Update app.py

app.py

@@ -5,9 +5,9 @@ from sahi.utils.cv import visualize_object_predictions, read_image
 from ultralyticsplus import YOLO
 
 # Images
-torch.hub.download_url_to_file('https://raw.githubusercontent.com/kadirnar/dethub/main/data/images/highway.jpg', 'highway.jpg')
-torch.hub.download_url_to_file('https://user-images.githubusercontent.com/34196005/142742872-1fefcc4d-d7e6-4c43-bbb7-6b5982f7e4ba.jpg', 'highway1.jpg')
-torch.hub.download_url_to_file('https://raw.githubusercontent.com/obss/sahi/main/tests/data/small-vehicles1.jpeg', 'small-vehicles1.jpeg')
+torch.hub.download_url_to_file('https://raw.githubusercontent.com/Owaiskhan9654/test_test/main/20.jpeg', '20.jpeg')
+torch.hub.download_url_to_file('https://raw.githubusercontent.com/Owaiskhan9654/test_test/main/30.jpeg', '30.jpeg')
+torch.hub.download_url_to_file('https://raw.githubusercontent.com/Owaiskhan9654/test_test/main/17.jpeg', '17.jpeg')
 
 def yolov8_inference(
     image: gr.inputs.Image = None,
@@ -37,6 +37,7 @@ def yolov8_inference(
         if len(image_results)!=0:
             image_predictions_in_xyxy_format = image_results#['det']
             for pred in image_predictions_in_xyxy_format:
+                print(pred)
                 x1, y1, x2, y2 = (
                     int(pred[0]),
                     int(pred[1]),
@@ -72,7 +73,7 @@ inputs = [
 outputs = gr.outputs.Image(type="filepath", label="Output Image")
 title = "Ultralytics YOLOv8: State-of-the-Art YOLO Models"
 
-examples = [['highway.jpg', 'owaiskha9654/yolov8-custom_objects', 224, 0.25, 0.45], ['highway1.jpg', 'owaiskha9654/yolov8-custom_objects', 224, 0.25, 0.45],]# ['small-vehicles1.jpeg', 'owaiskha9654/yolov8-custom_objects', 1280, 0.25, 0.45]]
+examples = [['20.jpeg', 'owaiskha9654/yolov8-custom_objects', 224, 0.25, 0.45], ['30.jpeg', 'owaiskha9654/yolov8-custom_objects', 224, 0.25, 0.45],]# ['17.jpeg', 'owaiskha9654/yolov8-custom_objects', 1280, 0.25, 0.45]]
 demo_app = gr.Interface(
     fn=yolov8_inference,
     inputs=inputs,