Video processing

OpenCV: read a file

import cv2

cap = cv2.VideoCapture("clip.mp4")
if not cap.isOpened():
    raise RuntimeError("cannot open video")

fps = cap.get(cv2.CAP_PROP_FPS)
w = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
h = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
n = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
print(fps, w, h, n)

while True:
    ok, frame = cap.read()
    if not ok:
        break
    # frame: BGR uint8, shape (h, w, 3)

cap.release()

Always call release() (or use a context-style pattern) so file handles and camera devices are freed.

Frame index and seek

cap.set(cv2.CAP_PROP_POS_FRAMES, 120)  # jump to frame 120
ok, frame = cap.read()
ms = cap.get(cv2.CAP_PROP_POS_MSEC)     # position in ms (if available)

Seek accuracy depends on codec and container; keyframe-only seeking can land on the nearest keyframe.

Webcam and backend

cap = cv2.VideoCapture(0, cv2.CAP_DSHOW)  # Windows: DirectShow optional
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)
if not cap.isOpened():
    raise RuntimeError("camera not available")

Write MP4 (example)

fourcc = cv2.VideoWriter_fourcc(*"mp4v")
out = cv2.VideoWriter("out.mp4", fourcc, 30.0, (640, 480))
# ... for each frame BGR:
# out.write(frame)
out.release()

Codec fourcc must match what your OpenCV build supports; on some systems avc1 or H264 works better than mp4v.

torchvision: read_video

from torchvision.io import read_video

video, audio, info = read_video("clip.mp4", start_pts=0, end_pts=4, pts_unit="sec")
# video: (T, H, W, C) uint8 in RGB order
print(video.shape, info)

Useful for training clips; for long files prefer decoders that stream frames to limit RAM.