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| from detect import * | |
| from pathlib import Path | |
| # Get the current script's directory | |
| script_dir = Path(__file__).resolve().parent | |
| # Define the relative path to the weights file | |
| weights_path = script_dir / 'runs/train/exp17/weights/best.pt' | |
| def yolo_inference(image): | |
| import tempfile | |
| temp_dir = tempfile.TemporaryDirectory() | |
| temp_path = Path(temp_dir.name) / "input_image.jpg" | |
| output_path = Path(temp_dir.name) / "output_image.jpg" | |
| image.save(temp_path) | |
| run(weights=weights_path, source=str(temp_path), project=str(temp_dir.name), name='result', exist_ok=True) | |
| result_image_path = list((Path(temp_dir.name) / 'result').glob('*.jpg'))[0] | |
| result_image = Image.open(result_image_path) | |
| return result_image | |
| interface = gr.Interface( | |
| fn=yolo_inference, | |
| inputs=gr.Image(type="pil"), | |
| outputs=gr.Image(type="pil"), | |
| title="YOLO Object Detection", | |
| description="Upload an image to detect objects using YOLO." | |
| ) | |
| interface.launch() |