Update app.py

app.py

@@ -1,30 +1,34 @@
 import gradio as gr
 from huggingface_hub import hf_hub_download
 from ultralytics import YOLO
-from PIL import Image
+import numpy as np
 
-# Load YOLO model correctly
 model_path = hf_hub_download(repo_id="newtechdevng/detect", filename="best.pt")
 model = YOLO(model_path)
 
 def predict(image):
     results = model(image)
     result = results[0]
-    
-    output = []
+
+    # Get annotated image with boxes drawn
+    annotated = result.plot()
+
+    labels = []
     for box in result.boxes:
-        label = result.names[int(box.cls)]
         confidence = float(box.conf)
-        output.append(f"{label}: {confidence:.2f}")
-    
-    if not output:
-        return "No objects detected"
-    
-    return "\n".join(output)
+        if confidence < 0.5:
+            continue
+        label = result.names[int(box.cls)]
+        labels.append(f"{label}: {confidence:.2f}")
+
+    return annotated, "\n".join(labels) if labels else "No objects detected"
 
 gr.Interface(
     fn=predict,
     inputs=gr.Image(type="pil"),
-    outputs=gr.Text(label="Detections"),
+    outputs=[
+        gr.Image(label="Detected Objects"),   # image with boxes
+        gr.Text(label="Labels")               # text results
+    ],
     title="Car / Bike / Mountain / Road Detector"
 ).launch()