changes
This commit is contained in:
harisreedhar
henryruhs
parent
00c7c6a6ba
commit
518e00ff22
@ -1,9 +1,10 @@
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from typing import List, Sequence
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from facefusion.common_helper import create_float_range, create_int_range
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from facefusion.processors.typing import AgeModifierModel, ExpressionRestorerModel, FaceDebuggerItem, FaceEditorModel, FaceEnhancerModel, FaceSwapperSet, FrameColorizerModel, FrameEnhancerModel, LipSyncerModel
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from facefusion.processors.typing import AgeModifierModel, DeepSwapperModel, ExpressionRestorerModel, FaceDebuggerItem, FaceEditorModel, FaceEnhancerModel, FaceSwapperSet, FrameColorizerModel, FrameEnhancerModel, LipSyncerModel
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age_modifier_models : List[AgeModifierModel] = [ 'styleganex_age' ]
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deep_swapper_models : List[DeepSwapperModel] = [ 'jackie_chan' ]
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expression_restorer_models : List[ExpressionRestorerModel] = [ 'live_portrait' ]
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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' ]
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face_editor_models : List[FaceEditorModel] = [ 'live_portrait' ]
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244
facefusion/processors/modules/deep_swapper.py
Executable file
244
facefusion/processors/modules/deep_swapper.py
Executable file
@ -0,0 +1,244 @@
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from argparse import ArgumentParser
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from typing import List, Tuple
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import cv2
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import numpy
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import facefusion.jobs.job_manager
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import facefusion.jobs.job_store
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import facefusion.processors.core as processors
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from facefusion import config, content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer, inference_manager, logger, process_manager, state_manager, wording
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from facefusion.download import conditional_download_hashes, conditional_download_sources
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from facefusion.face_analyser import get_many_faces, get_one_face
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from facefusion.face_helper import paste_back, warp_face_by_face_landmark_5
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from facefusion.face_masker import create_occlusion_mask, create_static_box_mask
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from facefusion.face_selector import find_similar_faces, sort_and_filter_faces
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from facefusion.face_store import get_reference_faces
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from facefusion.filesystem import in_directory, is_image, is_video, resolve_relative_path, same_file_extension
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from facefusion.processors import choices as processors_choices
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from facefusion.processors.typing import DeepSwapperInputs
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from facefusion.program_helper import find_argument_group
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from facefusion.thread_helper import thread_semaphore
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from facefusion.typing import ApplyStateItem, Args, Face, InferencePool, Mask, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
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from facefusion.vision import read_image, read_static_image, write_image
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MODEL_SET : ModelSet =\
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{
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'jackie_chan':
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{
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'hashes':
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{
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'deep_swapper':
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{
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'url': 'https://huggingface.co/bluefoxcreation/DFM/resolve/main/Jackie_Chan.hash',
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'path': resolve_relative_path('../.assets/models/Jackie_Chan.hash')
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}
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},
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'sources':
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{
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'deep_swapper':
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{
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'url': 'https://github.com/iperov/DeepFaceLive/releases/download/JACKIE_CHAN/Jackie_Chan.dfm',
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'path': resolve_relative_path('../.assets/models/Jackie_Chan.dfm')
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}
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},
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'template': 'arcface_128_v2',
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'size': (224, 224)
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}
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}
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def get_inference_pool() -> InferencePool:
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model_sources = get_model_options().get('sources')
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model_context = __name__ + '.' + state_manager.get_item('deep_swapper_model')
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return inference_manager.get_inference_pool(model_context, model_sources)
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def clear_inference_pool() -> None:
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model_context = __name__ + '.' + state_manager.get_item('deep_swapper_model')
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inference_manager.clear_inference_pool(model_context)
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def get_model_options() -> ModelOptions:
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deep_swapper_model = state_manager.get_item('deep_swapper_model')
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return MODEL_SET.get(deep_swapper_model)
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def register_args(program : ArgumentParser) -> None:
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group_processors = find_argument_group(program, 'processors')
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if group_processors:
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group_processors.add_argument('--deep-swapper-model', help = wording.get('help.deep_swapper_model'), default = config.get_str_value('processors.deep_swapper_model', 'jackie_chan'), choices = processors_choices.deep_swapper_models)
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facefusion.jobs.job_store.register_step_keys([ 'deep_swapper_model' ])
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def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
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apply_state_item('deep_swapper_model', args.get('deep_swapper_model'))
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def pre_check() -> bool:
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download_directory_path = resolve_relative_path('../.assets/models')
