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Refactor/choices and naming (#833)

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* Refactor choices, imports and naming

* Refactor choices, imports and naming
This commit is contained in:
Henry Ruhs 2024-12-12 08:30:23 +01:00 committed by GitHub
parent 5856ac509e
commit 2ca200bd0a
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GPG Key ID: B5690EEEBB952194
19 changed files with 103 additions and 94 deletions
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6
facefusion/choices.py
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@ -2,7 +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, DownloadProviderSet, DownloadScope, ExecutionProviderSet, FaceDetectorSet, FaceLandmarkerModel, FaceMaskRegion, FaceMaskType, FaceSelectorMode, FaceSelectorOrder, Gender, JobStatus, LogLevelSet, OutputAudioEncoder, OutputVideoEncoder, OutputVideoPreset, Race, Score, TempFrameFormat, UiWorkflow, VideoMemoryStrategy
from facefusion.typing import Angle, DownloadProvider, DownloadProviderSet, DownloadScope, ExecutionProvider, ExecutionProviderSet, FaceDetectorModel, FaceDetectorSet, FaceLandmarkerModel, FaceMaskRegion, FaceMaskType, FaceSelectorMode, FaceSelectorOrder, Gender, JobStatus, LogLevel, LogLevelSet, OutputAudioEncoder, OutputVideoEncoder, OutputVideoPreset, Race, Score, TempFrameFormat, UiWorkflow, VideoMemoryStrategy
face_detector_set : FaceDetectorSet =\
{
@ -11,6 +11,7 @@ face_detector_set : FaceDetectorSet =\
'scrfd': [ '160x160', '320x320', '480x480', '512x512', '640x640' ],
'yoloface': [ '640x640' ]
}
face_detector_models : List[FaceDetectorModel] = list(face_detector_set.keys())
face_landmarker_models : List[FaceLandmarkerModel] = [ 'many', '2dfan4', 'peppa_wutz' ]
face_selector_modes : List[FaceSelectorMode] = [ 'many', 'one', 'reference' ]
face_selector_orders : List[FaceSelectorOrder] = [ 'left-right', 'right-left', 'top-bottom', 'bottom-top', 'small-large', 'large-small', 'best-worst', 'worst-best' ]
@ -36,11 +37,13 @@ execution_provider_set : ExecutionProviderSet =\
'rocm': 'ROCMExecutionProvider',
'tensorrt': 'TensorrtExecutionProvider'
}
execution_providers : List[ExecutionProvider] = list(execution_provider_set.keys())
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_providers : List[DownloadProvider] = list(download_provider_set.keys())
download_scopes : List[DownloadScope] = [ 'lite', 'full' ]
video_memory_strategies : List[VideoMemoryStrategy] = [ 'strict', 'moderate', 'tolerant' ]
@ -52,6 +55,7 @@ log_level_set : LogLevelSet =\
'info': logging.INFO,
'debug': logging.DEBUG
}
log_levels : List[LogLevel] = list(log_level_set.keys())
ui_workflows : List[UiWorkflow] = [ 'instant_runner', 'job_runner', 'job_manager' ]
job_statuses : List[JobStatus] = [ 'drafted', 'queued', 'completed', 'failed' ]

10
facefusion/download.py
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@ -9,12 +9,12 @@ from urllib.parse import urlparse
from tqdm import tqdm
import facefusion.choices
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 DownloadProviderKey, DownloadSet
from facefusion.typing import DownloadProvider, DownloadSet
if is_macos():
ssl._create_default_https_context = ssl._create_unverified_context
@ -128,11 +128,11 @@ def validate_source_paths(source_paths : List[str]) -> Tuple[List[str], List[str
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:
for download_provider in facefusion.choices.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)
def resolve_download_url_by_provider(download_provider : DownloadProvider, base_name : str, file_name : str) -> Optional[str]:
return facefusion.choices.download_provider_set.get(download_provider).format(base_name = base_name, file_name = file_name)

