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Fix spacing

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This commit is contained in:
henryruhs
2025-06-12 17:36:48 +02:00
parent 75344fa0dd
commit 4150cda64e
1 changed files with 10 additions and 11 deletions
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21
facefusion/processors/modules/lip_syncer.py
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@@ -184,35 +184,34 @@ def sync_lip(target_face : Face, temp_audio_frame : AudioFrame, temp_vision_fram
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'):
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(face_landmark_68, [ 'lower-face' ])
crop_masks.append(area_mask)
bounding_box = create_bounding_box(face_landmark_68)
bounding_box = resize_bounding_box(bounding_box, 4 / 3)
close_vision_frame, close_matrix = warp_face_by_bounding_box(crop_vision_frame, bounding_box, model_size)
close_vision_frame = prepare_crop_frame(close_vision_frame)
close_vision_frame = forward_wav2lip(temp_audio_frame, close_vision_frame)
close_vision_frame = normalize_crop_frame(close_vision_frame)
crop_vision_frame = cv2.warpAffine(close_vision_frame, cv2.invertAffineTransform(close_matrix), (512, 512), borderMode = cv2.BORDER_REPLICATE)
temp_vision_frame, temp_matrix = warp_face_by_bounding_box(crop_vision_frame, bounding_box, model_size)
temp_vision_frame = prepare_crop_frame(temp_vision_frame)
temp_vision_frame = forward_wav2lip(temp_audio_frame, temp_vision_frame)
temp_vision_frame = normalize_crop_frame(temp_vision_frame)
crop_vision_frame = cv2.warpAffine(temp_vision_frame, cv2.invertAffineTransform(temp_matrix), (512, 512), borderMode = cv2.BORDER_REPLICATE)
crop_mask = numpy.minimum.reduce(crop_masks)
paste_vision_frame = paste_back(temp_vision_frame, crop_vision_frame, crop_mask, affine_matrix)
return paste_vision_frame
def forward_wav2lip(temp_audio_frame : AudioFrame, close_vision_frame : VisionFrame) -> VisionFrame:
def forward_wav2lip(temp_audio_frame : AudioFrame, crop_vision_frame : VisionFrame) -> VisionFrame:
lip_syncer = get_inference_pool().get('lip_syncer')
with conditional_thread_semaphore():
close_vision_frame = lip_syncer.run(None,
crop_vision_frame = lip_syncer.run(None,
{
'source': temp_audio_frame,
'target': close_vision_frame
'target': crop_vision_frame
})[0]
return close_vision_frame
return crop_vision_frame
def forward_edtalk(temp_audio_frame : AudioFrame, crop_vision_frame : VisionFrame, lip_syncer_weight : LipSyncerWeight) -> VisionFrame:
@@ -272,7 +271,7 @@ def normalize_crop_frame(crop_vision_frame : VisionFrame) -> VisionFrame:
if model_type == 'edtalk':
crop_vision_frame = crop_vision_frame[:, :, ::-1]
crop_vision_frame = cv2.resize(crop_vision_frame, (512, 512), interpolation = cv2.INTER_CUBIC)
crop_vision_frame = cv2.resize(crop_vision_frame, (512, 512), interpolation=cv2.INTER_CUBIC)
return crop_vision_frame