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Configuration error
| from typing import Optional, List, Tuple | |
| from functools import lru_cache | |
| import cv2 | |
| import numpy | |
| from cv2.typing import Size | |
| from facefusion.common_helper import is_windows | |
| from facefusion.typing import VisionFrame, Resolution, Fps | |
| from facefusion.choices import image_template_sizes, video_template_sizes | |
| from facefusion.filesystem import is_image, is_video, sanitize_path_for_windows | |
| def read_static_image(image_path : str) -> Optional[VisionFrame]: | |
| return read_image(image_path) | |
| def read_static_images(image_paths : List[str]) -> Optional[List[VisionFrame]]: | |
| frames = [] | |
| if image_paths: | |
| for image_path in image_paths: | |
| frames.append(read_static_image(image_path)) | |
| return frames | |
| def read_image(image_path : str) -> Optional[VisionFrame]: | |
| if is_image(image_path): | |
| if is_windows(): | |
| image_path = sanitize_path_for_windows(image_path) | |
| return cv2.imread(image_path) | |
| return None | |
| def write_image(image_path : str, vision_frame : VisionFrame) -> bool: | |
| if image_path: | |
| if is_windows(): | |
| image_path = sanitize_path_for_windows(image_path) | |
| return cv2.imwrite(image_path, vision_frame) | |
| return False | |
| def detect_image_resolution(image_path : str) -> Optional[Resolution]: | |
| if is_image(image_path): | |
| image = read_image(image_path) | |
| height, width = image.shape[:2] | |
| return width, height | |
| return None | |
| def restrict_image_resolution(image_path : str, resolution : Resolution) -> Resolution: | |
| if is_image(image_path): | |
| image_resolution = detect_image_resolution(image_path) | |
| if image_resolution < resolution: | |
| return image_resolution | |
| return resolution | |
| def create_image_resolutions(resolution : Resolution) -> List[str]: | |
| resolutions = [] | |
| temp_resolutions = [] | |
| if resolution: | |
| width, height = resolution | |
| temp_resolutions.append(normalize_resolution(resolution)) | |
| for template_size in image_template_sizes: | |
| temp_resolutions.append(normalize_resolution((width * template_size, height * template_size))) | |
| temp_resolutions = sorted(set(temp_resolutions)) | |
| for temp_resolution in temp_resolutions: | |
| resolutions.append(pack_resolution(temp_resolution)) | |
| return resolutions | |
| def get_video_frame(video_path : str, frame_number : int = 0) -> Optional[VisionFrame]: | |
| if is_video(video_path): | |
| if is_windows(): | |
| video_path = sanitize_path_for_windows(video_path) | |
| video_capture = cv2.VideoCapture(video_path) | |
| if video_capture.isOpened(): | |
| frame_total = video_capture.get(cv2.CAP_PROP_FRAME_COUNT) | |
| video_capture.set(cv2.CAP_PROP_POS_FRAMES, min(frame_total, frame_number - 1)) | |
| has_vision_frame, vision_frame = video_capture.read() | |
| video_capture.release() | |
| if has_vision_frame: | |
| return vision_frame | |
| return None | |
| def count_video_frame_total(video_path : str) -> int: | |
| if is_video(video_path): | |
| if is_windows(): | |
| video_path = sanitize_path_for_windows(video_path) | |
| video_capture = cv2.VideoCapture(video_path) | |
| if video_capture.isOpened(): | |
| video_frame_total = int(video_capture.get(cv2.CAP_PROP_FRAME_COUNT)) | |
| video_capture.release() | |
| return video_frame_total | |
| return 0 | |
| def detect_video_fps(video_path : str) -> Optional[float]: | |
| if is_video(video_path): | |
| if is_windows(): | |
| video_path = sanitize_path_for_windows(video_path) | |
| video_capture = cv2.VideoCapture(video_path) | |
| if video_capture.isOpened(): | |
| video_fps = video_capture.get(cv2.CAP_PROP_FPS) | |
| video_capture.release() | |
| return video_fps | |
| return None | |
| def restrict_video_fps(video_path : str, fps : Fps) -> Fps: | |
| if is_video(video_path): | |
| video_fps = detect_video_fps(video_path) | |
| if video_fps < fps: | |
| return video_fps | |
| return fps | |
| def detect_video_resolution(video_path : str) -> Optional[Resolution]: | |
| if is_video(video_path): | |
| if is_windows(): | |
| video_path = sanitize_path_for_windows(video_path) | |
| video_capture = cv2.VideoCapture(video_path) | |
| if video_capture.isOpened(): | |
| width = video_capture.get(cv2.CAP_PROP_FRAME_WIDTH) | |
| height = video_capture.get(cv2.CAP_PROP_FRAME_HEIGHT) | |
| video_capture.release() | |
