OpenCV Face Detection with Haar Cascade Classifier

This function uses the Haar feature cascade classifier from the OpenCV library for face detection and draws rectangles around the detected faces in the image.

Technology Stack : OpenCV, Numpy

Code Type : The type of code

Code Difficulty : Advanced

                
                    
def face_detection(image_path):
    import cv2
    import numpy as np
    
    # Load the pre-trained face detection model
    face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
    
    # Read the image
    image = cv2.imread(image_path)
    
    # Convert the image to grayscale
    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)
    
    # Return the image with face detections
    return image