OpenCV Face Detection with Haar Cascades

This function uses the Haar feature classifier from the OpenCV library to detect faces in the given image and draw rectangles around the detected faces.

Technology Stack : OpenCV, Numpy

Code Type : Image processing

Code Difficulty : Intermediate

                
                    
def face_detection(image_path):
    import cv2
    import numpy as np

    # Load the face detection model
    face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')

    # Read the image
    image = cv2.imread(image_path)
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

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

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

    # Display the image with detected faces
    cv2.imshow('Face Detection', image)
    cv2.waitKey(0)
    cv2.destroyAllWindows()

    return image