Delete app.py

app.py

@@ -1,39 +0,0 @@
-import gradio as gr
-import tensorflow as tf
-from PIL import Image
-import numpy as np
- 
-# Load the Pokémon classifier model
-model_path = "pokemon_classifier_finetuned.keras"
-model = tf.keras.models.load_model(model_path)
- 
-labels = ['Arbok', 'Nidoking', 'Tauros']
- 
-# Define function for Pokémon classification
-def preprocess_image(image):
-    # Preprocess image
-    image = Image.fromarray(image.astype('uint8'))
-    image = image.resize((224, 224))
-    image = np.array(image)
-    image = image / 255.0  # Normalize pixel values
-    return image
- 
-# Prediction
-def predict_pokemon(image):
-    image = preprocess_image(image)
-    prediction = model.predict(image[None, ...])
-    predicted_class = labels[np.argmax(prediction)]
-    confidence = np.round(np.max(prediction) * 100, 2)
-    result = f"Label: {predicted_class}, Confidence: {confidence}%"
-    return result
- 
-# Create Gradio interface
-input_image = gr.Image()
-output_text = gr.Textbox(label="Pokemon")
-interface = gr.Interface(fn=predict_pokemon, 
-                         inputs=input_image, 
-                         outputs=output_text,   
-                         description="A Pokémon classifier using transfer learning and fine-tuning with EfficientNetB0.")
- 
-if __name__ == "__main__":
-    interface.launch()