def detect_video_duration(video_path : str) -> Duration:
+	video_frame_total = count_video_frame_total(video_path)
+	video_fps = detect_video_fps(video_path)
+	if video_frame_total and video_fps:
+		return video_frame_total / video_fps
+	return 0
+
+
 def detect_video_resolution(video_path : str) -> Optional[Resolution]:
 	if is_video(video_path):
 		if is_windows():
@@ -202,6 +210,42 @@ def normalize_frame_color(vision_frame : VisionFrame) -> VisionFrame:
 	return cv2.cvtColor(vision_frame, cv2.COLOR_BGR2RGB)
 
 
+def conditional_match_frame_color(source_vision_frame : VisionFrame, target_vision_frame : VisionFrame) -> VisionFrame:
+	histogram_factor = calc_histogram_difference(source_vision_frame, target_vision_frame)
+	target_vision_frame = blend_vision_frames(target_vision_frame, match_frame_color(source_vision_frame, target_vision_frame), histogram_factor)
+	return target_vision_frame
+
+
+def match_frame_color(source_vision_frame : VisionFrame, target_vision_frame : VisionFrame) -> VisionFrame:
+	color_difference_sizes = numpy.linspace(16, target_vision_frame.shape[0], 3, endpoint = False)
+
+	for color_difference_size in color_difference_sizes:
+		source_vision_frame = equalize_frame_color(source_vision_frame, target_vision_frame, normalize_resolution((color_difference_size, color_difference_size)))
+	target_vision_frame = equalize_frame_color(source_vision_frame, target_vision_frame, target_vision_frame.shape[:2][::-1])
+	return target_vision_frame
+
+
+def equalize_frame_color(source_vision_frame : VisionFrame, target_vision_frame : VisionFrame, size : Size) -> VisionFrame:
+	source_frame_resize = cv2.resize(source_vision_frame, size, interpolation = cv2.INTER_AREA).astype(numpy.float32)
+	target_frame_resize = cv2.resize(target_vision_frame, size, interpolation = cv2.INTER_AREA).astype(numpy.float32)
+	color_difference_vision_frame = numpy.subtract(source_frame_resize, target_frame_resize)
+	color_difference_vision_frame = cv2.resize(color_difference_vision_frame, target_vision_frame.shape[:2][::-1], interpolation = cv2.INTER_CUBIC)
+	target_vision_frame = numpy.add(target_vision_frame, color_difference_vision_frame).clip(0, 255).astype(numpy.uint8)
+	return target_vision_frame
+
+
+def calc_histogram_difference(source_vision_frame : VisionFrame, target_vision_frame : VisionFrame) -> float:
+	histogram_source = cv2.calcHist([cv2.cvtColor(source_vision_frame, cv2.COLOR_BGR2HSV)], [ 0, 1 ], None, [ 50, 60 ], [ 0, 180, 0, 256 ])
+	histogram_target = cv2.calcHist([cv2.cvtColor(target_vision_frame, cv2.COLOR_BGR2HSV)], [ 0, 1 ], None, [ 50, 60 ], [ 0, 180, 0, 256 ])
+	histogram_differnce = float(numpy.interp(cv2.compareHist(histogram_source, histogram_target, cv2.HISTCMP_CORREL), [ -1, 1 ], [ 0, 1 ]))
+	return histogram_differnce
+
+
+def blend_vision_frames(source_vision_frame : VisionFrame, target_vision_frame : VisionFrame, blend_factor : float) -> VisionFrame:
+	blend_vision_frame = cv2.addWeighted(source_vision_frame, 1 - blend_factor, target_vision_frame, blend_factor, 0)
+	return blend_vision_frame
+
+
 def create_tile_frames(vision_frame : VisionFrame, size : Size) -> Tuple[List[VisionFrame], int, int]:
 	vision_frame = numpy.pad(vision_frame, ((size[1], size[1]), (size[1], size[1]), (0, 0)))
 	tile_width = size[0] - 2 * size[2]

facefusion/voice_extractor.py

@@ -1,36 +1,40 @@
+from functools import lru_cache
 from typing import Tuple
 
 import numpy
 import scipy
 
 from facefusion import inference_manager
-from facefusion.download import conditional_download_hashes, conditional_download_sources
+from facefusion.download import conditional_download_hashes, conditional_download_sources, resolve_download_url
 from facefusion.filesystem import resolve_relative_path
 from facefusion.thread_helper import thread_semaphore
-from facefusion.typing import Audio, AudioChunk, InferencePool, ModelOptions, ModelSet
+from facefusion.typing import Audio, AudioChunk, DownloadScope, InferencePool, ModelOptions, ModelSet
 
-MODEL_SET : ModelSet =\
-{
-	'kim_vocal_2':
+
+@lru_cache(maxsize = None)
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
+	return\
 	{
-		'hashes':
+		'kim_vocal_2':
 		{
-			'voice_extractor':
+			'hashes':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/kim_vocal_2.hash',
-				'path': resolve_relative_path('../.assets/models/kim_vocal_2.hash')
-			}
-		},
-		'sources':
-		{
-			'voice_extractor':
+				'voice_extractor':
+				{
+					'url': resolve_download_url('models-3.0.0', 'kim_vocal_2.hash'),
+					'path': resolve_relative_path('../.assets/models/kim_vocal_2.hash')
+				}
+			},
+			'sources':
 			{
-				'url': 'https://github.com/facefusion/facefusion-assets/releases/download/models-3.0.0/kim_vocal_2.onnx',
-				'path': resolve_relative_path('../.assets/models/kim_vocal_2.onnx')
+				'voice_extractor':
+				{
+					'url': resolve_download_url('models-3.0.0', 'kim_vocal_2.onnx'),
+					'path': resolve_relative_path('../.assets/models/kim_vocal_2.onnx')
+				}
 			}
 		}
 	}
-}
 
 
 def get_inference_pool() -> InferencePool:
@@ -43,15 +47,14 @@ def clear_inference_pool() -> None:
 
 
 def get_model_options() -> ModelOptions:
-	return MODEL_SET.get('kim_vocal_2')
+	return create_static_model_set('full').get('kim_vocal_2')
 
 
 def pre_check() -> bool:
-	download_directory_path = resolve_relative_path('../.assets/models')
 	model_hashes = get_model_options().get('hashes')
 	model_sources = get_model_options().get('sources')
 