55
facefusion/execution.py
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@ -6,37 +6,38 @@ from typing import Any, List, Optional
from onnxruntime import get_available_providers, set_default_logger_severity
from facefusion.choices import execution_provider_set
from facefusion.typing import ExecutionDevice, ExecutionProviderKey, ExecutionProviderSet, ValueAndUnit
import facefusion.choices
from facefusion.typing import ExecutionDevice, ExecutionProvider, ValueAndUnit
set_default_logger_severity(3)
def has_execution_provider(execution_provider_key : ExecutionProviderKey) -> bool:
return execution_provider_key in get_execution_provider_set().keys()
def has_execution_provider(execution_provider : ExecutionProvider) -> bool:
return execution_provider in get_available_execution_providers()
def get_execution_provider_set() -> ExecutionProviderSet:
available_execution_providers = get_available_providers()
available_execution_provider_set : ExecutionProviderSet = {}
def get_available_execution_providers() -> List[ExecutionProvider]:
inference_execution_providers = get_available_providers()
available_execution_providers = []
for execution_provider_key, execution_provider_value in execution_provider_set.items():
if execution_provider_value in available_execution_providers:
available_execution_provider_set[execution_provider_key] = execution_provider_value
return available_execution_provider_set
for execution_provider, execution_provider_value in facefusion.choices.execution_provider_set.items():
if execution_provider_value in inference_execution_providers:
available_execution_providers.append(execution_provider)
return available_execution_providers
def create_execution_providers(execution_device_id : str, execution_provider_keys : List[ExecutionProviderKey]) -> List[Any]:
execution_providers : List[Any] = []
def create_inference_execution_providers(execution_device_id : str, execution_providers : List[ExecutionProvider]) -> List[Any]:
inference_execution_providers : List[Any] = []
for execution_provider_key in execution_provider_keys:
if execution_provider_key == 'cuda':
execution_providers.append((execution_provider_set.get(execution_provider_key),
for execution_provider in execution_providers:
if execution_provider == 'cuda':
inference_execution_providers.append((facefusion.choices.execution_provider_set.get(execution_provider),
{
'device_id': execution_device_id
}))
if execution_provider_key == 'tensorrt':
execution_providers.append((execution_provider_set.get(execution_provider_key),
if execution_provider == 'tensorrt':
inference_execution_providers.append((facefusion.choices.execution_provider_set.get(execution_provider),
{
'device_id': execution_device_id,
'trt_engine_cache_enable': True,
@ -45,24 +46,24 @@ def create_execution_providers(execution_device_id : str, execution_provider_key
'trt_timing_cache_path': '.caches',
'trt_builder_optimization_level': 5
}))
if execution_provider_key == 'openvino':
execution_providers.append((execution_provider_set.get(execution_provider_key),
if execution_provider == 'openvino':
inference_execution_providers.append((facefusion.choices.execution_provider_set.get(execution_provider),
{
'device_type': 'GPU' if execution_device_id == '0' else 'GPU.' + execution_device_id,
'precision': 'FP32'
}))
if execution_provider_key in [ 'directml', 'rocm' ]:
execution_providers.append((execution_provider_set.get(execution_provider_key),
if execution_provider in [ 'directml', 'rocm' ]:
inference_execution_providers.append((facefusion.choices.execution_provider_set.get(execution_provider),
{
'device_id': execution_device_id
}))
if execution_provider_key == 'coreml':
execution_providers.append(execution_provider_set.get(execution_provider_key))
if execution_provider == 'coreml':
inference_execution_providers.append(facefusion.choices.execution_provider_set.get(execution_provider))
if 'cpu' in execution_provider_keys:
execution_providers.append(execution_provider_set.get('cpu'))
if 'cpu' in execution_providers:
inference_execution_providers.append(facefusion.choices.execution_provider_set.get('cpu'))
return execution_providers
return inference_execution_providers
def run_nvidia_smi() -> subprocess.Popen[bytes]:

