code

#requirements
!pip install opencv-python
!pip install opencv-python-headless
#The files or the images that we should upload
from google.colab import files
uploaded = files.upload()
#This is the main code
import cv2
import numpy as np
from matplotlib import pyplot as plt

# Load the uploaded image
image_path = list(uploaded.keys())[0]
img = cv2.imread(image_path)

# Convert to grayscale
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# Load Haar Cascade Classifier
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')

# 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(img, (x, y), (x+w, y+h), (255, 0, 0), 2)

    # Convert BGR image to RGB for matplotlib
    img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)

    # Show the output image
    plt.figure(figsize=(10,10))
    plt.imshow(img_rgb)
    plt.axis('off')
    plt.show()