| return int(width), int(height) | |
| return None | |
| def restrict_video_resolution(video_path : str, resolution : Resolution) -> Resolution: | |
| if is_video(video_path): | |
| video_resolution = detect_video_resolution(video_path) | |
| if video_resolution < resolution: | |
| return video_resolution | |
| return resolution | |
| def create_video_resolutions(resolution : Resolution) -> List[str]: | |
| resolutions = [] | |
| temp_resolutions = [] | |
| if resolution: | |
| width, height = resolution | |
| temp_resolutions.append(normalize_resolution(resolution)) | |
| for template_size in video_template_sizes: | |
| if width > height: | |
| temp_resolutions.append(normalize_resolution((template_size * width / height, template_size))) | |
| else: | |
| temp_resolutions.append(normalize_resolution((template_size, template_size * height / width))) | |
| temp_resolutions = sorted(set(temp_resolutions)) | |
| for temp_resolution in temp_resolutions: | |
| resolutions.append(pack_resolution(temp_resolution)) | |
| return resolutions | |
| def normalize_resolution(resolution : Tuple[float, float]) -> Resolution: | |
| width, height = resolution | |
| if width and height: | |
| normalize_width = round(width / 2) * 2 | |
| normalize_height = round(height / 2) * 2 | |
| return normalize_width, normalize_height | |
| return 0, 0 | |
| def pack_resolution(resolution : Resolution) -> str: | |
| width, height = normalize_resolution(resolution) | |
| return str(width) + 'x' + str(height) | |
| def unpack_resolution(resolution : str) -> Resolution: | |
| width, height = map(int, resolution.split('x')) | |
| return width, height | |
| def resize_frame_resolution(vision_frame : VisionFrame, max_resolution : Resolution) -> VisionFrame: | |
| height, width = vision_frame.shape[:2] | |
| max_width, max_height = max_resolution | |
| if height > max_height or width > max_width: | |
| scale = min(max_height / height, max_width / width) | |
| new_width = int(width * scale) | |
| new_height = int(height * scale) | |
| return cv2.resize(vision_frame, (new_width, new_height)) | |
| return vision_frame | |
| def normalize_frame_color(vision_frame : VisionFrame) -> VisionFrame: | |
| return cv2.cvtColor(vision_frame, cv2.COLOR_BGR2RGB) | |
| def create_tile_frames(vision_frame : VisionFrame, size : Size) -> Tuple[List[VisionFrame], int, int]: | |
| vision_frame = numpy.pad(vision_frame, ((size[1], size[1]), (size[1], size[1]), (0, 0))) | |
| tile_width = size[0] - 2 * size[2] | |
| pad_size_bottom = size[2] + tile_width - vision_frame.shape[0] % tile_width | |
| pad_size_right = size[2] + tile_width - vision_frame.shape[1] % tile_width | |
| pad_vision_frame = numpy.pad(vision_frame, ((size[2], pad_size_bottom), (size[2], pad_size_right), (0, 0))) | |
| pad_height, pad_width = pad_vision_frame.shape[:2] | |
| row_range = range(size[2], pad_height - size[2], tile_width) | |
| col_range = range(size[2], pad_width - size[2], tile_width) | |
| tile_vision_frames = [] | |
| for row_vision_frame in row_range: | |
| top = row_vision_frame - size[2] | |
| bottom = row_vision_frame + size[2] + tile_width | |
| for column_vision_frame in col_range: | |
| left = column_vision_frame - size[2] | |
| right = column_vision_frame + size[2] + tile_width | |
| tile_vision_frames.append(pad_vision_frame[top:bottom, left:right, :]) | |
| return tile_vision_frames, pad_width, pad_height | |
| def merge_tile_frames(tile_vision_frames : List[VisionFrame], temp_width : int, temp_height : int, pad_width : int, pad_height : int, size : Size) -> VisionFrame: | |
| merge_vision_frame = numpy.zeros((pad_height, pad_width, 3)).astype(numpy.uint8) | |
| tile_width = tile_vision_frames[0].shape[1] - 2 * size[2] | |
| tiles_per_row = min(pad_width // tile_width, len(tile_vision_frames)) | |
| for index, tile_vision_frame in enumerate(tile_vision_frames): | |
| tile_vision_frame = tile_vision_frame[size[2]:-size[2], size[2]:-size[2]] | |
| row_index = index // tiles_per_row | |
| col_index = index % tiles_per_row | |
| top = row_index * tile_vision_frame.shape[0] | |
| bottom = top + tile_vision_frame.shape[0] | |
| left = col_index * tile_vision_frame.shape[1] | |
| right = left + tile_vision_frame.shape[1] | |
| merge_vision_frame[top:bottom, left:right, :] = tile_vision_frame | |
| merge_vision_frame = merge_vision_frame[size[1] : size[1] + temp_height, size[1]: size[1] + temp_width, :] | |
| return merge_vision_frame | |