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Use 255.0 everywhere

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henryruhs
2025-01-18 15:00:57 +01:00
parent 2f66bde116
commit 330f86a4e4
3 changed files with 4 additions and 4 deletions
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2
facefusion/face_classifier.py
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@@ -67,7 +67,7 @@ def classify_face(temp_vision_frame : VisionFrame, face_landmark_5 : FaceLandmar
model_mean = get_model_options().get('mean') model_mean = get_model_options().get('mean')
model_standard_deviation = get_model_options().get('standard_deviation') model_standard_deviation = get_model_options().get('standard_deviation')
crop_vision_frame, _ = warp_face_by_face_landmark_5(temp_vision_frame, face_landmark_5, model_template, model_size) crop_vision_frame, _ = warp_face_by_face_landmark_5(temp_vision_frame, face_landmark_5, model_template, model_size)
crop_vision_frame = crop_vision_frame.astype(numpy.float32)[:, :, ::-1] / 255 crop_vision_frame = crop_vision_frame.astype(numpy.float32)[:, :, ::-1] / 255.0
crop_vision_frame -= model_mean crop_vision_frame -= model_mean
crop_vision_frame /= model_standard_deviation crop_vision_frame /= model_standard_deviation
crop_vision_frame = crop_vision_frame.transpose(2, 0, 1) crop_vision_frame = crop_vision_frame.transpose(2, 0, 1)

4
facefusion/face_masker.py
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@@ -171,7 +171,7 @@ def create_occlusion_mask(crop_vision_frame : VisionFrame) -> Mask:
face_occluder_model = state_manager.get_item('face_occluder_model') face_occluder_model = state_manager.get_item('face_occluder_model')
model_size = create_static_model_set('full').get(face_occluder_model).get('size') model_size = create_static_model_set('full').get(face_occluder_model).get('size')
prepare_vision_frame = cv2.resize(crop_vision_frame, model_size) prepare_vision_frame = cv2.resize(crop_vision_frame, model_size)
prepare_vision_frame = numpy.expand_dims(prepare_vision_frame, axis = 0).astype(numpy.float32) / 255 prepare_vision_frame = numpy.expand_dims(prepare_vision_frame, axis = 0).astype(numpy.float32) / 255.0
prepare_vision_frame = prepare_vision_frame.transpose(0, 1, 2, 3) prepare_vision_frame = prepare_vision_frame.transpose(0, 1, 2, 3)
occlusion_mask = forward_occlude_face(prepare_vision_frame) occlusion_mask = forward_occlude_face(prepare_vision_frame)
occlusion_mask = occlusion_mask.transpose(0, 1, 2).clip(0, 1).astype(numpy.float32) occlusion_mask = occlusion_mask.transpose(0, 1, 2).clip(0, 1).astype(numpy.float32)
@@ -184,7 +184,7 @@ def create_region_mask(crop_vision_frame : VisionFrame, face_mask_regions : List
face_parser_model = state_manager.get_item('face_parser_model') face_parser_model = state_manager.get_item('face_parser_model')
model_size = create_static_model_set('full').get(face_parser_model).get('size') model_size = create_static_model_set('full').get(face_parser_model).get('size')
prepare_vision_frame = cv2.resize(crop_vision_frame, model_size) prepare_vision_frame = cv2.resize(crop_vision_frame, model_size)
prepare_vision_frame = prepare_vision_frame[:, :, ::-1].astype(numpy.float32) / 255 prepare_vision_frame = prepare_vision_frame[:, :, ::-1].astype(numpy.float32) / 255.0
prepare_vision_frame = numpy.subtract(prepare_vision_frame, numpy.array([ 0.485, 0.456, 0.406 ]).astype(numpy.float32)) prepare_vision_frame = numpy.subtract(prepare_vision_frame, numpy.array([ 0.485, 0.456, 0.406 ]).astype(numpy.float32))
prepare_vision_frame = numpy.divide(prepare_vision_frame, numpy.array([ 0.229, 0.224, 0.225 ]).astype(numpy.float32)) prepare_vision_frame = numpy.divide(prepare_vision_frame, numpy.array([ 0.229, 0.224, 0.225 ]).astype(numpy.float32))
prepare_vision_frame = numpy.expand_dims(prepare_vision_frame, axis = 0) prepare_vision_frame = numpy.expand_dims(prepare_vision_frame, axis = 0)

2
facefusion/processors/modules/frame_enhancer.py
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@@ -479,7 +479,7 @@ def forward(tile_vision_frame : VisionFrame) -> VisionFrame:
def prepare_tile_frame(vision_tile_frame : VisionFrame) -> VisionFrame: def prepare_tile_frame(vision_tile_frame : VisionFrame) -> VisionFrame:
vision_tile_frame = numpy.expand_dims(vision_tile_frame[:, :, ::-1], axis = 0) vision_tile_frame = numpy.expand_dims(vision_tile_frame[:, :, ::-1], axis = 0)
vision_tile_frame = vision_tile_frame.transpose(0, 3, 1, 2) vision_tile_frame = vision_tile_frame.transpose(0, 3, 1, 2)
vision_tile_frame = vision_tile_frame.astype(numpy.float32) / 255 vision_tile_frame = vision_tile_frame.astype(numpy.float32) / 255.0
return vision_tile_frame return vision_tile_frame