-	return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources)
+	return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
 
 
 def batch_extract_voice(audio : Audio, chunk_size : int, step_size : int) -> Audio:

facefusion/wording.py

@@ -11,7 +11,10 @@ WORDING : Dict[str, Any] =\
 	'extracting_frames_succeed': 'Extracting frames succeed',
 	'extracting_frames_failed': 'Extracting frames failed',
 	'analysing': 'Analysing',
+	'extracting': 'Extracting',
+	'streaming': 'Streaming',
 	'processing': 'Processing',
+	'merging': 'Merging',
 	'downloading': 'Downloading',
 	'temp_frames_not_found': 'Temporary frames not found',
 	'copying_image': 'Copying image with a resolution of {resolution}',
@@ -46,6 +49,7 @@ WORDING : Dict[str, Any] =\
 	'ui_layout_not_loaded': 'UI layout {ui_layout} could not be loaded',
 	'ui_layout_not_implemented': 'UI layout {ui_layout} not implemented correctly',
 	'stream_not_loaded': 'Stream {stream_mode} could not be loaded',
+	'stream_not_supported': 'Stream not supported',
 	'job_created': 'Job {job_id} created',
 	'job_not_created': 'Job {job_id} not created',
 	'job_submitted': 'Job {job_id} submitted',
@@ -94,10 +98,15 @@ WORDING : Dict[str, Any] =\
 		'skip_conda': 'skip the conda environment check',
 		# paths
 		'config_path': 'choose the config file to override defaults',
+		'temp_path': 'specify the directory for the temporary resources',
 		'jobs_path': 'specify the directory to store jobs',
-		'source_paths': 'choose single or multiple source images or audios',
-		'target_path': 'choose single target image or video',
-		'output_path': 'specify the output image or video within a directory',
+		'source_paths': 'choose the image or audio paths',
+		'target_path': 'choose the image or video path',
+		'output_path': 'specify the image or video within a directory',
+		# patterns
+		'source_pattern': 'choose the image or audio pattern',
+		'target_pattern': 'choose the image or video pattern',
+		'output_pattern': 'specify the image or video pattern',
 		# face detector
 		'face_detector_model': 'choose the model responsible for detecting the faces',
 		'face_detector_size': 'specify the frame size provided to the face detector',
@@ -118,7 +127,7 @@ WORDING : Dict[str, Any] =\
 		'reference_frame_number': 'specify the frame used to create the reference face',
 		# face masker
 		'face_mask_types': 'mix and match different face mask types (choices: {choices})',
-		'face_mask_blur': 'specify the degree of blur applied the box mask',
+		'face_mask_blur': 'specify the degree of blur applied to the box mask',
 		'face_mask_padding': 'apply top, right, bottom and left padding to the box mask',
 		'face_mask_regions': 'choose the facial features used for the region mask (choices: {choices})',
 		# frame extraction
@@ -140,6 +149,8 @@ WORDING : Dict[str, Any] =\
 		'processors': 'load a single or multiple processors (choices: {choices}, ...)',
 		'age_modifier_model': 'choose the model responsible for aging the face',
 		'age_modifier_direction': 'specify the direction in which the age should be modified',
+		'deep_swapper_model': 'choose the model responsible for swapping the face',
+		'deep_swapper_morph': 'morph between source face and target faces',
 		'expression_restorer_model': 'choose the model responsible for restoring the expression',
 		'expression_restorer_factor': 'restore factor of expression from the target face',
 		'face_debugger_items': 'load a single or multiple processors (choices: {choices})',
@@ -160,6 +171,7 @@ WORDING : Dict[str, Any] =\
 		'face_editor_head_roll': 'specify the head roll',
 		'face_enhancer_model': 'choose the model responsible for enhancing the face',
 		'face_enhancer_blend': 'blend the enhanced into the previous face',
+		'face_enhancer_weight': 'specify the degree of weight applied to the face',
 		'face_swapper_model': 'choose the model responsible for swapping the face',
 		'face_swapper_pixel_boost': 'choose the pixel boost resolution for the face swapper',
 		'frame_colorizer_model': 'choose the model responsible for colorizing the frame',
@@ -174,18 +186,21 @@ WORDING : Dict[str, Any] =\
 		'ui_workflow': 'choose the ui workflow',
 		# execution
 		'execution_device_id': 'specify the device used for processing',
-		'execution_providers': 'accelerate the model inference using different providers (choices: {choices}, ...)',
+		'execution_providers': 'inference using different providers (choices: {choices}, ...)',
 		'execution_thread_count': 'specify the amount of parallel threads while processing',
 		'execution_queue_count': 'specify the amount of frames each thread is processing',
+		# download
+		'download_providers': 'download using different providers (choices: {choices}, ...)',
+		'download_scope': 'specify the download scope',
 		# memory
 		'video_memory_strategy': 'balance fast processing and low VRAM usage',
 		'system_memory_limit': 'limit the available RAM that can be used while processing',
 		# misc
-		'skip_download': 'omit downloads and remote lookups',
 		'log_level': 'adjust the message severity displayed in the terminal',
 		# run
 		'run': 'run the program',
 		'headless_run': 'run the program in headless mode',
+		'batch_run': 'run the program in batch mode',
 		'force_download': 'force automate downloads and exit',
 		# jobs
 		'job_id': 'specify the job id',
@@ -223,6 +238,9 @@ WORDING : Dict[str, Any] =\
 		'benchmark_runs_checkbox_group': 'BENCHMARK RUNS',
 		'clear_button': 'CLEAR',
 		'common_options_checkbox_group': 'OPTIONS',
+		'download_providers_checkbox_group': 'DOWNLOAD PROVIDERS',
+		'deep_swapper_model_dropdown': 'DEEP SWAPPER MODEL',
+		'deep_swapper_morph_slider': 'DEEP SWAPPER MORPH',
 		'execution_providers_checkbox_group': 'EXECUTION PROVIDERS',
 		'execution_queue_count_slider': 'EXECUTION QUEUE COUNT',
 		'execution_thread_count_slider': 'EXECUTION THREAD COUNT',
@@ -250,6 +268,7 @@ WORDING : Dict[str, Any] =\
 		'face_editor_mouth_smile_slider': 'FACE EDITOR MOUTH SMILE',
 		'face_enhancer_blend_slider': 'FACE ENHANCER BLEND',
 		'face_enhancer_model_dropdown': 'FACE ENHANCER MODEL',
+		'face_enhancer_weight_slider': 'FACE ENHANCER WEIGHT',
 		'face_landmarker_model_dropdown': 'FACE LANDMARKER MODEL',
 		'face_landmarker_score_slider': 'FACE LANDMARKER SCORE',
 		'face_mask_blur_slider': 'FACE MASK BLUR',

requirements.txt

@@ -1,10 +1,9 @@
 filetype==1.2.0
-gradio==4.44.0
-gradio-rangeslider==0.0.6
-numpy==2.1.0
-onnx==1.16.1
-onnxruntime==1.19.2
+litestar==2.13.0
+numpy==2.1.3
+onnx==1.17.0
+onnxruntime==1.20.1
 opencv-python==4.10.0.84
-psutil==6.0.0
-tqdm==4.66.5
+psutil==6.1.0
+tqdm==4.67.1
 scipy==1.14.1

tests/helper.py

@@ -1,7 +1,7 @@
 import os
+import tempfile
 
 from facefusion.filesystem import create_directory, is_directory, is_file, remove_directory
-from facefusion.temp_helper import get_base_directory_path
 from facefusion.typing import JobStatus
 
