Face Detection with OpenCV Haar Cascade

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

Technology Stack : OpenCV, Numpy

Code Type : Function

Code Difficulty : Intermediate

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

    # Load a pre-trained face detector 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)

    # Return the image with face detection results
    return image