Done

app.py

@@ -20,12 +20,14 @@ def yolov8_predict_func(image : gr.Image = None, # uploading an image as input
     # Performing the detection on the YOLO Image
     
     results = model.predict(
-        image,
+        source = image,
         conf = conf_threshold,
         iou = iou_threshold,
         imgsz = image_size
     )
     
+    print(results)
+    
     # Displaying the detected object's information
     
     # box = results[0].boxes
@@ -35,7 +37,7 @@ def yolov8_predict_func(image : gr.Image = None, # uploading an image as input
     
     # Rendering the output image with bounding boxes around detected objects
     
-    render = render_result(model = model, image = image, result = results[0])
+    render = render_result(model = model, image = image, result = int(results[0].obb[0].cls))
 
     return render
 
@@ -62,4 +64,4 @@ yolo_app = gr.Interface(
     cache_examples = True
 )
 
-yolo_app.launch()
+yolo_app.launch(share = True)

yolov8n.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:31e20dde3def09e2cf938c7be6fe23d9150bbbe503982af13345706515f2ef95
+size 6534387