 
@@ -14,7 +14,7 @@ def get_test_job_file(file_path : str, job_status : JobStatus) -> str:
 
 
 def get_test_jobs_directory() -> str:
-	return os.path.join(get_base_directory_path(), 'test-jobs')
+	return os.path.join(tempfile.gettempdir(), 'facefusion-test-jobs')
 
 
 def get_test_example_file(file_path : str) -> str:
@@ -22,7 +22,7 @@ def get_test_example_file(file_path : str) -> str:
 
 
 def get_test_examples_directory() -> str:
-	return os.path.join(get_base_directory_path(), 'test-examples')
+	return os.path.join(tempfile.gettempdir(), 'facefusion-test-examples')
 
 
 def is_test_output_file(file_path : str) -> bool:
@@ -34,7 +34,7 @@ def get_test_output_file(file_path : str) -> str:
 
 
 def get_test_outputs_directory() -> str:
-	return os.path.join(get_base_directory_path(), 'test-outputs')
+	return os.path.join(tempfile.gettempdir(), 'facefusion-test-outputs')
 
 
 def prepare_test_output_directory() -> bool:

tests/test_cli_age_modifier.py

@@ -25,14 +25,14 @@ def before_each() -> None:
 
 
 def test_modify_age_to_image() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'headless-run', '-j', get_test_jobs_directory(), '--processors', 'age_modifier', '--age-modifier-direction', '100', '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-age-face-to-image.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'headless-run', '--jobs-path', get_test_jobs_directory(), '--processors', 'age_modifier', '--age-modifier-direction', '100', '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-age-face-to-image.jpg') ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert is_test_output_file('test-age-face-to-image.jpg') is True
 
 
 def test_modify_age_to_video() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'headless-run', '-j', get_test_jobs_directory(), '--processors', 'age_modifier', '--age-modifier-direction', '100', '-t', get_test_example_file('target-240p.mp4'), '-o', get_test_output_file('test-age-face-to-video.mp4'), '--trim-frame-end', '1' ]
+	commands = [ sys.executable, 'facefusion.py', 'headless-run', '--jobs-path', get_test_jobs_directory(), '--processors', 'age_modifier', '--age-modifier-direction', '100', '-t', get_test_example_file('target-240p.mp4'), '-o', get_test_output_file('test-age-face-to-video.mp4'), '--trim-frame-end', '1' ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert is_test_output_file('test-age-face-to-video.mp4') is True

tests/test_cli_batch_runner.py

@@ -0,0 +1,45 @@
+import subprocess
+import sys
+
+import pytest
+
+from facefusion.download import conditional_download
+from facefusion.jobs.job_manager import clear_jobs, init_jobs
+from .helper import get_test_example_file, get_test_examples_directory, get_test_jobs_directory, get_test_output_file, is_test_output_file, prepare_test_output_directory
+
+
+@pytest.fixture(scope = 'module', autouse = True)
+def before_all() -> None:
+	conditional_download(get_test_examples_directory(),
+	[
+		'https://github.com/facefusion/facefusion-assets/releases/download/examples-3.0.0/target-240p.mp4'
+	])
+	subprocess.run([ 'ffmpeg', '-i', get_test_example_file('target-240p.mp4'), '-vframes', '1', get_test_example_file('target-240p-batch-1.jpg') ])
+	subprocess.run([ 'ffmpeg', '-i', get_test_example_file('target-240p.mp4'), '-vframes', '2', get_test_example_file('target-240p-batch-2.jpg') ])
+
+
+@pytest.fixture(scope = 'function', autouse = True)
+def before_each() -> None:
+	clear_jobs(get_test_jobs_directory())
+	init_jobs(get_test_jobs_directory())
+	prepare_test_output_directory()
+
+
+def test_batch_run_targets() -> None:
+	commands = [ sys.executable, 'facefusion.py', 'batch-run', '--jobs-path', get_test_jobs_directory(), '--processors', 'face_debugger', '-t', get_test_example_file('target-240p-batch-*.jpg'), '-o', get_test_output_file('test-batch-run-targets-{index}.jpg') ]
+
+	assert subprocess.run(commands).returncode == 0
+	assert is_test_output_file('test-batch-run-targets-0.jpg') is True
+	assert is_test_output_file('test-batch-run-targets-1.jpg') is True
+	assert is_test_output_file('test-batch-run-targets-2.jpg') is False
+
+
+def test_batch_run_sources_to_targets() -> None:
+	commands = [ sys.executable, 'facefusion.py', 'batch-run', '--jobs-path', get_test_jobs_directory(), '-s', get_test_example_file('target-240p-batch-*.jpg'), '-t', get_test_example_file('target-240p-batch-*.jpg'), '-o', get_test_output_file('test-batch-run-sources-to-targets-{index}.jpg') ]
+
+	assert subprocess.run(commands).returncode == 0
+	assert is_test_output_file('test-batch-run-sources-to-targets-0.jpg') is True
+	assert is_test_output_file('test-batch-run-sources-to-targets-1.jpg') is True
+	assert is_test_output_file('test-batch-run-sources-to-targets-2.jpg') is True
+	assert is_test_output_file('test-batch-run-sources-to-targets-3.jpg') is True
+	assert is_test_output_file('test-batch-run-sources-to-targets-4.jpg') is False

tests/test_cli_expression_restorer.py

@@ -25,14 +25,14 @@ def before_each() -> None:
 
 
 def test_restore_expression_to_image() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'headless-run', '-j', get_test_jobs_directory(), '--processors', 'expression_restorer', '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-restore-expression-to-image.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'headless-run', '--jobs-path', get_test_jobs_directory(), '--processors', 'expression_restorer', '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-restore-expression-to-image.jpg') ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert is_test_output_file('test-restore-expression-to-image.jpg') is True
 
 
 def test_restore_expression_to_video() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'headless-run', '-j', get_test_jobs_directory(), '--processors', 'expression_restorer', '-t', get_test_example_file('target-240p.mp4'), '-o', get_test_output_file('test-restore-expression-to-video.mp4'), '--trim-frame-end', '1' ]
+	commands = [ sys.executable, 'facefusion.py', 'headless-run', '--jobs-path', get_test_jobs_directory(), '--processors', 'expression_restorer', '-t', get_test_example_file('target-240p.mp4'), '-o', get_test_output_file('test-restore-expression-to-video.mp4'), '--trim-frame-end', '1' ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert is_test_output_file('test-restore-expression-to-video.mp4') is True

tests/test_cli_face_debugger.py

@@ -26,14 +26,14 @@ def before_each() -> None:
 
 
 def test_debug_face_to_image() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'headless-run', '-j', get_test_jobs_directory(), '--processors', 'face_debugger', '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-debug-face-to-image.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'headless-run', '--jobs-path', get_test_jobs_directory(), '--processors', 'face_debugger', '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-debug-face-to-image.jpg') ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert is_test_output_file('test-debug-face-to-image.jpg') is True
 
 
 def test_debug_face_to_video() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'headless-run', '-j', get_test_jobs_directory(), '--processors', 'face_debugger', '-t', get_test_example_file('target-240p.mp4'), '-o', get_test_output_file('test-debug-face-to-video.mp4'), '--trim-frame-end', '1' ]
+	commands = [ sys.executable, 'facefusion.py', 'headless-run', '--jobs-path', get_test_jobs_directory(), '--processors', 'face_debugger', '-t', get_test_example_file('target-240p.mp4'), '-o', get_test_output_file('test-debug-face-to-video.mp4'), '--trim-frame-end', '1' ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert is_test_output_file('test-debug-face-to-video.mp4') is True

tests/test_cli_face_editor.py

@@ -26,14 +26,14 @@ def before_each() -> None:
 
 
 def test_edit_face_to_image() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'headless-run', '-j', get_test_jobs_directory(), '--processors', 'face_editor', '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-edit-face-to-image.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'headless-run', '--jobs-path', get_test_jobs_directory(), '--processors', 'face_editor', '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-edit-face-to-image.jpg') ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert is_test_output_file('test-edit-face-to-image.jpg') is True
 
 
 def test_edit_face_to_video() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'headless-run', '-j', get_test_jobs_directory(), '--processors', 'face_editor', '-t', get_test_example_file('target-240p.mp4'), '-o', get_test_output_file('test-edit-face-to-video.mp4'), '--trim-frame-end', '1' ]
+	commands = [ sys.executable, 'facefusion.py', 'headless-run', '--jobs-path', get_test_jobs_directory(), '--processors', 'face_editor', '-t', get_test_example_file('target-240p.mp4'), '-o', get_test_output_file('test-edit-face-to-video.mp4'), '--trim-frame-end', '1' ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert is_test_output_file('test-edit-face-to-video.mp4') is True

