Update app.py

app.py

@@ -27,14 +27,13 @@ if uploaded_file is not None:
         img = Image.open(uploaded_file)
         st.image(img)
         img = np.array(img)
-        img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) # OpenCV images have a different color profile. So remember to switch to RGB, that our resnet model understands.
-
+        img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) 
         cust_transform = A.Compose([A.Resize(height=256, width=256, p=1.0),ToTensorV2(p=1.0)], p=1.0)
         tensor = cust_transform(image=img)
         tensor = tensor['image'].float().resize(1,3,256,256)
 
-        custom_pred = model.forward(tensor).detach().numpy() # Forward is the python method defined inside the resnet.
-        custom_pred
+        custom_pred = model.forward(tensor).detach().numpy()
+        #custom_pred
 
         st.write(f'Predicted: {id2class[np.argmax(custom_pred)]}')
     elif '.csv' in uploaded_file.name: