Update app.py

app.py

@@ -1,39 +1,35 @@
-%pip install tensorflow==2.15
 import gradio as gr
 import tensorflow as tf
 from PIL import Image
 import numpy as np
-
-
-labels = ['Cubone', 'Ditto', 'Psyduck', 'Snorlax', 'Weedle']
-
+ 
+labels = ['Gengar', 'Seel', 'Zapdos']
+ 
 def predict_pokemon_type(uploaded_file):
-    """Process the uploaded file and return the image of the most likely Pokémon."""
+    
     if uploaded_file is None:
         return "No file uploaded."
-
-    model = tf.keras.models.load_model('pokemon-model_transferlearning.keras')
+   
+    model = tf.keras.models.load_model('Gengar-vs-Seel-vs-Zapdos-model_transferlearning.keras')
+    # Load the image from the file path
     with Image.open(uploaded_file) as img:
-        img = img.resize((150, 150))
+        img = img.resize((150, 150)).convert('RGB')  # Convert image to RGB
         img_array = np.array(img)
-
+ 
         prediction = model.predict(np.expand_dims(img_array, axis=0))
-        max_index = np.argmax(prediction)
-        predicted_pokemon = labels[max_index]
-
-        # Load and return the image of the predicted Pokémon
-        result_img_path = f'pokemon_images/{predicted_pokemon}.jpg'
-        result_img = Image.open(result_img_path)
-        return result_img
-
+        confidences = {labels[i]: np.round(float(prediction[0][i]), 2) for i in range(len(labels))}
+ 
+        return confidences
+ 
+ 
 # Define the Gradio interface
 iface = gr.Interface(
     fn=predict_pokemon_type,  # Function to process the input
     inputs=gr.File(label="Upload File"),  # File upload widget
-    outputs=gr.Image(),  # Output type is now an image
-    title="Pokemon Classifier",
-    description="Upload a picture of a pokemon (preferably Cubone, Ditto, Psyduck, Snorlax, or Weedle), because the model was trained on 'em. 87.5% accuracy :)"
+    outputs="text",  # Output type
+    title="Pokemon Classifier",  # Title of the interface
+    description="Upload a picture of a pokemon (preferably Gengar, Seel, Zapdos)"  # Description of the interface
 )
-
+ 
 # Launch the interface
-iface.launch()
+iface.launch()