tests/test_cli_face_enhancer.py

@@ -26,14 +26,14 @@ def before_each() -> None:
 
 
 def test_enhance_face_to_image() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'headless-run', '-j', get_test_jobs_directory(), '--processors', 'face_enhancer', '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-enhance-face-to-image.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'headless-run', '--jobs-path', get_test_jobs_directory(), '--processors', 'face_enhancer', '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-enhance-face-to-image.jpg') ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert is_test_output_file('test-enhance-face-to-image.jpg') is True
 
 
 def test_enhance_face_to_video() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'headless-run', '-j', get_test_jobs_directory(), '--processors', 'face_enhancer', '-t', get_test_example_file('target-240p.mp4'), '-o', get_test_output_file('test-enhance-face-to-video.mp4'), '--trim-frame-end', '1' ]
+	commands = [ sys.executable, 'facefusion.py', 'headless-run', '--jobs-path', get_test_jobs_directory(), '--processors', 'face_enhancer', '-t', get_test_example_file('target-240p.mp4'), '-o', get_test_output_file('test-enhance-face-to-video.mp4'), '--trim-frame-end', '1' ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert is_test_output_file('test-enhance-face-to-video.mp4') is True

tests/test_cli_face_swapper.py

@@ -26,14 +26,14 @@ def before_each() -> None:
 
 
 def test_swap_face_to_image() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'headless-run', '-j', get_test_jobs_directory(), '--processors', 'face_swapper', '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-swap-face-to-image.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'headless-run', '--jobs-path', get_test_jobs_directory(), '--processors', 'face_swapper', '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-swap-face-to-image.jpg') ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert is_test_output_file('test-swap-face-to-image.jpg') is True
 
 
 def test_swap_face_to_video() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'headless-run', '-j', get_test_jobs_directory(), '--processors', 'face_swapper', '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.mp4'), '-o', get_test_output_file('test-swap-face-to-video.mp4'), '--trim-frame-end', '1' ]
+	commands = [ sys.executable, 'facefusion.py', 'headless-run', '--jobs-path', get_test_jobs_directory(), '--processors', 'face_swapper', '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.mp4'), '-o', get_test_output_file('test-swap-face-to-video.mp4'), '--trim-frame-end', '1' ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert is_test_output_file('test-swap-face-to-video.mp4') is True

tests/test_cli_frame_colorizer.py

@@ -27,14 +27,14 @@ def before_each() -> None:
 
 
 def test_colorize_frame_to_image() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'headless-run', '-j', get_test_jobs_directory(), '--processors', 'frame_colorizer', '-t', get_test_example_file('target-240p-0sat.jpg'), '-o', get_test_output_file('test_colorize-frame-to-image.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'headless-run', '--jobs-path', get_test_jobs_directory(), '--processors', 'frame_colorizer', '-t', get_test_example_file('target-240p-0sat.jpg'), '-o', get_test_output_file('test_colorize-frame-to-image.jpg') ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert is_test_output_file('test_colorize-frame-to-image.jpg') is True
 
 
 def test_colorize_frame_to_video() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'headless-run', '-j', get_test_jobs_directory(), '--processors', 'frame_colorizer', '-t', get_test_example_file('target-240p-0sat.mp4'), '-o', get_test_output_file('test-colorize-frame-to-video.mp4'), '--trim-frame-end', '1' ]
+	commands = [ sys.executable, 'facefusion.py', 'headless-run', '--jobs-path', get_test_jobs_directory(), '--processors', 'frame_colorizer', '-t', get_test_example_file('target-240p-0sat.mp4'), '-o', get_test_output_file('test-colorize-frame-to-video.mp4'), '--trim-frame-end', '1' ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert is_test_output_file('test-colorize-frame-to-video.mp4') is True

tests/test_cli_frame_enhancer.py

@@ -26,14 +26,14 @@ def before_each() -> None:
 
 
 def test_enhance_frame_to_image() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'headless-run', '-j', get_test_jobs_directory(), '--processors', 'frame_enhancer', '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-enhance-frame-to-image.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'headless-run', '--jobs-path', get_test_jobs_directory(), '--processors', 'frame_enhancer', '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-enhance-frame-to-image.jpg') ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert is_test_output_file('test-enhance-frame-to-image.jpg') is True
 
 
 def test_enhance_frame_to_video() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'headless-run', '-j', get_test_jobs_directory(), '--processors', 'frame_enhancer', '-t', get_test_example_file('target-240p.mp4'), '-o', get_test_output_file('test-enhance-frame-to-video.mp4'), '--trim-frame-end', '1' ]
+	commands = [ sys.executable, 'facefusion.py', 'headless-run', '--jobs-path', get_test_jobs_directory(), '--processors', 'frame_enhancer', '-t', get_test_example_file('target-240p.mp4'), '-o', get_test_output_file('test-enhance-frame-to-video.mp4'), '--trim-frame-end', '1' ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert is_test_output_file('test-enhance-frame-to-video.mp4') is True

tests/test_cli_job_manager.py

@@ -30,30 +30,30 @@ def test_job_list() -> None:
 
 
 def test_job_create() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-create', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-create', '--jobs-path', get_test_jobs_directory() ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert is_test_job_file('test-job-create.json', 'drafted') is True
 
-	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-create', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-create', '--jobs-path', get_test_jobs_directory() ]
 
 	assert subprocess.run(commands).returncode == 1
 
 
 def test_job_submit() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'job-submit', 'test-job-submit', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-submit', 'test-job-submit', '--jobs-path', get_test_jobs_directory() ]
 
 	assert subprocess.run(commands).returncode == 1
 
-	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-submit', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-submit', '--jobs-path', get_test_jobs_directory() ]
 	subprocess.run(commands)
 
 	assert subprocess.run(commands).returncode == 1
 
-	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-submit', '-j', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-submit', '--jobs-path', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-submit', 'test-job-submit', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-submit', 'test-job-submit', '--jobs-path', get_test_jobs_directory() ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert is_test_job_file('test-job-submit.json', 'queued') is True
@@ -61,25 +61,25 @@ def test_job_submit() -> None:
 
 
 def test_submit_all() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'job-submit-all', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-submit-all', '--jobs-path', get_test_jobs_directory() ]
 
 	assert subprocess.run(commands).returncode == 1
 
-	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-submit-all-1', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-submit-all-1', '--jobs-path', get_test_jobs_directory() ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-submit-all-2', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-submit-all-2', '--jobs-path', get_test_jobs_directory() ]
 	subprocess.run(commands)
 
 	assert subprocess.run(commands).returncode == 1
 
-	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-submit-all-1', '-j', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-submit-all-1', '--jobs-path', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-submit-all-2', '-j', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-submit-all-2', '--jobs-path', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-submit-all', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-submit-all', '--jobs-path', get_test_jobs_directory() ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert is_test_job_file('test-job-submit-all-1.json', 'queued') is True
@@ -88,14 +88,14 @@ def test_submit_all() -> None:
 
 
 def test_job_delete() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'job-delete', 'test-job-delete', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-delete', 'test-job-delete', '--jobs-path', get_test_jobs_directory() ]
 
