Update to Use YOLOv10 Models from Latest Ultralytics Package

This pull request updates this project to use the latest YOLOv10 models from the recently released Ultralytics package.

app.py

@@ -1,6 +1,5 @@
-
 import gradio as gr
-from ultralytics import YOLOv10 
+from ultralytics import YOLO
 import supervision as sv
 import spaces
 
@@ -28,11 +27,9 @@ category_dict = {
 
 @spaces.GPU(duration=200)
 def yolov10_inference(image, model_id, image_size, conf_threshold, iou_threshold):
-    model_path = download_models(model_id)
-    model = YOLOv10.from_pretrained(f"jameslahm/{model_id}")
+    model = YOLO(f"{model_id}.pt")
     results = model(source=image, imgsz=image_size, iou=iou_threshold, conf=conf_threshold, verbose=False)[0]
     detections = sv.Detections.from_ultralytics(results)
-    
     labels = [
         f"{category_dict[class_id]} {confidence:.2f}"
         for class_id, confidence in zip(detections.class_id, detections.confidence)
@@ -101,21 +98,21 @@ def app():
             examples=[
                 [
                     "dog.jpeg",
-                    "yolov10x.pt",
+                    "yolov10x",
                     640,
                     0.25,
                     0.45,
                 ],
                 [
                     "huggingface.jpg",
-                    "yolov10m.pt",
+                    "yolov10m",
                     640,
                     0.25,
                     0.45,
                 ],
                 [
                     "zidane.jpg",
-                    "yolov10b.pt",
+                    "yolov10b",
                     640,
                     0.25,
                     0.45,

requirements.txt

@@ -1,2 +1,4 @@
 supervision
-git+https://github.com/THU-MIG/yolov10.git
+ultralytics
+spaces
+gradio