minor

app.py

@@ -1,13 +1,13 @@
 import gradio as gr
-import torch
+#import torch
 from sahi.prediction import ObjectPrediction
 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/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')
 
 def yolov8_inference(
     image: gr.inputs.Image = None,
@@ -61,15 +61,15 @@ 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(["ihorbilyk/yolov8c-v1.0"], 
+                       default="ihorbilyk/yolov8c-v1.0", 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"),
 ]
 
 outputs = gr.outputs.Image(type="filepath", label="Output Image")
-title = "Ultralytics YOLOv8: State-of-the-Art YOLO Models"
+title = "Ultralytics YOLOv8: Fine-tuned for checks detection"
 
 demo_app = gr.Interface(
     fn=yolov8_inference,