main.py

import cv2

# Load the pre-trained Haar Cascade Classifier for face detection
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')

# Load an image
image = cv2.imread('test1.jpg')  # Replace with the path to your image
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)  # Convert to grayscale for better detection

# Detect faces in the image
faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))

# Draw rectangles around the faces
for (x, y, w, h) in faces:
    cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 3)

# Display the result
cv2.imshow('Face Detection', image)

# Wait until a key is pressed and close the image window
cv2.waitKey(0)
cv2.destroyAllWindows()