Update app.py

app.py

@@ -6,8 +6,8 @@ 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/tests/main/test_sample_images/favicon.jpg', 'favicon.jpg')
+torch.hub.download_url_to_file('https://raw.githubusercontent.com/Owaiskhan9654/tests/main/test_sample_images/Taj_Mahal.jpg', 'Taj_Mahal.jpg')
 
 def yolov8_inference(
     image: gr.inputs.Image = None,
@@ -71,7 +71,7 @@ inputs = [
 outputs = gr.outputs.Image(type="filepath", label="Output Image")
 title = "Ultralytics YOLOv8: State-of-the-Art YOLO Models"
 
-examples = [['highway.jpg', 'kadirnar/yolov8m-v8.0', 640, 0.25, 0.45], ['highway1.jpg', 'kadirnar/yolov8l-v8.0', 640, 0.25, 0.45], ['small-vehicles1.jpeg', 'kadirnar/yolov8x-v8.0', 1280, 0.25, 0.45]]
+examples = [['highway.jpg', 'kadirnar/yolov8m-v8.0', 640, 0.25, 0.45], ['Taj_Mahal.jpg', 'kadirnar/yolov8l-v8.0', 640, 0.25, 0.45], ['favicon.jpg', 'kadirnar/yolov8x-v8.0', 1280, 0.25, 0.45]]
 demo_app = gr.Interface(
     fn=yolov8_inference,
     inputs=inputs,