Update app.py

app.py

@@ -129,10 +129,16 @@ def predict_image(img):
     img_resized = tf.image.resize(img, (img_height, img_width))
     img_4d = tf.expand_dims(img_resized, axis=0)
     prediction = model.predict(img_4d)[0]
-    return {class_names[i]: float(prediction[i]) for i in range(len(class_names))}
+    max_index = np.argmax(prediction)
+    max_probability = tf.nn.softmax(prediction)[max_index]
+    
+    if max_probability == 1.0:
+        return {class_names[max_index]: float(max_probability)}
+    else:
+        return {"None": "No class with 100% confidence"}
 
 image = gr.Image()
-label = gr.Label(num_top_classes=12)
+label = gr.Label(num_top_classes=1)
 
 gr.Interface(
     fn=predict_image,