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model_hashes = get_model_options().get('hashes')
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model_sources = get_model_options().get('sources')
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return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources)
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def pre_process(mode : ProcessMode) -> bool:
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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')):
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logger.error(wording.get('choose_image_or_video_target') + wording.get('exclamation_mark'), __name__)
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return False
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if mode == 'output' and not in_directory(state_manager.get_item('output_path')):
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logger.error(wording.get('specify_image_or_video_output') + wording.get('exclamation_mark'), __name__)
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return False
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if mode == 'output' and not same_file_extension([ state_manager.get_item('target_path'), state_manager.get_item('output_path') ]):
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logger.error(wording.get('match_target_and_output_extension') + wording.get('exclamation_mark'), __name__)
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return False
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return True
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def post_process() -> None:
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read_static_image.cache_clear()
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if state_manager.get_item('video_memory_strategy') in [ 'strict', 'moderate' ]:
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clear_inference_pool()
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if state_manager.get_item('video_memory_strategy') == 'strict':
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content_analyser.clear_inference_pool()
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face_classifier.clear_inference_pool()
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face_detector.clear_inference_pool()
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face_landmarker.clear_inference_pool()
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face_masker.clear_inference_pool()
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face_recognizer.clear_inference_pool()
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def swap_face(target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame:
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model_template = get_model_options().get('template')
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model_size = get_model_options().get('size')
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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)
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crop_vision_frame_raw = crop_vision_frame.copy()
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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'))
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crop_masks =\
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[
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box_mask
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]
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if 'occlusion' in state_manager.get_item('face_mask_types'):
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occlusion_mask = create_occlusion_mask(crop_vision_frame)
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crop_masks.append(occlusion_mask)
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crop_vision_frame = prepare_crop_frame(crop_vision_frame)
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crop_vision_frame, crop_source_mask, crop_target_mask = forward(crop_vision_frame)
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crop_vision_frame = normalize_crop_frame(crop_vision_frame)
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crop_vision_frame = match_frame_color_with_mask(crop_vision_frame_raw, crop_vision_frame, crop_source_mask, crop_target_mask)
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crop_masks.append(feather_crop_mask(crop_source_mask))
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crop_masks.append(feather_crop_mask(crop_target_mask))
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crop_mask = numpy.minimum.reduce(crop_masks).clip(0, 1)
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paste_vision_frame = paste_back(temp_vision_frame, crop_vision_frame, crop_mask, affine_matrix)
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return paste_vision_frame
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def forward(crop_vision_frame : VisionFrame) -> Tuple[VisionFrame, Mask, Mask]:
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deep_swapper = get_inference_pool().get('deep_swapper')
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deep_swapper_inputs = {}
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for deep_swapper_input in deep_swapper.get_inputs():
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if deep_swapper_input.name == 'in_face:0':
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deep_swapper_inputs[deep_swapper_input.name] = crop_vision_frame
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if deep_swapper_input.name == 'morph_value:0':
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morph_value = numpy.array([ 1 ]).astype(numpy.float32)
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deep_swapper_inputs[deep_swapper_input.name] = morph_value
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with thread_semaphore():
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crop_target_mask, crop_vision_frame, crop_source_mask = deep_swapper.run(None, deep_swapper_inputs)
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return crop_vision_frame[0], crop_source_mask[0], crop_target_mask[0]
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def prepare_crop_frame(crop_vision_frame : VisionFrame) -> VisionFrame:
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crop_vision_frame = cv2.addWeighted(crop_vision_frame, 1.5, cv2.GaussianBlur(crop_vision_frame, (0, 0), 2), -0.5, 0)
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crop_vision_frame = crop_vision_frame / 255.0
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crop_vision_frame = numpy.expand_dims(crop_vision_frame, axis = 0).astype(numpy.float32)
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return crop_vision_frame
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def normalize_crop_frame(crop_vision_frame : VisionFrame) -> VisionFrame:
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crop_vision_frame = (crop_vision_frame * 255.0).clip(0, 255)
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crop_vision_frame = crop_vision_frame.astype(numpy.uint8)
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return crop_vision_frame
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def feather_crop_mask(crop_source_mask : Mask) -> Mask:
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model_size = get_model_options().get('size')
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crop_mask = crop_source_mask.reshape(model_size).clip(0, 1)
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crop_mask = cv2.erode(crop_mask, numpy.ones((7, 7), numpy.uint8), iterations = 1)
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crop_mask = cv2.GaussianBlur(crop_mask, (15, 15), 0)
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return crop_mask
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def match_frame_color_with_mask(source_vision_frame : VisionFrame, target_vision_frame : VisionFrame, source_mask : Mask, target_mask : Mask) -> VisionFrame:
