Update app.py

app.py

@@ -1,34 +1,39 @@
 import gradio as gr
-import tensorflow as tf
-from PIL import Image
 import numpy as np
-from tensorflow.keras.preprocessing.image import img_to_array
+from PIL import Image
 from tensorflow.keras.models import load_model
+from tensorflow.keras.preprocessing.image import img_to_array
 
-# Load the pre-trained model
+# Assuming your model and class names are loaded correctly
 model = load_model('pokemon_classifier_model.keras')
-classes = ['Doduo', 'Geodude', 'Zubat']  # List of classes
+classes = ['Doduo', 'Geodude', 'Zubat']
 
 def classify_image(image):
-    """Function to classify the image using the pre-trained model."""
-    image = image.resize((150, 150))  # Resize image to match model's expected input
-    image_array = img_to_array(image)
-    image_array = image_array.reshape((1, 150, 150, 3))  # Reshape for model
-    image_array /= 255.0  # Normalize the image
-    
-    prediction = model.predict(image_array)
-    predicted_class = classes[np.argmax(prediction)]
-    confidence = np.max(prediction)
-    return predicted_class, f"{confidence * 100:.2f}% Confidence"
+    try:
+        # Image preprocessing
+        image = image.resize((150, 150))
+        image_array = img_to_array(image)
+        image_array = image_array.reshape((1, 150, 150, 3))
+        image_array /= 255.0
+        
+        # Model prediction
+        prediction = model.predict(image_array)
+        predicted_class = classes[np.argmax(prediction)]
+        confidence = np.max(prediction)
+        
+        return predicted_class, f"{confidence * 100:.2f}% Confidence"
+    except Exception as e:
+        # Catch and print any error that occurs
+        print(f"Error during model prediction: {e}")
+        return "Error in prediction", "Error"
 
-# Create a Gradio interface
+# Gradio app setup
 iface = gr.Interface(
     fn=classify_image,
     inputs=gr.Image(),
-    outputs=[gr.Label(num_top_classes=3), gr.Text()],
+    outputs=[gr.Text(), gr.Text()],
     title="Pokémon Image Classifier",
     description="Upload an image of a Pokémon to classify!"
 )
 
-# Launch the Gradio app
-iface.launch()
+iface.launch()