Update app.py

app.py

@@ -1,16 +1,15 @@
- import numpy as np
- import cv2
- import gradio as gr
- from PIL import Image
- def detect_faces(image):
+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))
+ 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)
+     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.",)