modified 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/jerryli27/AniSeg/master/samples/inputs/PL0bHKk6wuUGL_Qd34mf0XsQnyiDk2OeGR_032_T66-dT9j12E-0028.jpg', '0028.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')
 
 def yolov8_inference(
     image: gr.inputs.Image = None,
@@ -61,8 +61,9 @@ def yolov8_inference(
 
 inputs = [
     gr.inputs.Image(type="filepath", label="Input Image"),
-    gr.inputs.Dropdown(["kadirnar/yolov8n-v8.0", "kadirnar/yolov8m-v8.0", "kadirnar/yolov8l-v8.0", "kadirnar/yolov8x-v8.0", "kadirnar/yolov8x6-v8.0"], 
-                       default="kadirnar/yolov8m-v8.0", label="Model"),
+    # gr.inputs.Dropdown(["kadirnar/yolov8n-v8.0", "kadirnar/yolov8m-v8.0", "kadirnar/yolov8l-v8.0", "kadirnar/yolov8x-v8.0", "kadirnar/yolov8x6-v8.0"], 
+    #                    default="kadirnar/yolov8m-v8.0", label="Model"),
+    gr.inputs.Dropdown(["https://huggingface.co/jongkook90/yolov8_comicbook/resolve/main/train/weights/best.pt"], default="https://huggingface.co/jongkook90/yolov8_comicbook/resolve/main/train/weights/best.pt", label="Model"),
     gr.inputs.Slider(minimum=320, maximum=1280, default=640, step=32, label="Image Size"),
     gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.25, step=0.05, label="Confidence Threshold"),
     gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.45, step=0.05, label="IOU Threshold"),
@@ -71,7 +72,7 @@ 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 = [['0028.jpg', 'https://huggingface.co/jongkook90/yolov8_comicbook/resolve/main/train/weights/best.pt', 640, 0.25, 0.45],] 
 demo_app = gr.Interface(
     fn=yolov8_inference,
     inputs=inputs,
@@ -81,4 +82,4 @@ demo_app = gr.Interface(
     cache_examples=True,
     theme='huggingface',
 )
-demo_app.launch(debug=True, enable_queue=True)
+demo_app.launch(debug=True, enable_queue=True)