app.py

import cv2
import gradio as gr
import numpy as np

def detect_face(image):
    # Load Haar cascade from OpenCV
    face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
    img = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5)
    for (x, y, w, h) in faces:
        cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 2)

    return cv2.cvtColor(img, cv2.COLOR_BGR2RGB)

iface = gr.Interface(fn=detect_face, inputs=gr.Image(), outputs=gr.Image())
iface.launch()