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from typing import Optional, List
from functools import lru_cache
import cv2
from facefusion.typing import Frame
def get_video_frame(video_path : str, frame_number : int = 0) -> Optional[Frame]:
if 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_frame, frame = video_capture.read()
video_capture.release()
if has_frame:
return frame
return None
def detect_fps(video_path : str) -> Optional[float]:
if video_path:
video_capture = cv2.VideoCapture(video_path)
if video_capture.isOpened():
return video_capture.get(cv2.CAP_PROP_FPS)
return None
def count_video_frame_total(video_path : str) -> int:
if 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 normalize_frame_color(frame : Frame) -> Frame:
return cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
def resize_frame_dimension(frame : Frame, max_width : int, max_height : int) -> Frame:
height, width = frame.shape[:2]
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(frame, (new_width, new_height))
return frame
@lru_cache(maxsize = 128)
def read_static_image(image_path : str) -> Optional[Frame]:
return read_image(image_path)
def read_static_images(image_paths : List[str]) -> Optional[List[Frame]]:
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[Frame]:
if image_path:
return cv2.imread(image_path)
return None
def write_image(image_path : str, frame : Frame) -> bool:
if image_path:
return cv2.imwrite(image_path, frame)
return False
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