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cosmetics changes on lip syncer

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This commit is contained in:
henryruhs
2025-06-17 19:18:46 +02:00
parent d1385fed0d
commit b76ca08dea
1 changed files with 14 additions and 14 deletions
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28
facefusion/processors/modules/lip_syncer.py
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@@ -201,19 +201,6 @@ def sync_lip(target_face : Face, temp_audio_frame : AudioFrame, temp_vision_fram
return paste_vision_frame
def forward_wav2lip(temp_audio_frame : AudioFrame, area_vision_frame : VisionFrame) -> VisionFrame:
lip_syncer = get_inference_pool().get('lip_syncer')
with conditional_thread_semaphore():
area_vision_frame = lip_syncer.run(None,
{
'source': temp_audio_frame,
'target': area_vision_frame
})[0]
return area_vision_frame
def forward_edtalk(temp_audio_frame : AudioFrame, crop_vision_frame : VisionFrame, lip_syncer_weight : LipSyncerWeight) -> VisionFrame:
lip_syncer = get_inference_pool().get('lip_syncer')
@@ -228,6 +215,19 @@ def forward_edtalk(temp_audio_frame : AudioFrame, crop_vision_frame : VisionFram
return crop_vision_frame
def forward_wav2lip(temp_audio_frame : AudioFrame, area_vision_frame : VisionFrame) -> VisionFrame:
lip_syncer = get_inference_pool().get('lip_syncer')
with conditional_thread_semaphore():
area_vision_frame = lip_syncer.run(None,
{
'source': temp_audio_frame,
'target': area_vision_frame
})[0]
return area_vision_frame
def prepare_audio_frame(temp_audio_frame : AudioFrame) -> AudioFrame:
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
@@ -242,7 +242,7 @@ def prepare_crop_frame(crop_vision_frame : VisionFrame) -> VisionFrame:
model_size = get_model_options().get('size')
if model_type == 'edtalk':
crop_vision_frame = cv2.resize(crop_vision_frame, (256, 256), interpolation = cv2.INTER_AREA)
crop_vision_frame = cv2.resize(crop_vision_frame, model_size, interpolation = cv2.INTER_AREA)
crop_vision_frame = crop_vision_frame[:, :, ::-1] / 255.0
crop_vision_frame = numpy.expand_dims(crop_vision_frame.transpose(2, 0, 1), axis = 0).astype(numpy.float32)
if model_type == 'wav2lip':