14
facefusion/inference_manager.py
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@ -5,9 +5,9 @@ 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
from facefusion.execution import create_inference_execution_providers
from facefusion.thread_helper import thread_lock
from facefusion.typing import DownloadSet, ExecutionProviderKey, InferencePool, InferencePoolSet
from facefusion.typing import DownloadSet, ExecutionProvider, InferencePool, InferencePoolSet
INFERENCE_POOLS : InferencePoolSet =\
{
@ -35,11 +35,11 @@ def get_inference_pool(model_context : str, model_sources : DownloadSet) -> Infe
return INFERENCE_POOLS.get(app_context).get(inference_context)
def create_inference_pool(model_sources : DownloadSet, execution_device_id : str, execution_provider_keys : List[ExecutionProviderKey]) -> InferencePool:
def create_inference_pool(model_sources : DownloadSet, execution_device_id : str, execution_providers : List[ExecutionProvider]) -> InferencePool:
inference_pool : InferencePool = {}
for model_name in model_sources.keys():
inference_pool[model_name] = create_inference_session(model_sources.get(model_name).get('path'), execution_device_id, execution_provider_keys)
inference_pool[model_name] = create_inference_session(model_sources.get(model_name).get('path'), execution_device_id, execution_providers)
return inference_pool
@ -53,9 +53,9 @@ def clear_inference_pool(model_context : str) -> None:
del INFERENCE_POOLS[app_context][inference_context]
def create_inference_session(model_path : str, execution_device_id : str, execution_provider_keys : List[ExecutionProviderKey]) -> InferenceSession:
execution_providers = create_execution_providers(execution_device_id, execution_provider_keys)
return InferenceSession(model_path, providers = execution_providers)
def create_inference_session(model_path : str, execution_device_id : str, execution_providers : List[ExecutionProvider]) -> InferenceSession:
inference_execution_providers = create_inference_execution_providers(execution_device_id, execution_providers)
return InferenceSession(model_path, providers = inference_execution_providers)
def get_inference_context(model_context : str) -> str:

6
facefusion/jobs/job_manager.py
View File

@ -2,7 +2,7 @@ import os
from copy import copy
from typing import List, Optional
from facefusion.choices import job_statuses
import facefusion.choices
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, resolve_file_pattern
from facefusion.jobs.job_helper import get_step_output_path
@ -16,7 +16,7 @@ def init_jobs(jobs_path : str) -> bool:
global JOBS_PATH
JOBS_PATH = jobs_path
job_status_paths = [ os.path.join(JOBS_PATH, job_status) for job_status in job_statuses ]
job_status_paths = [ os.path.join(JOBS_PATH, job_status) for job_status in facefusion.choices.job_statuses ]
for job_status_path in job_status_paths:
create_directory(job_status_path)
@ -245,7 +245,7 @@ def find_job_path(job_id : str) -> Optional[str]:
job_file_name = get_job_file_name(job_id)
if job_file_name:
for job_status in job_statuses:
for job_status in facefusion.choices.job_statuses:
job_pattern = os.path.join(JOBS_PATH, job_status, job_file_name)
job_paths = resolve_file_pattern(job_pattern)

4
facefusion/logger.py
View File

@ -1,14 +1,14 @@
from logging import Logger, basicConfig, getLogger
from typing import Tuple
from facefusion.choices import log_level_set
import facefusion.choices
from facefusion.common_helper import get_first, get_last
from facefusion.typing import LogLevel, TableContents, TableHeaders
def init(log_level : LogLevel) -> None:
basicConfig(format = '%(message)s')
get_package_logger().setLevel(log_level_set.get(log_level))
get_package_logger().setLevel(facefusion.choices.log_level_set.get(log_level))
def get_package_logger() -> Logger:

