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app.py

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+import gradio as gr
+from ultralytics import YOLOv10 
+import supervision as sv
+
+MODEL_PATH = 'yolov10n.pt'
+model = YOLOv10(MODEL_PATH)
+box_annotator = sv.BoxAnnotator()
+
+def detect(image):
+    results = model(source=image, conf=0.25, verbose=False)[0]
+    detections = sv.Detections.from_ultralytics(results)
+    
+    labels = [
+        f"{model.model.names[class_id]} {confidence:.2f}" 
+        for class_id, confidence in zip(detections.class_id, detections.confidence)
+    ]
+    annotated_image = box_annotator.annotate(image, detections=detections, labels=labels)
+
+    return annotated_image
+
+gr.Interface(
+    fn=detect, 
+    inputs=gr.inputs.Image(type="numpy"),
+    outputs=gr.outputs.Image(type="numpy", label="Annotated Image"),
+    title='YOLOv10 Object Detection',
+    description='Detect objects in images using the YOLOv10 model'
+).launch()

requirements.txt

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+supervision
+git+https://github.com/THU-MIG/yolov10.git