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target_lab_frame = cv2.cvtColor(target_vision_frame, cv2.COLOR_BGR2LAB).astype(numpy.float32) / 255
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source_lab_frame = cv2.cvtColor(source_vision_frame, cv2.COLOR_BGR2LAB).astype(numpy.float32) / 255
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source_mask = (source_mask > 0.5).astype(numpy.float32)
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target_mask = (target_mask > 0.5).astype(numpy.float32)
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target_lab_filter = target_lab_frame * cv2.cvtColor(source_mask, cv2.COLOR_GRAY2BGR)
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source_lab_filter = source_lab_frame * cv2.cvtColor(target_mask, cv2.COLOR_GRAY2BGR)
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target_lab_frame -= target_lab_filter.mean(axis = ( 0, 1 ))
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target_lab_frame /= target_lab_filter.std(axis = ( 0, 1 )) + 1e-6
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target_lab_frame *= source_lab_filter.std(axis = ( 0, 1 ))
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target_lab_frame += source_lab_filter.mean(axis = ( 0, 1 ))
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target_lab_frame = numpy.multiply(target_lab_frame.clip(0, 1), 255).astype(numpy.uint8)
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target_vision_frame = cv2.cvtColor(target_lab_frame, cv2.COLOR_LAB2BGR)
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return target_vision_frame
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def get_reference_frame(source_face : Face, target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame:
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return swap_face(target_face, temp_vision_frame)
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def process_frame(inputs : DeepSwapperInputs) -> VisionFrame:
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reference_faces = inputs.get('reference_faces')
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target_vision_frame = inputs.get('target_vision_frame')
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many_faces = sort_and_filter_faces(get_many_faces([ target_vision_frame ]))
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if state_manager.get_item('face_selector_mode') == 'many':
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if many_faces:
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for target_face in many_faces:
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target_vision_frame = swap_face(target_face, target_vision_frame)
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if state_manager.get_item('face_selector_mode') == 'one':
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target_face = get_one_face(many_faces)
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if target_face:
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target_vision_frame = swap_face(target_face, target_vision_frame)
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if state_manager.get_item('face_selector_mode') == 'reference':
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similar_faces = find_similar_faces(many_faces, reference_faces, state_manager.get_item('reference_face_distance'))
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if similar_faces:
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for similar_face in similar_faces:
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target_vision_frame = swap_face(similar_face, target_vision_frame)
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return target_vision_frame
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def process_frames(source_path : List[str], queue_payloads : List[QueuePayload], update_progress : UpdateProgress) -> None:
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reference_faces = get_reference_faces() if 'reference' in state_manager.get_item('face_selector_mode') else None
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for queue_payload in process_manager.manage(queue_payloads):
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target_vision_path = queue_payload['frame_path']
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target_vision_frame = read_image(target_vision_path)
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output_vision_frame = process_frame(
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{
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'reference_faces': reference_faces,
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'target_vision_frame': target_vision_frame
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})
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write_image(target_vision_path, output_vision_frame)
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update_progress(1)
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def process_image(source_path : str, target_path : str, output_path : str) -> None:
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reference_faces = get_reference_faces() if 'reference' in state_manager.get_item('face_selector_mode') else None
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target_vision_frame = read_static_image(target_path)
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output_vision_frame = process_frame(
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{
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'reference_faces': reference_faces,
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'target_vision_frame': target_vision_frame
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})
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write_image(output_path, output_vision_frame)
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def process_video(source_paths : List[str], temp_frame_paths : List[str]) -> None:
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processors.multi_process_frames(None, temp_frame_paths, process_frames)
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@ -5,6 +5,7 @@ from numpy._typing import NDArray
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from facefusion.typing import AppContext, AudioFrame, Face, FaceSet, VisionFrame
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AgeModifierModel = Literal['styleganex_age']
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DeepSwapperModel = Literal['jackie_chan']
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ExpressionRestorerModel = Literal['live_portrait']
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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']
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FaceEditorModel = Literal['live_portrait']
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@ -21,6 +22,11 @@ AgeModifierInputs = TypedDict('AgeModifierInputs',
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'reference_faces' : FaceSet,
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'target_vision_frame' : VisionFrame
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})
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DeepSwapperInputs = TypedDict('DeepSwapperInputs',
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{
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'reference_faces' : FaceSet,
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'target_vision_frame' : VisionFrame
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})
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ExpressionRestorerInputs = TypedDict('ExpressionRestorerInputs',
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{
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'reference_faces' : FaceSet,
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@ -67,6 +73,7 @@ ProcessorStateKey = Literal\
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[
