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from typing import Optional |
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from functools import lru_cache |
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import cv2 |
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from facefusion.typing import Frame |
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def get_video_frame(video_path : str, frame_number : int = 0) -> Optional[Frame]: |
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if video_path: |
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video_capture = cv2.VideoCapture(video_path) |
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if video_capture.isOpened(): |
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frame_total = video_capture.get(cv2.CAP_PROP_FRAME_COUNT) |
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video_capture.set(cv2.CAP_PROP_POS_FRAMES, min(frame_total, frame_number - 1)) |
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has_frame, frame = video_capture.read() |
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video_capture.release() |
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if has_frame: |
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return frame |
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return None |
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def detect_fps(video_path : str) -> Optional[float]: |
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if video_path: |
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video_capture = cv2.VideoCapture(video_path) |
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if video_capture.isOpened(): |
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return video_capture.get(cv2.CAP_PROP_FPS) |
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return None |
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def count_video_frame_total(video_path : str) -> int: |
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if video_path: |
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video_capture = cv2.VideoCapture(video_path) |
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if video_capture.isOpened(): |
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video_frame_total = int(video_capture.get(cv2.CAP_PROP_FRAME_COUNT)) |
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video_capture.release() |
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return video_frame_total |
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return 0 |
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def normalize_frame_color(frame : Frame) -> Frame: |
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return cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) |
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def resize_frame_dimension(frame : Frame, max_width : int, max_height : int) -> Frame: |
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height, width = frame.shape[:2] |
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if height > max_height or width > max_width: |
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scale = min(max_height / height, max_width / width) |
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new_width = int(width * scale) |
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new_height = int(height * scale) |
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return cv2.resize(frame, (new_width, new_height)) |
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return frame |
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@lru_cache(maxsize = 128) |
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def read_static_image(image_path : str) -> Optional[Frame]: |
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return read_image(image_path) |
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def read_image(image_path : str) -> Optional[Frame]: |
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if image_path: |
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return cv2.imread(image_path) |
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return None |
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def write_image(image_path : str, frame : Frame) -> bool: |
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if image_path: |
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return cv2.imwrite(image_path, frame) |
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return False |
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