11
facefusion/processors/choices.py
View File

@ -2,7 +2,7 @@ from typing import List, Sequence
from facefusion.common_helper import create_float_range, create_int_range
from facefusion.filesystem import list_directory, resolve_relative_path
from facefusion.processors.typing import AgeModifierModel, DeepSwapperModel, ExpressionRestorerModel, FaceDebuggerItem, FaceEditorModel, FaceEnhancerModel, FaceSwapperSet, FrameColorizerModel, FrameEnhancerModel, LipSyncerModel
from facefusion.processors.typing import AgeModifierModel, DeepSwapperModel, ExpressionRestorerModel, FaceDebuggerItem, FaceEditorModel, FaceEnhancerModel, FaceSwapperModel, FaceSwapperSet, FrameColorizerModel, FrameEnhancerModel, LipSyncerModel
age_modifier_models : List[AgeModifierModel] = [ 'styleganex_age' ]
deep_swapper_models : List[DeepSwapperModel] =\
@ -156,12 +156,12 @@ deep_swapper_models : List[DeepSwapperModel] =\
'rumateus/taylor_swift_224'
]
model_files = list_directory(resolve_relative_path('../.assets/models/local'))
custom_model_files = list_directory(resolve_relative_path('../.assets/models/custom'))
if model_files:
if custom_model_files:
for model_file in model_files:
model_id = '/'.join([ 'local', model_file.get('name') ])
for model_file in custom_model_files:
model_id = '/'.join([ 'custom', model_file.get('name') ])
deep_swapper_models.append(model_id)
expression_restorer_models : List[ExpressionRestorerModel] = [ 'live_portrait' ]
@ -181,6 +181,7 @@ face_swapper_set : FaceSwapperSet =\
'simswap_unofficial_512': [ '512x512', '768x768', '1024x1024' ],
'uniface_256': [ '256x256', '512x512', '768x768', '1024x1024' ]
}
face_swapper_models : List[FaceSwapperModel] = list(face_swapper_set.keys())
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', 'real_web_photo_x4', 'realistic_rescaler_x4', 'remacri_x4', 'siax_x4', 'span_kendata_x4', 'swin2_sr_x4', 'ultra_sharp_x4' ]

4
facefusion/processors/modules/age_modifier.py
View File

@ -5,11 +5,11 @@ from typing import List
import cv2
import numpy
import facefusion.choices
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, resolve_download_url
from facefusion.execution import has_execution_provider
@ -163,7 +163,7 @@ def forward(crop_vision_frame : VisionFrame, extend_vision_frame : VisionFrame,
age_modifier_inputs = {}
if has_execution_provider('coreml'):
age_modifier.set_providers([ execution_provider_set.get('cpu') ])
age_modifier.set_providers([ facefusion.choices.execution_provider_set.get('cpu') ])
for age_modifier_input in age_modifier.get_inputs():
if age_modifier_input.name == 'target':

8
facefusion/processors/modules/deep_swapper.py
View File

@ -215,12 +215,12 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
'template': 'dfl_whole_face'
}
model_files = list_directory(resolve_relative_path('../.assets/models/local'))
custom_model_files = list_directory(resolve_relative_path('../.assets/models/custom'))
if model_files:
if custom_model_files:
for model_file in model_files:
model_id = '/'.join([ 'local', model_file.get('name') ])
for model_file in custom_model_files:
model_id = '/'.join([ 'custom', model_file.get('name') ])
model_set[model_id] =\
{

6
facefusion/processors/modules/face_swapper.py
View File

@ -4,11 +4,11 @@ from typing import List, Tuple
import numpy
import facefusion.choices
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, resolve_download_url
from facefusion.execution import has_execution_provider
@ -354,7 +354,7 @@ def get_model_options() -> ModelOptions:
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())
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_models)
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)
@ -449,7 +449,7 @@ def forward_swap_face(source_face : Face, crop_vision_frame : VisionFrame) -> Vi
face_swapper_inputs = {}
if has_execution_provider('coreml') and model_type in [ 'ghost', 'uniface' ]:
face_swapper.set_providers([ execution_provider_set.get('cpu') ])
face_swapper.set_providers([ facefusion.choices.execution_provider_set.get('cpu') ])
for face_swapper_input in face_swapper.get_inputs():
if face_swapper_input.name == 'source':

