2nd update

app.py

@@ -14,13 +14,18 @@ def predict_rice_disease(img):
     img = img.resize((224, 224))
     img_array = image.img_to_array(img) / 255.0
     img_array = np.expand_dims(img_array, axis=0)
-    predictions = model.predict(img_array)
-    predicted_class = class_names[np.argmax(predictions)]
-    return predicted_class
+    predictions = model.predict(img_array)[0]  # shape: (num_classes,)
+    
+    # Map class names to confidence scores
+    confidence_scores = {class_names[i]: float(f"{predictions[i]:.4f}") for i in range(len(class_names))}
+    
+    return confidence_scores
 
-iface = gr.Interface(fn=predict_rice_disease,
-                     inputs=gr.Image(type="pil"),
-                     outputs="text",
-                     title="Rice Disease Classifier")
+iface = gr.Interface(
+    fn=predict_rice_disease,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Label(num_top_classes=len(class_names)),  # shows all class scores nicely
+    title="Rice Disease Classifier"
+)
 
 iface.launch()