Update app.py

app.py

@@ -1,8 +1,15 @@
+
 import gradio as gr
 from ultralytics import YOLOv10 
 import supervision as sv
 import spaces
+from huggingface_hub import hf_hub_download
+
 
+def download_models(model_id):
+    hf_hub_download("kadirnar/Yolov10", filename=f"{model_id}", local_dir=f"./")
+    return f"./{model_id}"
+    
 box_annotator = sv.BoxAnnotator()
 category_dict = {
     0: 'person', 1: 'bicycle', 2: 'car', 3: 'motorcycle', 4: 'airplane', 5: 'bus',
@@ -26,7 +33,8 @@ category_dict = {
 
 @spaces.GPU(duration=200)
 def yolov10_inference(image, model_id, image_size, conf_threshold, iou_threshold):
-    model = YOLOv10.from_pretrained(f"kadirnar/{model_id}")
+    model_path = download_models(model_id)
+    model = YOLOv10(model_path)
     results = model(source=image, imgsz=image_size, iou=iou_threshold, conf=conf_threshold, verbose=False)[0]
     detections = sv.Detections.from_ultralytics(results)
     
@@ -47,14 +55,14 @@ def app():
                 model_id = gr.Dropdown(
                     label="Model",
                     choices=[
-                        "yolov10n",
-                        "yolov10s",
-                        "yolov10m",
-                        "yolov10b",
-                        "yolov10l",
-                        "yolov10x",
+                        "yolov10n.pt",
+                        "yolov10s.pt",
+                        "yolov10m.pt",
+                        "yolov10b.pt",
+                        "yolov10l.pt",
+                        "yolov10x.pt",
                     ],
-                    value="yolov10m",
+                    value="yolov10m.pt",
                 )
                 image_size = gr.Slider(
                     label="Image Size",