Face Detection in Video

import cv2
import time

def face_detection_video(source=0, max_frames=300):
    """
    Real-time face detection from camera or video file.
    source: 0 = default webcam, or a video file path
    max_frames: stop after this many frames (0 = run until 'q' pressed)
    """
    face_cascade = cv2.CascadeClassifier(
        cv2.data.haarcascades + "haarcascade_frontalface_default.xml"
    )

    cap = cv2.VideoCapture(source)
    if not cap.isOpened():
        print("Error: Could not open video source")
        return

    # Get video properties
    fps = cap.get(cv2.CAP_PROP_FPS)
    total = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
    print(f"Video: {fps:.1f} FPS, {total} frames")

    frame_count = 0
    face_counts = []
    start_time = time.time()

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

        # Resize for faster processing
        small = cv2.resize(frame, (640, 480))
        gray = cv2.cvtColor(small, cv2.COLOR_BGR2GRAY)

        # Detect faces — tune parameters for speed vs. accuracy
        faces = face_cascade.detectMultiScale(
            gray,
            scaleFactor=1.2,   # Larger = faster but less accurate
            minNeighbors=5,
            minSize=(30, 30)
        )

        face_counts.append(len(faces))

        # Draw detections
        for (x, y, w, h) in faces:
            cv2.rectangle(small, (x, y), (x+w, y+h), (0, 255, 0), 2)

        # Display FPS and count
        elapsed = time.time() - start_time
        proc_fps = frame_count / elapsed if elapsed > 0 else 0
        cv2.putText(small, f"Faces: {len(faces)} | FPS: {proc_fps:.1f}",
                   (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 0), 2)

        frame_count += 1
        if max_frames > 0 and frame_count >= max_frames:
            break

    cap.release()
    elapsed = time.time() - start_time
    print(f"Processed {frame_count} frames in {elapsed:.1f}s ({frame_count/elapsed:.1f} FPS)")
    print(f"Average faces per frame: {sum(face_counts)/len(face_counts):.1f}")

face_detection_video(source="video.mp4")