Update app.py

app.py

@@ -1,8 +1,22 @@
 import gradio as gr
+import numpy as np 
+import cv2
+
 
 def detect_faces(image ) : 
     # detect faces 
-    return image 
+    # convert image in to numpy array
+    image_np = np.array(image)
+    # convert image into gray 
+    gray_image = cv2.cvtColor(image_np, cv2.COLOR_RGB2GRAY)
+    # use detectmultiscale function to detect faces using haar cascade 
+    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))
+    # draw rectangle along detected faces
+    for (x, y, w, h) in faces:
+        cv2.rectangle(image_np, (x, y), (x+w, y+h), (255, 0, 0), 5)        
+    
+    return image_np 
 
 iface = gr.Interface(  fn=detect_faces,
     inputs="image",