 	assert subprocess.run(commands).returncode == 1
 
-	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-delete', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-delete', '--jobs-path', get_test_jobs_directory() ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-delete', 'test-job-delete', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-delete', 'test-job-delete', '--jobs-path', get_test_jobs_directory() ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert is_test_job_file('test-job-delete.json', 'drafted') is False
@@ -103,17 +103,17 @@ def test_job_delete() -> None:
 
 
 def test_job_delete_all() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'job-delete-all', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-delete-all', '--jobs-path', get_test_jobs_directory() ]
 
 	assert subprocess.run(commands).returncode == 1
 
-	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-delete-all-1', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-delete-all-1', '--jobs-path', get_test_jobs_directory() ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-delete-all-2', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-delete-all-2', '--jobs-path', get_test_jobs_directory() ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-delete-all', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-delete-all', '--jobs-path', get_test_jobs_directory() ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert is_test_job_file('test-job-delete-all-1.json', 'drafted') is False
@@ -122,87 +122,87 @@ def test_job_delete_all() -> None:
 
 
 def test_job_add_step() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-add-step', '-j', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-add-step', '--jobs-path', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
 
 	assert subprocess.run(commands).returncode == 1
 	assert count_step_total('test-job-add-step') == 0
 
-	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-add-step', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-add-step', '--jobs-path', get_test_jobs_directory() ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-add-step', '-j', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-add-step', '--jobs-path', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert count_step_total('test-job-add-step') == 1
 
 
 def test_job_remix() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'job-remix-step', 'test-job-remix-step', '0', '-j', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'job-remix-step', 'test-job-remix-step', '0', '--jobs-path', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
 
 	assert subprocess.run(commands).returncode == 1
 	assert count_step_total('test-job-remix-step') == 0
 
-	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-remix-step', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-remix-step', '--jobs-path', get_test_jobs_directory() ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-remix-step', '-j', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-remix-step', '--jobs-path', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-remix-step', 'test-job-remix-step', '0', '-j', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'job-remix-step', 'test-job-remix-step', '0', '--jobs-path', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
 
 	assert count_step_total('test-job-remix-step') == 1
 	assert subprocess.run(commands).returncode == 0
 	assert count_step_total('test-job-remix-step') == 2
 
-	commands = [ sys.executable, 'facefusion.py', 'job-remix-step', 'test-job-remix-step', '-1', '-j', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'job-remix-step', 'test-job-remix-step', '-1', '--jobs-path', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert count_step_total('test-job-remix-step') == 3
 
 
 def test_job_insert_step() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'job-insert-step', 'test-job-insert-step', '0', '-j', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'job-insert-step', 'test-job-insert-step', '0', '--jobs-path', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
 
 	assert subprocess.run(commands).returncode == 1
 	assert count_step_total('test-job-insert-step') == 0
 
-	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-insert-step', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-insert-step', '--jobs-path', get_test_jobs_directory() ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-insert-step', '-j', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-insert-step', '--jobs-path', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-insert-step', 'test-job-insert-step', '0', '-j', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'job-insert-step', 'test-job-insert-step', '0', '--jobs-path', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
 
 	assert count_step_total('test-job-insert-step') == 1
 	assert subprocess.run(commands).returncode == 0
 	assert count_step_total('test-job-insert-step') == 2
 
-	commands = [ sys.executable, 'facefusion.py', 'job-insert-step', 'test-job-insert-step', '-1', '-j', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'job-insert-step', 'test-job-insert-step', '-1', '--jobs-path', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert count_step_total('test-job-insert-step') == 3
 
 
 def test_job_remove_step() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'job-remove-step', 'test-job-remove-step', '0', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-remove-step', 'test-job-remove-step', '0', '--jobs-path', get_test_jobs_directory() ]
 
 	assert subprocess.run(commands).returncode == 1
 
-	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-remove-step', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-remove-step', '--jobs-path', get_test_jobs_directory() ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-remove-step', '-j', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-remove-step', '--jobs-path', get_test_jobs_directory(), '-s', get_test_example_file('source.jpg'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-remix-step.jpg') ]
 	subprocess.run(commands)
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-remove-step', 'test-job-remove-step', '0', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-remove-step', 'test-job-remove-step', '0', '--jobs-path', get_test_jobs_directory() ]
 
 	assert count_step_total('test-job-remove-step') == 2
 	assert subprocess.run(commands).returncode == 0
 	assert count_step_total('test-job-remove-step') == 1
 
-	commands = [ sys.executable, 'facefusion.py', 'job-remove-step', 'test-job-remove-step', '-1', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-remove-step', 'test-job-remove-step', '-1', '--jobs-path', get_test_jobs_directory() ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert subprocess.run(commands).returncode == 1

tests/test_cli_job_runner.py

@@ -26,24 +26,24 @@ def before_each() -> None:
 
 
 def test_job_run() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'job-run', 'test-job-run', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-run', 'test-job-run', '--jobs-path', get_test_jobs_directory() ]
 
 	assert subprocess.run(commands).returncode == 1
 
-	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-run', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-run', '--jobs-path', get_test_jobs_directory() ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-run', '-j', get_test_jobs_directory(), '--processors', 'face_debugger', '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-run.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-run', '--jobs-path', get_test_jobs_directory(), '--processors', 'face_debugger', '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-run.jpg') ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-run', 'test-job-run', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-run', 'test-job-run', '--jobs-path', get_test_jobs_directory() ]
 
 	assert subprocess.run(commands).returncode == 1
 
-	commands = [ sys.executable, 'facefusion.py', 'job-submit', 'test-job-run', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-submit', 'test-job-run', '--jobs-path', get_test_jobs_directory() ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-run', 'test-job-run', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-run', 'test-job-run', '--jobs-path', get_test_jobs_directory() ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert subprocess.run(commands).returncode == 1
@@ -51,33 +51,33 @@ def test_job_run() -> None:
 
 
 def test_job_run_all() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'job-run-all', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-run-all', '--jobs-path', get_test_jobs_directory() ]
 
 	assert subprocess.run(commands).returncode == 1
 
-	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-run-all-1', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-run-all-1', '--jobs-path', get_test_jobs_directory() ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-run-all-2', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-run-all-2', '--jobs-path', get_test_jobs_directory() ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-run-all-1', '-j', get_test_jobs_directory(), '--processors', 'face_debugger', '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-run-all-1.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-run-all-1', '--jobs-path', get_test_jobs_directory(), '--processors', 'face_debugger', '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-run-all-1.jpg') ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-run-all-2', '-j', get_test_jobs_directory(), '--processors', 'face_debugger', '-t', get_test_example_file('target-240p.mp4'), '-o', get_test_output_file('test-job-run-all-2.mp4'), '--trim-frame-end', '1' ]
+	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-run-all-2', '--jobs-path', get_test_jobs_directory(), '--processors', 'face_debugger', '-t', get_test_example_file('target-240p.mp4'), '-o', get_test_output_file('test-job-run-all-2.mp4'), '--trim-frame-end', '1' ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-run-all-2', '-j', get_test_jobs_directory(), '--processors', 'face_debugger', '-t', get_test_example_file('target-240p.mp4'), '-o', get_test_output_file('test-job-run-all-2.mp4'), '--trim-frame-start', '0', '--trim-frame-end', '1' ]
+	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-run-all-2', '--jobs-path', get_test_jobs_directory(), '--processors', 'face_debugger', '-t', get_test_example_file('target-240p.mp4'), '-o', get_test_output_file('test-job-run-all-2.mp4'), '--trim-frame-start', '0', '--trim-frame-end', '1' ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-run-all', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-run-all', '--jobs-path', get_test_jobs_directory() ]
 
