mirrors/facefusion
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

limit expression restorer

Browse Source
This commit is contained in:
harisreedhar 2024-09-19 12:13:00 +05:30
parent 9b4c0c3da7
commit 1d36e85b85
2 changed files with 2 additions and 2 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
facefusion/processors/choices.py
View File

@ -26,7 +26,7 @@ frame_enhancer_models : List[FrameEnhancerModel] = [ 'clear_reality_x4', 'lsdir_
lip_syncer_models : List[LipSyncerModel] = [ 'wav2lip', 'wav2lip_gan' ]
age_modifier_direction_range : Sequence[int] = create_int_range(-100, 100, 1)
expression_restorer_factor_range : Sequence[int] = create_int_range(0, 200, 1)
expression_restorer_factor_range : Sequence[int] = create_int_range(0, 120, 1)
face_editor_eyebrow_direction_range : Sequence[float] = create_float_range(-1.0, 1.0, 0.05)
face_editor_eye_gaze_horizontal_range : Sequence[float] = create_float_range(-1.0, 1.0, 0.05)
face_editor_eye_gaze_vertical_range : Sequence[float] = create_float_range(-1.0, 1.0, 0.05)

2
facefusion/processors/modules/expression_restorer.py
View File

@ -137,7 +137,7 @@ def post_process() -> None:
def restore_expression(source_vision_frame : VisionFrame, target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame:
model_template = get_model_options().get('template')
model_size = get_model_options().get('size')
expression_restorer_factor = float(numpy.interp(float(state_manager.get_item('expression_restorer_factor')), [ 0, 200 ], [ 0, 2 ]))
expression_restorer_factor = float(numpy.interp(float(state_manager.get_item('expression_restorer_factor')), [ 0, 120 ], [ 0, 1.2 ]))
source_vision_frame = cv2.resize(source_vision_frame, temp_vision_frame.shape[:2][::-1])
source_crop_vision_frame, _ = warp_face_by_face_landmark_5(source_vision_frame, target_face.landmark_set.get('5/68'), model_template, model_size)
target_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)