Update app.py

app.py

@@ -1,23 +1,25 @@
 import numpy as np
 import cv2
 import gradio as gr
-from PIL import Image
 
-def detect_faces(image):
-    image_np = np.array(image)
+def detect_faces(image_file):
+    image_np = cv2.imread(image_file.name)
     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=(10, 10))
-    print("faces: ",faces)
+    if len(faces) > 0:
+        print("Face detected!")
+    else:
+        print("No faces detected.")
     for (x, y, w, h) in faces:
         cv2.rectangle(image_np, (x, y), (x+w, y+h), (0, 255, 0), 2)
     return image_np
     
 interface = gr.Interface(
     fn=detect_faces,
-    inputs="image",
+    inputs="file",
     outputs="image",
     title="Face Detection with Haar Cascade",
-    description="Upload an image, and the model will detect faces and draw bounding boxes around them.",
+    description="Upload an image file, and the model will detect faces and draw bounding boxes around them.",
 )
 interface.launch()