Video Processing with OpenCV

import cv2

# Open webcam (0 = default camera)
cap = cv2.VideoCapture(0)
# Or open a video file
# cap = cv2.VideoCapture("video.mp4")

if not cap.isOpened():
    raise IOError("Cannot open video source")

# Get video properties
fps = cap.get(cv2.CAP_PROP_FPS)
width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
print(f"Resolution: {width}x{height} @ {fps} FPS")

while True:
    ret, frame = cap.read()
    if not ret:
        break

    # Process frame here
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    cv2.imshow("Video", gray)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()

fourcc = cv2.VideoWriter_fourcc(*'mp4v')
out = cv2.VideoWriter('output.mp4', fourcc, 30.0, (640, 480))

cap = cv2.VideoCapture("input.mp4")
while cap.isOpened():
    ret, frame = cap.read()
    if not ret:
        break

    # Apply processing
    processed = cv2.GaussianBlur(frame, (15, 15), 0)
    out.write(processed)

cap.release()
out.release()

# Create background subtractor
bg_sub = cv2.createBackgroundSubtractorMOG2(
    history=500, varThreshold=50, detectShadows=True
)

cap = cv2.VideoCapture("traffic.mp4")
while cap.isOpened():
    ret, frame = cap.read()
    if not ret:
        break

    # Apply background subtraction
    fg_mask = bg_sub.apply(frame)

    # Clean up the mask
    kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
    fg_mask = cv2.morphologyEx(fg_mask, cv2.MORPH_OPEN, kernel)

    # Find moving objects
    contours, _ = cv2.findContours(fg_mask, cv2.RETR_EXTERNAL,
                                    cv2.CHAIN_APPROX_SIMPLE)
    for cnt in contours:
        if cv2.contourArea(cnt) > 1000:
            x, y, w, h = cv2.boundingRect(cnt)
            cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)

    cv2.imshow("Motion Detection", frame)

cap = cv2.VideoCapture("video.mp4")
ret, old_frame = cap.read()
old_gray = cv2.cvtColor(old_frame, cv2.COLOR_BGR2GRAY)

# Detect initial feature points
p0 = cv2.goodFeaturesToTrack(old_gray, maxCorners=100,
                              qualityLevel=0.3, minDistance=7)

lk_params = dict(winSize=(15, 15), maxLevel=2,
                  criteria=(cv2.TERM_CRITERIA_EPS |
                           cv2.TERM_CRITERIA_COUNT, 10, 0.03))

while cap.isOpened():
    ret, frame = cap.read()
    if not ret:
        break

    frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    p1, status, err = cv2.calcOpticalFlowPyrLK(
        old_gray, frame_gray, p0, None, **lk_params
    )

    # Draw tracks
    good_new = p1[status == 1]
    good_old = p0[status == 1]
    for new, old in zip(good_new, good_old):
        a, b = new.ravel().astype(int)
        c, d = old.ravel().astype(int)
        cv2.line(frame, (a, b), (c, d), (0, 255, 0), 2)
        cv2.circle(frame, (a, b), 5, (0, 0, 255), -1)

    old_gray = frame_gray.copy()
    p0 = good_new.reshape(-1, 1, 2)