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Fix lip syncer

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This commit is contained in:
henryruhs
2025-06-19 08:41:06 +02:00
parent fc501754cd
commit 6f9997bd31
1 changed files with 8 additions and 4 deletions
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10
facefusion/processors/modules/lip_syncer.py
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@@ -167,7 +167,7 @@ def post_process() -> None:
def sync_lip(target_face : Face, temp_audio_frame : AudioFrame, temp_vision_frame : VisionFrame) -> VisionFrame:
model_name = state_manager.get_item('lip_syncer_model')
model_type = get_model_options().get('type')
model_size = get_model_options().get('size')
temp_audio_frame = prepare_audio_frame(temp_audio_frame)
crop_vision_frame, affine_matrix = warp_face_by_face_landmark_5(temp_vision_frame, target_face.landmark_set.get('5/68'), 'ffhq_512', (512, 512))
@@ -177,14 +177,14 @@ def sync_lip(target_face : Face, temp_audio_frame : AudioFrame, temp_vision_fram
occlusion_mask = create_occlusion_mask(crop_vision_frame)
crop_masks.append(occlusion_mask)
if model_name == 'edtalk_256':
if model_type == 'edtalk':
lip_syncer_weight = numpy.array([ state_manager.get_item('lip_syncer_weight') ]).astype(numpy.float32) * 1.25
box_mask = create_box_mask(crop_vision_frame, state_manager.get_item('face_mask_blur'), state_manager.get_item('face_mask_padding'))
crop_masks.append(box_mask)
crop_vision_frame = prepare_crop_frame(crop_vision_frame)
crop_vision_frame = forward_edtalk(temp_audio_frame, crop_vision_frame, lip_syncer_weight)
crop_vision_frame = normalize_crop_frame(crop_vision_frame)
if model_name.startswith('wav2lip'):
if model_type == 'wav2lip':
face_landmark_68 = cv2.transform(target_face.landmark_set.get('68').reshape(1, -1, 2), affine_matrix).reshape(-1, 2)
area_mask = create_area_mask(crop_vision_frame, face_landmark_68, [ 'lower-face' ])
crop_masks.append(area_mask)
@@ -229,10 +229,14 @@ def forward_wav2lip(temp_audio_frame : AudioFrame, area_vision_frame : VisionFra
def prepare_audio_frame(temp_audio_frame : AudioFrame) -> AudioFrame:
model_type = get_model_options().get('type')
temp_audio_frame = numpy.maximum(numpy.exp(-5 * numpy.log(10)), temp_audio_frame)
temp_audio_frame = numpy.log10(temp_audio_frame) * 1.6 + 3.2
temp_audio_frame = temp_audio_frame.clip(-4, 4).astype(numpy.float32)
if model_type == 'wav2lip':
temp_audio_frame = temp_audio_frame * state_manager.get_item('lip_syncer_weight') * 2.0
temp_audio_frame = numpy.expand_dims(temp_audio_frame, axis = (0, 1))
return temp_audio_frame