Delete app.py

app.py

@@ -1,46 +0,0 @@
-import gradio as gr
-import tensorflow as tf
-from PIL import Image
-import numpy as np
-import os
-
-# Modellpfad relativ zum aktuellen Arbeitsverzeichnis
-model_path = 'models/chess_piece_classifier.keras'
-
-# Modell laden
-model = tf.keras.models.load_model(model_path)
-
-# Klassenlabels (Passe diese entsprechend deinem Modell an)
-labels = ['Black bishop', 'Black king', 'Black knight', 'Black pawn', 'Black queen', 'Black rook', 'White bishop', 'White king', 'White knight', 'White pawn', 'White queen', 'White rook']
-
-# Vorhersagefunktion
-def predict(image):
-    try:
-        # Bildvorverarbeitung
-        image = image.resize((150, 150))
-        image = np.array(image) / 255.0
-        image = np.expand_dims(image, axis=0)
-        
-        # Vorhersage
-        predictions = model.predict(image)
-        confidences = {labels[i]: float(predictions[0][i]) for i in range(len(labels))}
-        
-        return confidences
-    except Exception as e:
-        return str(e)  # Fehlernachricht zurückgeben
-
-# Gradio-Interface erstellen
-iface = gr.Interface(
-    fn=predict, 
-    inputs=gr.Image(type="pil"),  # Bild als PIL-Objekt
-    outputs=gr.Label(),
-    description="Chess Piece Classifier",
-    examples=[
-        ['data/Black bishop/example1.png'],
-        ['data/Black king/example1.png'],
-        ['data/Black knight/example1.png']
-    ]
-)
-
-if __name__ == "__main__":
-    iface.launch()