import cv2

Load the pre-trained Haar Cascade face detector

face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_frontalface_default.xml")

Start webcam capture

cap = cv2.VideoCapture(0)

while True: # Read frame from webcam ret, frame = cap.read() if not ret: break

# Convert frame to grayscale (needed for detection)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

# Detect faces
faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5)

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

# Show the result
cv2.imshow("Face Detection", frame)

# Exit on pressing 'q'
if cv2.waitKey(1) & 0xFF == ord('q'):
    break

Release resources

cap.release() cv2.destroyAllWindows()

Face-Detection

A Face Detection App uses your webcam or an image to detect faces using Haar Cascade or a pre-trained DNN model.