 	assert subprocess.run(commands).returncode == 1
 
-	commands = [ sys.executable, 'facefusion.py', 'job-submit-all', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-submit-all', '--jobs-path', get_test_jobs_directory() ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-run-all', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-run-all', '--jobs-path', get_test_jobs_directory() ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert subprocess.run(commands).returncode == 1
@@ -86,24 +86,24 @@ def test_job_run_all() -> None:
 
 
 def test_job_retry() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'job-retry', 'test-job-retry', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-retry', 'test-job-retry', '--jobs-path', get_test_jobs_directory() ]
 
 	assert subprocess.run(commands).returncode == 1
 
-	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-retry', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-retry', '--jobs-path', get_test_jobs_directory() ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-retry', '-j', get_test_jobs_directory(), '--processors', 'face_debugger', '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-retry.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-retry', '--jobs-path', get_test_jobs_directory(), '--processors', 'face_debugger', '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-retry.jpg') ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-retry', 'test-job-retry', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-retry', 'test-job-retry', '--jobs-path', get_test_jobs_directory() ]
 
 	assert subprocess.run(commands).returncode == 1
 
 	set_steps_status('test-job-retry', 'failed')
 	move_job_file('test-job-retry', 'failed')
 
-	commands = [ sys.executable, 'facefusion.py', 'job-retry', 'test-job-retry', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-retry', 'test-job-retry', '--jobs-path', get_test_jobs_directory() ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert subprocess.run(commands).returncode == 1
@@ -111,26 +111,26 @@ def test_job_retry() -> None:
 
 
 def test_job_retry_all() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'job-retry-all', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-retry-all', '--jobs-path', get_test_jobs_directory() ]
 
 	assert subprocess.run(commands).returncode == 1
 
-	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-retry-all-1', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-retry-all-1', '--jobs-path', get_test_jobs_directory() ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-retry-all-2', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-retry-all-2', '--jobs-path', get_test_jobs_directory() ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-retry-all-1', '-j', get_test_jobs_directory(), '--processors', 'face_debugger', '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-retry-all-1.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-retry-all-1', '--jobs-path', get_test_jobs_directory(), '--processors', 'face_debugger', '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test-job-retry-all-1.jpg') ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-retry-all-2', '-j', get_test_jobs_directory(), '--processors', 'face_debugger', '-t', get_test_example_file('target-240p.mp4'), '-o', get_test_output_file('test-job-retry-all-2.mp4'), '--trim-frame-end', '1' ]
+	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-retry-all-2', '--jobs-path', get_test_jobs_directory(), '--processors', 'face_debugger', '-t', get_test_example_file('target-240p.mp4'), '-o', get_test_output_file('test-job-retry-all-2.mp4'), '--trim-frame-end', '1' ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-retry-all-2', '-j', get_test_jobs_directory(), '--processors', 'face_debugger', '-t', get_test_example_file('target-240p.mp4'), '-o', get_test_output_file('test-job-retry-all-2.mp4'), '--trim-frame-start', '0', '--trim-frame-end', '1' ]
+	commands = [ sys.executable, 'facefusion.py', 'job-add-step', 'test-job-retry-all-2', '--jobs-path', get_test_jobs_directory(), '--processors', 'face_debugger', '-t', get_test_example_file('target-240p.mp4'), '-o', get_test_output_file('test-job-retry-all-2.mp4'), '--trim-frame-start', '0', '--trim-frame-end', '1' ]
 	subprocess.run(commands)
 
-	commands = [ sys.executable, 'facefusion.py', 'job-retry-all', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-retry-all', '--jobs-path', get_test_jobs_directory() ]
 
 	assert subprocess.run(commands).returncode == 1
 
@@ -139,7 +139,7 @@ def test_job_retry_all() -> None:
 	move_job_file('test-job-retry-all-1', 'failed')
 	move_job_file('test-job-retry-all-2', 'failed')
 
-	commands = [ sys.executable, 'facefusion.py', 'job-retry-all', '-j', get_test_jobs_directory() ]
+	commands = [ sys.executable, 'facefusion.py', 'job-retry-all', '--jobs-path', get_test_jobs_directory() ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert subprocess.run(commands).returncode == 1

tests/test_cli_lip_syncer.py

@@ -27,14 +27,14 @@ def before_each() -> None:
 
 
 def test_sync_lip_to_image() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'headless-run', '-j', get_test_jobs_directory(), '--processors', 'lip_syncer', '-s', get_test_example_file('source.mp3'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test_sync_lip_to_image.jpg') ]
+	commands = [ sys.executable, 'facefusion.py', 'headless-run', '--jobs-path', get_test_jobs_directory(), '--processors', 'lip_syncer', '-s', get_test_example_file('source.mp3'), '-t', get_test_example_file('target-240p.jpg'), '-o', get_test_output_file('test_sync_lip_to_image.jpg') ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert is_test_output_file('test_sync_lip_to_image.jpg') is True
 
 
 def test_sync_lip_to_video() -> None:
-	commands = [ sys.executable, 'facefusion.py', 'headless-run', '-j', get_test_jobs_directory(), '--processors', 'lip_syncer', '-s', get_test_example_file('source.mp3'), '-t', get_test_example_file('target-240p.mp4'), '-o', get_test_output_file('test_sync_lip_to_video.mp4'), '--trim-frame-end', '1' ]
+	commands = [ sys.executable, 'facefusion.py', 'headless-run', '--jobs-path', get_test_jobs_directory(), '--processors', 'lip_syncer', '-s', get_test_example_file('source.mp3'), '-t', get_test_example_file('target-240p.mp4'), '-o', get_test_output_file('test_sync_lip_to_video.mp4'), '--trim-frame-end', '1' ]
 
 	assert subprocess.run(commands).returncode == 0
 	assert is_test_output_file('test_sync_lip_to_video.mp4') is True

tests/test_date_helper.py

@@ -10,6 +10,6 @@ def get_time_ago(days : int, hours : int, minutes : int) -> datetime:
 
 def test_describe_time_ago() -> None:
 	assert describe_time_ago(get_time_ago(0, 0, 0)) == 'just now'
-	assert describe_time_ago(get_time_ago(0, 0, 5)) == '5 minutes ago'
+	assert describe_time_ago(get_time_ago(0, 0, 10)) == '10 minutes ago'
 	assert describe_time_ago(get_time_ago(0, 5, 10)) == '5 hours and 10 minutes ago'
-	assert describe_time_ago(get_time_ago(5, 10, 15)) == '5 days, 10 hours and 15 minutes ago'
+	assert describe_time_ago(get_time_ago(1, 5, 10)) == '1 days, 5 hours and 10 minutes ago'

tests/test_download.py

@@ -1,7 +1,7 @@
 import pytest
 
-from facefusion.download import conditional_download, get_download_size, is_download_done
-from .helper import get_test_example_file, get_test_examples_directory
+from facefusion.download import conditional_download, get_download_size
+from .helper import get_test_examples_directory
 
