Update app.py

app.py

@@ -26,82 +26,30 @@ st.markdown('''
  </div>
 ''', unsafe_allow_html=True)
 
-# Function to take a photo using the webcam
-def take_photo(filename='photo.jpg', quality=
- 0.8):
-  js = Javascript('''
-    async function takePhoto(quality) {
-      const div = document.createElement('div');
-      const capture = document.createElement('button');
-      capture.textContent = 'Capture';
-      div.appendChild(capture);
-
-      const video = document.createElement('video');
-      video.style.display = 'block';
-      const stream = await navigator.mediaDevices.getUserMedia({ video: true });
-
-      document.body.appendChild(div);
-      div.appendChild(video);
-      video.srcObject = stream;
-      await video.play();
-
-      // Resize the output to fit the video element.
-      google.colab.output.setIframeHeight(document.documentElement.scrollHeight, true);
-
-      // Wait for Capture to be clicked.
-      await new Promise((resolve) => capture.onclick = resolve);
-
-      const canvas = document.createElement('canvas');
-      canvas.width = video.videoWidth;
-      canvas.height = video.videoHeight;
-      canvas.getContext('2d').drawImage(video, 0, 0);
-      stream.getVideoTracks()[0].stop();
-      div.remove();
-      return canvas.toDataURL('image/jpeg', quality);
-    }
-  ''')
-  display(js)
-  data = eval_js('takePhoto({})'.format(quality))
-  binary = b64decode(data.split(',')[1])
-  with open(filename, 'wb') as f:
-    f.write(binary)
-  return filename
-   
-
-opt = st.selectbox("How do you want to upload the image for classification?",
-          ('Please Select', 'Upload image via link', 'Upload image from device', 'Capture a picture'))
-
-# Image processing based on user selection
+
 image = None
 if opt == 'Upload image from device':
   file = st.file_uploader('Select', type=['jpg', 'png', 'jpeg'])
   if file:
-    try:
-      image = cv2.imread(file)
-      image = cv2.resize(image, (256, 256))
-    except Exception as e:
-      st.error(f"Error reading the file: {e}")
+      image = preprocess_image(file)
+    
 
 elif opt == 'Upload image via link':
   img_url = st.text_input('Enter the Image Address')
   if st.button('Submit'):
     try:
       response = urllib.request.urlopen(img_url)
-      image = cv2.imread(io.BytesIO(response.read()))
-      image = cv2.resize(image, (256, 256))
+      image = preprocess_image(response)
     except ValueError:
       st.error("Please Enter a valid Image Address!")
 
-elif opt == 'Capture a picture':
-  take_photo()
+
 
 try:
   if image is not None:
     st.image(image, width=256, caption='Uploaded Image')
     if st.button('Predict'):
-      img = preprocess(image)
-      #model = model_arc()
-      # model.load_weights("classify_model.h5")
+
 
       print("---------------img-array---------------------")
       print(img[np.newaxis, ...])