Update app.py

app.py

@@ -46,18 +46,22 @@ classes = ['Colon Adenocarcinoma', 'Colon Benign Tissue', 'Lung Adenocarcinoma',
 
 # Function to preprocess the uploaded image and make predictions
 def predict(img):
-    # Resize and preprocess the image
-    img = img.resize((224, 224))
-    img_array = image.img_to_array(img)
-    img_array = np.expand_dims(img_array, axis=0)
-    
-    # Make predictions
-    predictions = model.predict(img_array)
-    predicted_class_index = np.argmax(predictions[0])
-    predicted_class = classes[predicted_class_index]
-    
-    # Return the predicted class and the raw predictions
-    return predicted_class, predictions[0]
+    try:
+        # Resize and preprocess the image
+        img = img.resize((224, 224))
+        img_array = image.img_to_array(img)
+        img_array = np.expand_dims(img_array, axis=0)
+        
+        # Make predictions
+        predictions = model.predict(img_array)
+        predicted_class_index = np.argmax(predictions[0])
+        predicted_class = classes[predicted_class_index]
+        
+        # Return the predicted class and the raw predictions
+        return predicted_class, predictions[0]
+    except Exception as e:
+        # Print the error message
+        return str(e), str(e)
 
 # Create a Gradio interface
 iface = gr.Interface(
@@ -72,4 +76,4 @@ iface = gr.Interface(
 )
 
 # Launch the interface
-iface.launch()
+iface.launch()