15
facefusion/program.py
View File

@ -4,7 +4,7 @@ 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, get_last
from facefusion.execution import get_execution_provider_set
from facefusion.execution import get_available_execution_providers
from facefusion.filesystem import list_directory
from facefusion.jobs import job_store
from facefusion.processors.core import get_processors_modules
@ -94,7 +94,7 @@ def create_output_pattern_program() -> ArgumentParser:
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 = list(facefusion.choices.face_detector_set.keys()))
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_models)
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)
@ -190,9 +190,10 @@ def create_uis_program() -> ArgumentParser:
def create_execution_program() -> ArgumentParser:
program = ArgumentParser(add_help = False)
available_execution_providers = get_available_execution_providers()
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(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-providers', help = wording.get('help.execution_providers').format(choices = ', '.join(available_execution_providers)), default = config.get_str_list('execution.execution_providers', 'cpu'), choices = available_execution_providers, 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' ])
@ -201,8 +202,9 @@ def create_execution_program() -> ArgumentParser:
def create_download_providers_program() -> ArgumentParser:
program = ArgumentParser(add_help = False)
download_providers = list(facefusion.choices.download_provider_set.keys())
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')
group_download.add_argument('--download-providers', help = wording.get('help.download_providers').format(choices = ', '.join(download_providers)), default = config.get_str_list('download.download_providers', 'github'), choices = download_providers, nargs = '+', metavar = 'DOWNLOAD_PROVIDERS')
job_store.register_job_keys([ 'download_providers' ])
return program
@ -210,7 +212,7 @@ def create_download_providers_program() -> ArgumentParser:
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))
group_download.add_argument('--download-scope', help = wording.get('help.download_scope'), default = config.get_str_value('download.download_scope', 'lite'), choices = facefusion.choices.download_scopes)
job_store.register_job_keys([ 'download_scope' ])
return program
@ -226,8 +228,9 @@ def create_memory_program() -> ArgumentParser:
def create_misc_program() -> ArgumentParser:
program = ArgumentParser(add_help = False)
log_level_keys = list(facefusion.choices.log_level_set.keys())
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 = list(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 = log_level_keys)
job_store.register_job_keys([ 'log_level' ])
return program

12
facefusion/typing.py
View File

@ -112,9 +112,9 @@ ModelOptions = Dict[str, Any]
ModelSet = Dict[str, ModelOptions]
ModelInitializer = NDArray[Any]
ExecutionProviderKey = Literal['cpu', 'coreml', 'cuda', 'directml', 'openvino', 'rocm', 'tensorrt']
ExecutionProvider = Literal['cpu', 'coreml', 'cuda', 'directml', 'openvino', 'rocm', 'tensorrt']
ExecutionProviderValue = Literal['CPUExecutionProvider', 'CoreMLExecutionProvider', 'CUDAExecutionProvider', 'DmlExecutionProvider', 'OpenVINOExecutionProvider', 'ROCMExecutionProvider', 'TensorrtExecutionProvider']
ExecutionProviderSet = Dict[ExecutionProviderKey, ExecutionProviderValue]
ExecutionProviderSet = Dict[ExecutionProvider, ExecutionProviderValue]
ValueAndUnit = TypedDict('ValueAndUnit',
{
'value' : int,
@ -155,8 +155,8 @@ ExecutionDevice = TypedDict('ExecutionDevice',
'utilization' : ExecutionDeviceUtilization
})
DownloadProviderKey = Literal['github', 'huggingface']
DownloadProviderSet = Dict[DownloadProviderKey, str]
DownloadProvider = Literal['github', 'huggingface']
DownloadProviderSet = Dict[DownloadProvider, str]
DownloadScope = Literal['lite', 'full']
Download = TypedDict('Download',
{
@ -314,10 +314,10 @@ State = TypedDict('State',
'ui_layouts' : List[str],
'ui_workflow' : UiWorkflow,
'execution_device_id' : str,
'execution_providers' : List[ExecutionProviderKey],
'execution_providers' : List[ExecutionProvider],
'execution_thread_count' : int,
'execution_queue_count' : int,
'download_providers' : List[DownloadProviderKey],
'download_providers' : List[DownloadProvider],
'download_scope' : DownloadScope,
'video_memory_strategy' : VideoMemoryStrategy,
'system_memory_limit' : int,

