| # Commented out IPython magic to ensure Python compatibility. | |
| !git clone https://github.com/meituan/YOLOv6.git | |
| %cd YOLOv6 | |
| %pip install -r requirements.txt | |
| """# Inference | |
| First, download a pretrained model from the YOLOv6 [release](https://github.com/meituan/YOLOv6/releases). | |
| ### You can also use torch.hub style to load the pretrained model or custom model to inference. | |
| """ | |
| import gradio | |
| from gradio.mix import Series | |
| # Download a pretrained model | |
| import torch | |
| torch.hub.download_url_to_file('https://github.com/meituan/YOLOv6/releases/download/0.3.0/yolov6s.pt', 'yolov6s.pt') | |
| import torch | |
| model_local = torch.hub.load('.', 'yolov6n', source='local') | |
| img_path = 'data/images/image1.jpg' | |
| prediction = model_local.predict(img_path) | |
| model_local.show_predict(img_path) |