Added detection boxes

app.py

@@ -9,14 +9,32 @@ model = YOLO('best.pt')  # Make sure best.pt is in the same folder
 def detect(image):
     results = model(image)
     annotated_frame = results[0].plot()  # Draw predictions on the image
-    return Image.fromarray(annotated_frame)
+    
+    # Get detection results
+    detections = []
+    for r in results:
+        boxes = r.boxes
+        for box in boxes:
+            x1, y1, x2, y2 = box.xyxy[0].tolist()  # Get box coordinates
+            conf = float(box.conf[0])  # Get confidence
+            cls = int(box.cls[0])  # Get class
+            detections.append({
+                'class': cls,
+                'confidence': conf,
+                'box': [x1, y1, x2, y2]
+            })
+    
+    return Image.fromarray(annotated_frame), detections
 
 # Launch the Gradio interface
 gr.Interface(
     fn=detect,
     inputs=gr.Image(type="pil"),
-    outputs=gr.Image(type="pil"),
+    outputs=[
+        gr.Image(type="pil", label="Detected Image"),
+        gr.JSON(label="Detection Results")
+    ],
     title="YOLOv9 (Ultralytics) Object Detection",
-    description="Upload an image to run object detection using your custom YOLOv9 model.",
+    description="Upload an image to run object detection using your custom YOLOv9 model. The results will show both the annotated image and the detection details.",
 ).launch()