Upload app.py

app.py

@@ -18,6 +18,7 @@ label_map = {
     # Add more if needed
 }
 
+# 🧠 Classification function
 def classify_mushroom(image: Image.Image):
     print("✅ classify_mushroom: NEW VERSION")
 
@@ -31,14 +32,15 @@ def classify_mushroom(image: Image.Image):
         score = round(result['score'] * 100, 2)
 
         prediction_en, prediction_th = label_map.get(label, ("Unknown", "ไม่ทราบ"))
-        print("✅ RETURNING:", prediction_en, prediction_th, f"{score:.2f}%")
-        return prediction_en, prediction_th, f"{score:.2f}%"
+        print("✅ RETURNING:", prediction_en, prediction_th, f"{score:.2f}%", label)
+
+        return prediction_en, prediction_th, f"{score:.2f}%", label
 
     except Exception as e:
         print(f"❌ Error: {e}")
-        return "Error", "ผิดพลาด", "N/A"
+        return "Error", "ผิดพลาด", "N/A", "N/A"
 
-# ✅ Put Gradio inside the main block
+# 🎨 Gradio UI
 if __name__ == "__main__":
     with gr.Blocks() as demo:
         gr.Markdown("## 🍄 Mushroom Safety Classifier")
@@ -50,13 +52,16 @@ if __name__ == "__main__":
                 label_en = gr.Textbox(label="🧠 Prediction (English)")
                 label_th = gr.Textbox(label="🗣️ คำทำนาย (ภาษาไทย)")
                 confidence = gr.Textbox(label="📶 Confidence Score")
+                label_raw = gr.Textbox(label="🏷️ Predicted Mushroom Name")
 
         classify_btn = gr.Button("🔍 Classify")
 
         classify_btn.click(
             fn=classify_mushroom,
             inputs=image_input,
-            outputs=[label_en, label_th, confidence]
+            outputs=[label_en, label_th, confidence, label_raw]
         )
 
     demo.launch()
+
+