Create app.py

app.py

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+ import numpy as np
+ import cv2
+ import gradio as gr
+ from PIL import Image
+ def detect_faces(image):
+ image_np= np.array(image)
+ gray_image= cv2.cvtColor(image_np, cv2.COLOR_RGB2GRAY)
+ face_cascade= cv2.CascadeClassifier(cv2.data.haarcascades + 
+"haarcascade_frontalface_default.xml")
+ faces = face_cascade.detectMultiScale(gray_image, 
+scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))
+ for (x, y, w, h) in faces:
+ cv2.rectangle(image_np, (x, y), (x+w, y+h), (0, 255, 0), 2)
+ return image_np
+
+iface= gr.Interface(fn=detect_faces,inputs="image",outputs="image",title="Face Detection",description="Upload an image, and the model will detect faces and draw bounding boxes around them.",)
+iface.launch()
+