 
 @pytest.fixture(scope = 'module', autouse = True)
@@ -16,9 +16,3 @@ def test_get_download_size() -> None:
 	assert get_download_size('https://github.com/facefusion/facefusion-assets/releases/download/examples-3.0.0/target-240p.mp4') == 191675
 	assert get_download_size('https://github.com/facefusion/facefusion-assets/releases/download/examples-3.0.0/target-360p.mp4') == 370732
 	assert get_download_size('invalid') == 0
-
-
-def test_is_download_done() -> None:
-	assert is_download_done('https://github.com/facefusion/facefusion-assets/releases/download/examples-3.0.0/target-240p.mp4', get_test_example_file('target-240p.mp4')) is True
-	assert is_download_done('https://github.com/facefusion/facefusion-assets/releases/download/examples-3.0.0/target-240p.mp4', 'invalid') is False
-	assert is_download_done('invalid', 'invalid') is False

tests/test_execution.py

@@ -1,8 +1,8 @@
-from facefusion.execution import create_execution_providers, get_execution_provider_choices, has_execution_provider
+from facefusion.execution import create_execution_providers, get_execution_provider_set, has_execution_provider
 
 
-def test_get_execution_provider_choices() -> None:
-	assert 'cpu' in get_execution_provider_choices()
+def test_get_execution_provider_set() -> None:
+	assert 'cpu' in get_execution_provider_set().keys()
 
 
 def test_has_execution_provider() -> None:
@@ -15,8 +15,7 @@ def test_multiple_execution_providers() -> None:
 	[
 		('CUDAExecutionProvider',
 		{
-			'device_id': '1',
-			'cudnn_conv_algo_search': 'DEFAULT'
+			'device_id': '1'
 		}),
 		'CPUExecutionProvider'
 	]

tests/test_face_analyser.py

@@ -21,6 +21,7 @@ def before_all() -> None:
 	subprocess.run([ 'ffmpeg', '-i', get_test_example_file('source.jpg'), '-vf', 'crop=iw*0.6:ih*0.6', get_test_example_file('source-60crop.jpg') ])
 	state_manager.init_item('execution_device_id', 0)
 	state_manager.init_item('execution_providers', [ 'cpu' ])
+	state_manager.init_item('download_providers', [ 'github' ])
 	state_manager.init_item('face_detector_angles', [ 0 ])
 	state_manager.init_item('face_detector_model', 'many')
 	state_manager.init_item('face_detector_score', 0.5)

tests/test_ffmpeg.py

@@ -1,12 +1,13 @@
-import glob
 import subprocess
+import tempfile
 
 import pytest
 
 from facefusion import process_manager, state_manager
 from facefusion.download import conditional_download
-from facefusion.ffmpeg import concat_video, extract_frames, read_audio_buffer
-from facefusion.temp_helper import clear_temp_directory, create_temp_directory, get_temp_directory_path
+from facefusion.ffmpeg import concat_video, extract_frames, read_audio_buffer, replace_audio, restore_audio
+from facefusion.filesystem import copy_file
+from facefusion.temp_helper import clear_temp_directory, create_temp_directory, get_temp_file_path, get_temp_frame_paths
 from .helper import get_test_example_file, get_test_examples_directory, get_test_output_file, prepare_test_output_directory
 
 
@@ -23,7 +24,10 @@ def before_all() -> None:
 	subprocess.run([ 'ffmpeg', '-i', get_test_example_file('target-240p.mp4'), '-vf', 'fps=25', get_test_example_file('target-240p-25fps.mp4') ])
 	subprocess.run([ 'ffmpeg', '-i', get_test_example_file('target-240p.mp4'), '-vf', 'fps=30', get_test_example_file('target-240p-30fps.mp4') ])
 	subprocess.run([ 'ffmpeg', '-i', get_test_example_file('target-240p.mp4'), '-vf', 'fps=60', get_test_example_file('target-240p-60fps.mp4') ])
-	state_manager.init_item('temp_frame_format', 'jpg')
+	subprocess.run([ 'ffmpeg', '-i', get_test_example_file('source.mp3'), '-i', get_test_example_file('target-240p.mp4'), '-ar', '16000', get_test_example_file('target-240p-16khz.mp4') ])
+	subprocess.run([ 'ffmpeg', '-i', get_test_example_file('source.mp3'), '-i', get_test_example_file('target-240p.mp4'), '-ar', '48000', get_test_example_file('target-240p-48khz.mp4') ])
+	state_manager.init_item('temp_path', tempfile.gettempdir())
+	state_manager.init_item('temp_frame_format', 'png')
 	state_manager.init_item('output_audio_encoder', 'aac')
 
 
@@ -43,30 +47,28 @@ def test_extract_frames() -> None:
 	]
 
 	for target_path in target_paths:
-		temp_directory_path = get_temp_directory_path(target_path)
 		create_temp_directory(target_path)
 
 		assert extract_frames(target_path, '452x240', 30.0) is True
-		assert len(glob.glob1(temp_directory_path, '*.jpg')) == 324
+		assert len(get_temp_frame_paths(target_path)) == 324
 
 		clear_temp_directory(target_path)
 
 
 def test_extract_frames_with_trim_start() -> None:
 	state_manager.init_item('trim_frame_start', 224)
-	providers =\
+	target_paths =\
 	[
 		(get_test_example_file('target-240p-25fps.mp4'), 55),
 		(get_test_example_file('target-240p-30fps.mp4'), 100),
 		(get_test_example_file('target-240p-60fps.mp4'), 212)
 	]
 
-	for target_path, frame_total in providers:
-		temp_directory_path = get_temp_directory_path(target_path)
+	for target_path, frame_total in target_paths:
 		create_temp_directory(target_path)
 
 		assert extract_frames(target_path, '452x240', 30.0) is True
-		assert len(glob.glob1(temp_directory_path, '*.jpg')) == frame_total
+		assert len(get_temp_frame_paths(target_path)) == frame_total
 
 		clear_temp_directory(target_path)
 
@@ -74,38 +76,36 @@ def test_extract_frames_with_trim_start() -> None:
 def test_extract_frames_with_trim_start_and_trim_end() -> None:
 	state_manager.init_item('trim_frame_start', 124)
 	state_manager.init_item('trim_frame_end', 224)
-	providers =\
+	target_paths =\
 	[
 		(get_test_example_file('target-240p-25fps.mp4'), 120),
 		(get_test_example_file('target-240p-30fps.mp4'), 100),
 		(get_test_example_file('target-240p-60fps.mp4'), 50)
 	]
 
-	for target_path, frame_total in providers:
-		temp_directory_path = get_temp_directory_path(target_path)
+	for target_path, frame_total in target_paths:
 		create_temp_directory(target_path)
 
 		assert extract_frames(target_path, '452x240', 30.0) is True
-		assert len(glob.glob1(temp_directory_path, '*.jpg')) == frame_total
+		assert len(get_temp_frame_paths(target_path)) == frame_total
 
 		clear_temp_directory(target_path)
 
 
 def test_extract_frames_with_trim_end() -> None:
 	state_manager.init_item('trim_frame_end', 100)
-	providers =\
+	target_paths =\
 	[
 		(get_test_example_file('target-240p-25fps.mp4'), 120),
 		(get_test_example_file('target-240p-30fps.mp4'), 100),
 		(get_test_example_file('target-240p-60fps.mp4'), 50)
 	]
 
-	for target_path, frame_total in providers:
-		temp_directory_path = get_temp_directory_path(target_path)
+	for target_path, frame_total in target_paths:
 		create_temp_directory(target_path)
 
 		assert extract_frames(target_path, '426x240', 30.0) is True
-		assert len(glob.glob1(temp_directory_path, '*.jpg')) == frame_total
+		assert len(get_temp_frame_paths(target_path)) == frame_total
 
 		clear_temp_directory(target_path)
 