10
facefusion/uis/components/download.py
View File

@ -2,11 +2,11 @@ from typing import List, Optional
import gradio
import facefusion.choices
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
from facefusion.typing import DownloadProvider
DOWNLOAD_PROVIDERS_CHECKBOX_GROUP : Optional[gradio.CheckboxGroup] = None
@ -16,7 +16,7 @@ def render() -> None:
DOWNLOAD_PROVIDERS_CHECKBOX_GROUP = gradio.CheckboxGroup(
label = wording.get('uis.download_providers_checkbox_group'),
choices = list(download_provider_set.keys()),
choices = facefusion.choices.download_providers,
value = state_manager.get_item('download_providers')
)
@ -25,7 +25,7 @@ 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:
def update_download_providers(download_providers : List[DownloadProvider]) -> gradio.CheckboxGroup:
common_modules =\
[
content_analyser,
@ -43,6 +43,6 @@ def update_download_providers(download_providers : List[DownloadProviderKey]) ->
if hasattr(module, 'create_static_model_set'):
module.create_static_model_set.cache_clear()
download_providers = download_providers or list(download_provider_set.keys())
download_providers = download_providers or facefusion.choices.download_providers
state_manager.set_item('download_providers', download_providers)
return gradio.CheckboxGroup(value = state_manager.get_item('download_providers'))

10
facefusion/uis/components/execution.py
View File

@ -3,10 +3,10 @@ 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_set
from facefusion.execution import get_available_execution_providers
from facefusion.filesystem import list_directory
from facefusion.processors.core import get_processors_modules
from facefusion.typing import ExecutionProviderKey
from facefusion.typing import ExecutionProvider
EXECUTION_PROVIDERS_CHECKBOX_GROUP : Optional[gradio.CheckboxGroup] = None
@ -16,7 +16,7 @@ def render() -> None:
EXECUTION_PROVIDERS_CHECKBOX_GROUP = gradio.CheckboxGroup(
label = wording.get('uis.execution_providers_checkbox_group'),
choices = list(get_execution_provider_set().keys()),
choices = get_available_execution_providers(),
value = state_manager.get_item('execution_providers')
)
@ -25,7 +25,7 @@ def listen() -> None:
EXECUTION_PROVIDERS_CHECKBOX_GROUP.change(update_execution_providers, inputs = EXECUTION_PROVIDERS_CHECKBOX_GROUP, outputs = EXECUTION_PROVIDERS_CHECKBOX_GROUP)
def update_execution_providers(execution_providers : List[ExecutionProviderKey]) -> gradio.CheckboxGroup:
def update_execution_providers(execution_providers : List[ExecutionProvider]) -> gradio.CheckboxGroup:
common_modules =\
[
content_analyser,
@ -43,6 +43,6 @@ def update_execution_providers(execution_providers : List[ExecutionProviderKey])
if hasattr(module, 'clear_inference_pool'):
module.clear_inference_pool()
execution_providers = execution_providers or list(get_execution_provider_set())
execution_providers = execution_providers or get_available_execution_providers()
state_manager.set_item('execution_providers', execution_providers)
return gradio.CheckboxGroup(value = state_manager.get_item('execution_providers'))

