change enhance

roop/processors/frame/face_enhancer.py

@@ -17,88 +17,88 @@ NAME = 'ROOP.FACE-ENHANCER'
 
 
 def get_face_enhancer() -> Any:
-    global FACE_ENHANCER
+global FACE_ENHANCER
 
-    with THREAD_LOCK:
-        if FACE_ENHANCER is None:
-            model_path = resolve_relative_path('../models/GFPGANv1.4.pth')
-            # todo: set models path -> https://github.com/TencentARC/GFPGAN/issues/399
-            FACE_ENHANCER = GFPGANer(model_path=model_path, upscale=1, device=get_device())
-    return FACE_ENHANCER
+with THREAD_LOCK:
+if FACE_ENHANCER is None:
+model_path = resolve_relative_path('../models/GFPGANv1.4.pth')
+# todo: set models path -> https://github.com/TencentARC/GFPGAN/issues/399
+FACE_ENHANCER = GFPGANer(model_path=model_path, upscale=1, device=get_device())
+return FACE_ENHANCER
 
 
 def get_device() -> str:
-    if 'CUDAExecutionProvider' in roop.globals.execution_providers:
-        return 'cuda'
-    if 'CoreMLExecutionProvider' in roop.globals.execution_providers:
-        return 'mps'
-    return 'cpu'
+if 'CUDAExecutionProvider' in roop.globals.execution_providers:
+return 'cuda'
+if 'CoreMLExecutionProvider' in roop.globals.execution_providers:
+return 'mps'
+return 'cpu'
 
 
 def clear_face_enhancer() -> None:
-    global FACE_ENHANCER
+global FACE_ENHANCER
 
-    FACE_ENHANCER = None
+FACE_ENHANCER = None
 
 
 def pre_check() -> bool:
-    download_directory_path = resolve_relative_path('../models')
-    conditional_download(download_directory_path, ['https://github.com/TencentARC/GFPGAN/releases/download/v1.3.8/GFPGANv1.4.pth'])
-    return True
+download_directory_path = resolve_relative_path('../models')
+conditional_download(download_directory_path, ['https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/GFPGANv1.4.pth'])
+return True
 
 
 def pre_start() -> bool:
-    if not is_image(roop.globals.target_path) and not is_video(roop.globals.target_path):
-        update_status('Select an image or video for target path.', NAME)
-        return False
-    return True
+if not is_image(roop.globals.target_path) and not is_video(roop.globals.target_path):
+update_status('Select an image or video for target path.', NAME)
+return False
+return True
 
 
 def post_process() -> None:
-    clear_face_enhancer()
+clear_face_enhancer()
 
 
 def enhance_face(target_face: Face, temp_frame: Frame) -> Frame:
-    start_x, start_y, end_x, end_y = map(int, target_face['bbox'])
-    padding_x = int((end_x - start_x) * 0.5)
-    padding_y = int((end_y - start_y) * 0.5)
-    start_x = max(0, start_x - padding_x)
-    start_y = max(0, start_y - padding_y)
-    end_x = max(0, end_x + padding_x)
-    end_y = max(0, end_y + padding_y)
-    temp_face = temp_frame[start_y:end_y, start_x:end_x]
-    if temp_face.size:
-        with THREAD_SEMAPHORE:
-            _, _, temp_face = get_face_enhancer().enhance(
-                temp_face,
-                paste_back=True
-            )
-        temp_frame[start_y:end_y, start_x:end_x] = temp_face
-    return temp_frame
+start_x, start_y, end_x, end_y = map(int, target_face['bbox'])
+padding_x = int((end_x - start_x) * 0.5)
+padding_y = int((end_y - start_y) * 0.5)
+start_x = max(0, start_x - padding_x)
+start_y = max(0, start_y - padding_y)
+end_x = max(0, end_x + padding_x)
+end_y = max(0, end_y + padding_y)
+temp_face = temp_frame[start_y:end_y, start_x:end_x]
+if temp_face.size:
+with THREAD_SEMAPHORE:
+_, _, temp_face = get_face_enhancer().enhance(
+temp_face,
+paste_back=True
+)
+temp_frame[start_y:end_y, start_x:end_x] = temp_face
+return temp_frame
 
 
 def process_frame(source_face: Face, reference_face: Face, temp_frame: Frame) -> Frame:
-    many_faces = get_many_faces(temp_frame)
-    if many_faces:
-        for target_face in many_faces:
-            temp_frame = enhance_face(target_face, temp_frame)
-    return temp_frame
+many_faces = get_many_faces(temp_frame)
+if many_faces:
+for target_face in many_faces:
+temp_frame = enhance_face(target_face, temp_frame)
+return temp_frame
 
 
 def process_frames(source_path: str, temp_frame_paths: List[str], update: Callable[[], None]) -> None:
-    for temp_frame_path in temp_frame_paths:
-        temp_frame = cv2.imread(temp_frame_path)
-        result = process_frame(None, None, temp_frame)
-        cv2.imwrite(temp_frame_path, result)
-        if update:
-            update()
+for temp_frame_path in temp_frame_paths:
+temp_frame = cv2.imread(temp_frame_path)
+result = process_frame(None, None, temp_frame)
+cv2.imwrite(temp_frame_path, result)
+if update:
+update()
 
 
 def process_image(source_path: str, target_path: str, output_path: str) -> None:
-    target_frame = cv2.imread(target_path)
-    result = process_frame(None, None, target_frame)
-    cv2.imwrite(output_path, result)
+target_frame = cv2.imread(target_path)
+result = process_frame(None, None, target_frame)
+cv2.imwrite(output_path, result)
 
 
 def process_video(source_path: str, temp_frame_paths: List[str]) -> None:
-    roop.processors.frame.core.process_video(None, temp_frame_paths, process_frames)
+roop.processors.frame.core.process_video(None, temp_frame_paths, process_frames)