@@ -125,3 +125,33 @@ def test_read_audio_buffer() -> None:
 	assert isinstance(read_audio_buffer(get_test_example_file('source.mp3'), 1, 1), bytes)
 	assert isinstance(read_audio_buffer(get_test_example_file('source.wav'), 1, 1), bytes)
 	assert read_audio_buffer(get_test_example_file('invalid.mp3'), 1, 1) is None
+
+
+def test_restore_audio() -> None:
+	target_paths =\
+	[
+		get_test_example_file('target-240p-16khz.mp4'),
+		get_test_example_file('target-240p-48khz.mp4')
+	]
+	output_path = get_test_output_file('test-restore-audio.mp4')
+
+	for target_path in target_paths:
+		create_temp_directory(target_path)
+		copy_file(target_path, get_temp_file_path(target_path))
+
+		assert restore_audio(target_path, output_path, 30) is True
+
+		clear_temp_directory(target_path)
+
+
+def test_replace_audio() -> None:
+	target_path = get_test_example_file('target-240p.mp4')
+	output_path = get_test_output_file('test-replace-audio.mp4')
+
+	create_temp_directory(target_path)
+	copy_file(target_path, get_temp_file_path(target_path))
+
+	assert replace_audio(target_path, get_test_example_file('source.mp3'), output_path) is True
+	assert replace_audio(target_path, get_test_example_file('source.wav'), output_path) is True
+
+	clear_temp_directory(target_path)

tests/test_inference_pool.py

@@ -9,9 +9,10 @@ from facefusion.inference_manager import INFERENCE_POOLS, get_inference_pool
 
 @pytest.fixture(scope = 'module', autouse = True)
 def before_all() -> None:
-	content_analyser.pre_check()
 	state_manager.init_item('execution_device_id', 0)
 	state_manager.init_item('execution_providers', [ 'cpu' ])
+	state_manager.init_item('download_providers', [ 'github' ])
+	content_analyser.pre_check()
 
 
 def test_get_inference_pool() -> None:

tests/test_program_helper.py

@@ -2,7 +2,7 @@ from argparse import ArgumentParser
 
 import pytest
 
-from facefusion.program_helper import find_argument_group, remove_args, validate_actions
+from facefusion.program_helper import find_argument_group, validate_actions
 
 
 def test_find_argument_group() -> None:
@@ -38,23 +38,3 @@ def test_validate_actions() -> None:
 			action.default = args[action.dest]
 
 	assert validate_actions(program) is False
-
-
-def test_remove_args() -> None:
-	program = ArgumentParser()
-	program.add_argument('--test-1')
-	program.add_argument('--test-2')
-	program.add_argument('--test-3')
-
-	actions = [ action.dest for action in program._actions ]
-
-	assert 'test_1' in actions
-	assert 'test_2' in actions
-	assert 'test_3' in actions
-
-	program = remove_args(program, [ 'test_1', 'test_2' ])
-	actions = [ action.dest for action in program._actions ]
-
-	assert 'test_1' not in actions
-	assert 'test_2' not in actions
-	assert 'test_3' in actions

tests/test_temp_helper.py

@@ -15,6 +15,7 @@ def before_all() -> None:
 	[
 		'https://github.com/facefusion/facefusion-assets/releases/download/examples-3.0.0/target-240p.mp4'
 	])
+	state_manager.init_item('temp_path', tempfile.gettempdir())
 	state_manager.init_item('temp_frame_format', 'png')
 
 

tests/test_vision.py

@@ -3,7 +3,7 @@ import subprocess
 import pytest
 
 from facefusion.download import conditional_download
-from facefusion.vision import count_video_frame_total, create_image_resolutions, create_video_resolutions, detect_image_resolution, detect_video_fps, detect_video_resolution, get_video_frame, normalize_resolution, pack_resolution, restrict_image_resolution, restrict_video_fps, restrict_video_resolution, unpack_resolution
+from facefusion.vision import calc_histogram_difference, count_video_frame_total, create_image_resolutions, create_video_resolutions, detect_image_resolution, detect_video_duration, detect_video_fps, detect_video_resolution, get_video_frame, match_frame_color, normalize_resolution, pack_resolution, read_image, restrict_image_resolution, restrict_video_fps, restrict_video_resolution, unpack_resolution
 from .helper import get_test_example_file, get_test_examples_directory
 
 
@@ -17,6 +17,7 @@ def before_all() -> None:
 	])
 	subprocess.run([ 'ffmpeg', '-i', get_test_example_file('target-240p.mp4'), '-vframes', '1', get_test_example_file('target-240p.jpg') ])
 	subprocess.run([ 'ffmpeg', '-i', get_test_example_file('target-1080p.mp4'), '-vframes', '1', get_test_example_file('target-1080p.jpg') ])
+	subprocess.run([ 'ffmpeg', '-i', get_test_example_file('target-240p.mp4'), '-vframes', '1', '-vf', 'hue=s=0', get_test_example_file('target-240p-0sat.jpg') ])
 	subprocess.run([ 'ffmpeg', '-i', get_test_example_file('target-240p.mp4'), '-vframes', '1', '-vf', 'transpose=0', get_test_example_file('target-240p-90deg.jpg') ])
 	subprocess.run([ 'ffmpeg', '-i', get_test_example_file('target-1080p.mp4'), '-vframes', '1', '-vf', 'transpose=0', get_test_example_file('target-1080p-90deg.jpg') ])
 	subprocess.run([ 'ffmpeg', '-i', get_test_example_file('target-240p.mp4'), '-vf', 'fps=25', get_test_example_file('target-240p-25fps.mp4') ])
@@ -73,6 +74,11 @@ def test_restrict_video_fps() -> None:
 	assert restrict_video_fps(get_test_example_file('target-1080p.mp4'), 60.0) == 25.0
 
 
+def test_detect_video_duration() -> None:
+	assert detect_video_duration(get_test_example_file('target-240p.mp4')) == 10.8
+	assert detect_video_duration('invalid') == 0
+
+
 def test_detect_video_resolution() -> None:
 	assert detect_video_resolution(get_test_example_file('target-240p.mp4')) == (426, 226)
 	assert detect_video_resolution(get_test_example_file('target-240p-90deg.mp4')) == (226, 426)
@@ -109,3 +115,19 @@ def test_pack_resolution() -> None:
 def test_unpack_resolution() -> None:
 	assert unpack_resolution('0x0') == (0, 0)
 	assert unpack_resolution('2x2') == (2, 2)
+
+
+def test_calc_histogram_difference() -> None:
+	source_vision_frame = read_image(get_test_example_file('target-240p.jpg'))
+	target_vision_frame = read_image(get_test_example_file('target-240p-0sat.jpg'))
+
+	assert calc_histogram_difference(source_vision_frame, source_vision_frame) == 1.0
+	assert calc_histogram_difference(source_vision_frame, target_vision_frame) < 0.5
+
+
+def test_match_frame_color() -> None:
+	source_vision_frame = read_image(get_test_example_file('target-240p.jpg'))
+	target_vision_frame = read_image(get_test_example_file('target-240p-0sat.jpg'))
+	output_vision_frame = match_frame_color(source_vision_frame, target_vision_frame)
+
+	assert calc_histogram_difference(source_vision_frame, output_vision_frame) > 0.5