Update app.py

app.py

@@ -9,19 +9,18 @@ model = tf.keras.models.load_model('pokemon_model.keras')
 # Klassennamen, sollten deinem Dataset entsprechen
 class_names = ['Jolteon', 'Kakuna', 'Mr. Mime']
 
-    def classify_image(image):
+def classify_image(image):
     image = Image.fromarray(image.astype('uint8'), 'RGB')
     img = image.resize((160, 160))
     img_array = tf.keras.preprocessing.image.img_to_array(img)
-    img_array = tf.expand_dims(img_array, 0)  # Erstelle einen Batch        
+    img_array = tf.expand_dims(img_array, 0)  # Erstelle einen Batch
     predictions = model.predict(img_array)
     predicted_class = class_names[np.argmax(predictions[0])]
     confidence = np.max(predictions[0])
     return predicted_class, confidence
 
-
-image_input = gr.Image()
-label = gr.Label(num_top_classes=3)      
+image_input = gr.Image()  # Entferne den `shape` Parameter
+label = gr.Label(num_top_classes=3)
 
 iface = gr.Interface(
     fn=classify_image,