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
+
+# Lade das Modell
+model = tf.keras.models.load_model("fruit_classifier_model_v2.keras")
+
+class_names = ['Apple', 'Banana', 'Grapes', 'Kiwi', 'Orange', 'Pineapple', 'Strawberries']
+
+def classify_fruit(image):
+    image = Image.fromarray(image).resize((224, 224))
+    image = np.array(image) / 255.0
+    image = np.expand_dims(image, axis=0)
+    predictions = model.predict(image)[0]
+    
+    results = {class_name: float(predictions[i]) for i, class_name in enumerate(class_names)}
+    return results
+
+interface = gr.Interface(
+    fn=classify_fruit,
+    inputs=gr.Image(),
+    outputs=gr.Label(num_top_classes=7),
+    live=True
+)
+
+if __name__ == "__main__":
+    interface.launch(share=True)