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'age_modifier_model',
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'age_modifier_direction',
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'deep_swapper_model',
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'expression_restorer_model',
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'expression_restorer_factor',
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'face_debugger_items',
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@ -100,6 +107,7 @@ ProcessorState = TypedDict('ProcessorState',
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{
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'age_modifier_model' : AgeModifierModel,
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'age_modifier_direction' : int,
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'deep_swapper_model' : DeepSwapperModel,
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'expression_restorer_model' : ExpressionRestorerModel,
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'expression_restorer_factor' : int,
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'face_debugger_items' : List[FaceDebuggerItem],
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46
facefusion/uis/components/deep_swapper_options.py
Executable file
46
facefusion/uis/components/deep_swapper_options.py
Executable file
@ -0,0 +1,46 @@
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from typing import List, Optional
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import gradio
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from facefusion import state_manager, wording
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from facefusion.processors import choices as processors_choices
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from facefusion.processors.core import load_processor_module
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from facefusion.processors.typing import FaceEnhancerModel
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from facefusion.uis.core import get_ui_component, register_ui_component
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DEEP_SWAPPER_MODEL_DROPDOWN : Optional[gradio.Dropdown] = None
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def render() -> None:
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global DEEP_SWAPPER_MODEL_DROPDOWN
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DEEP_SWAPPER_MODEL_DROPDOWN = gradio.Dropdown(
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label = wording.get('uis.deep_swapper_model_dropdown'),
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choices = processors_choices.deep_swapper_models,
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value = state_manager.get_item('deep_swapper_model'),
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visible = 'deep_swapper' in state_manager.get_item('processors')
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)
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register_ui_component('deep_swapper_model_dropdown', DEEP_SWAPPER_MODEL_DROPDOWN)
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def listen() -> None:
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DEEP_SWAPPER_MODEL_DROPDOWN.change(update_face_enhancer_model, inputs = DEEP_SWAPPER_MODEL_DROPDOWN, outputs = DEEP_SWAPPER_MODEL_DROPDOWN)
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processors_checkbox_group = get_ui_component('processors_checkbox_group')
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if processors_checkbox_group:
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processors_checkbox_group.change(remote_update, inputs = processors_checkbox_group, outputs = DEEP_SWAPPER_MODEL_DROPDOWN)
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def remote_update(processors : List[str]) -> gradio.Dropdown:
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has_face_enhancer = 'deep_swapper' in processors
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return gradio.Dropdown(visible = has_face_enhancer)
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def update_face_enhancer_model(face_enhancer_model : FaceEnhancerModel) -> gradio.Dropdown:
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deep_swapper_module = load_processor_module('deep_swapper')
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deep_swapper_module.clear_inference_pool()
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state_manager.set_item('deep_swapper_model', face_enhancer_model)
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if deep_swapper_module.pre_check():
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return gradio.Dropdown(value = state_manager.get_item('deep_swapper_model'))
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return gradio.Dropdown()
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@ -142,6 +142,7 @@ def listen() -> None:
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for ui_component in get_ui_components(
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[
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'age_modifier_model_dropdown',
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'deep_swapper_model_dropdown',
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'expression_restorer_model_dropdown',
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'processors_checkbox_group',
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'face_editor_model_dropdown',
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@ -2,7 +2,7 @@ import gradio
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from facefusion import state_manager
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from facefusion.download import conditional_download
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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
|
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from facefusion.uis.components import about, age_modifier_options, benchmark, benchmark_options, deep_swapper_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
|
||||
|
||||
|
||||
def pre_check() -> bool:
|
||||
@ -33,6 +33,8 @@ 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():
|
||||
@ -66,6 +68,7 @@ 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()
|
||||
|
||||
@ -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, 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():
|
||||
@ -79,6 +81,7 @@ 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()
|
||||
|
||||
@ -1,7 +1,7 @@
|
||||
import gradio
|
||||
|
||||
from facefusion import state_manager
|
||||
from facefusion.uis.components import about, age_modifier_options, 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
|
||||
from facefusion.uis.components import about, age_modifier_options, deep_swapper_options, 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:
|
||||
@ -18,6 +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():
|
||||
@ -50,6 +52,7 @@ 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()
|
||||
|
||||
@ -9,6 +9,7 @@ ComponentName = Literal\
|
||||
'age_modifier_model_dropdown',
|
||||
'benchmark_cycles_slider',
|
||||
'benchmark_runs_checkbox_group',
|
||||
'deep_swapper_model_dropdown',
|
||||
'expression_restorer_factor_slider',
|
||||
'expression_restorer_model_dropdown',
|
||||
'face_debugger_items_checkbox_group',
|
||||
|
||||
@ -143,6 +143,7 @@ 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',
|
||||
'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})',
|
||||
@ -226,6 +227,7 @@ WORDING : Dict[str, Any] =\
|
||||
'benchmark_runs_checkbox_group': 'BENCHMARK RUNS',
|
||||
'clear_button': 'CLEAR',
|
||||
'common_options_checkbox_group': 'OPTIONS',
|
||||
'deep_swapper_model_dropdown': 'DEEP SWAPPER MODEL',
|
||||
'execution_providers_checkbox_group': 'EXECUTION PROVIDERS',
|
||||
'execution_queue_count_slider': 'EXECUTION QUEUE COUNT',
|
||||
'execution_thread_count_slider': 'EXECUTION THREAD COUNT',
|
||||
|
||||
Loading…
Reference in New Issue
Block a user