2
facefusion/uis/components/face_detector.py
View File

@ -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 = list(facefusion.choices.face_detector_set.keys()),
choices = facefusion.choices.face_detector_models,
value = state_manager.get_item('face_detector_model')
)
FACE_DETECTOR_SIZE_DROPDOWN = gradio.Dropdown(**face_detector_size_dropdown_options)

2
facefusion/uis/components/face_swapper_options.py
View File

@ -20,7 +20,7 @@ def render() -> None:
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 = list(processors_choices.face_swapper_set.keys()),
choices = processors_choices.face_swapper_models,
value = state_manager.get_item('face_swapper_model'),
visible = has_face_swapper
)

4
facefusion/uis/components/terminal.py
View File

@ -7,8 +7,8 @@ from typing import Optional
import gradio
from tqdm import tqdm
import facefusion.choices
from facefusion import logger, state_manager, wording
from facefusion.choices import log_level_set
from facefusion.typing import LogLevel
LOG_LEVEL_DROPDOWN : Optional[gradio.Dropdown] = None
@ -24,7 +24,7 @@ def render() -> None:
LOG_LEVEL_DROPDOWN = gradio.Dropdown(
label = wording.get('uis.log_level_dropdown'),
choices = list(log_level_set.keys()),
choices = facefusion.choices.log_levels,
value = state_manager.get_item('log_level')
)
TERMINAL_TEXTBOX = gradio.Textbox(

12
facefusion/vision.py
View File

@ -5,7 +5,7 @@ import cv2
import numpy
from cv2.typing import Size
from facefusion.choices import image_template_sizes, video_template_sizes
import facefusion.choices
from facefusion.common_helper import is_windows
from facefusion.filesystem import is_image, is_video, sanitize_path_for_windows
from facefusion.typing import Duration, Fps, Orientation, Resolution, VisionFrame
@ -64,8 +64,8 @@ def create_image_resolutions(resolution : Resolution) -> List[str]:
if resolution:
width, height = resolution
temp_resolutions.append(normalize_resolution(resolution))
for template_size in image_template_sizes:
temp_resolutions.append(normalize_resolution((width * template_size, height * template_size)))
for image_template_size in facefusion.choices.image_template_sizes:
temp_resolutions.append(normalize_resolution((width * image_template_size, height * image_template_size)))
temp_resolutions = sorted(set(temp_resolutions))
for temp_resolution in temp_resolutions:
resolutions.append(pack_resolution(temp_resolution))
@ -155,11 +155,11 @@ def create_video_resolutions(resolution : Resolution) -> List[str]:
if resolution:
width, height = resolution
temp_resolutions.append(normalize_resolution(resolution))
for template_size in video_template_sizes:
for video_template_size in facefusion.choices.video_template_sizes:
if width > height:
temp_resolutions.append(normalize_resolution((template_size * width / height, template_size)))
temp_resolutions.append(normalize_resolution((video_template_size * width / height, video_template_size)))
else:
temp_resolutions.append(normalize_resolution((template_size, template_size * height / width)))
temp_resolutions.append(normalize_resolution((video_template_size, video_template_size * height / width)))
temp_resolutions = sorted(set(temp_resolutions))
for temp_resolution in temp_resolutions:
resolutions.append(pack_resolution(temp_resolution))

6
tests/test_execution.py
View File

@ -1,8 +1,8 @@
from facefusion.execution import create_execution_providers, get_execution_provider_set, has_execution_provider
from facefusion.execution import create_inference_execution_providers, get_available_execution_providers, has_execution_provider
def test_get_execution_provider_set() -> None:
assert 'cpu' in get_execution_provider_set().keys()
assert 'cpu' in get_available_execution_providers()
def test_has_execution_provider() -> None:
@ -20,4 +20,4 @@ def test_multiple_execution_providers() -> None:
'CPUExecutionProvider'
]
assert create_execution_providers('1', [ 'cpu', 'cuda' ]) == execution_providers
assert create_inference_execution_providers('1', [ 'cpu', 'cuda' ]) == execution_providers