Upload app.py

app.py

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+import gradio as gr
+import tensorflow as tf
+from PIL import Image
+import numpy as np
+
+# Modellpfad
+model_path = "pokemon_classifier_model.keras"
+
+# Modell laden
+model = tf.keras.models.load_model(model_path)
+
+# Klassenlabels (Passe diese entsprechend deinem Modell an)
+labels = ['Abra', 'Cloyster', 'Dodrio']
+
+# Vorhersagefunktion
+def predict(image):
+    # Bildvorverarbeitung
+    image = image.resize((64, 64))
+    image = np.array(image) / 255.0
+    image = np.expand_dims(image, axis=0)
+    predictions = model.predict(image)
+    confidences = {labels[i]: float(predictions[0][i]) for i in range(len(labels))}
+    return confidences
+
+# Gradio-Interface erstellen
+iface = gr.Interface(fn=predict, 
+                     inputs=gr.inputs.Image(shape=(64, 64)),
+                     outputs=gr.outputs.Label(),
+                     description="Pokémon Classifier")
+
+if __name__ == "__main__":
+    iface.launch()