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--- |
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license: mit |
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tags: |
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- Astronomy |
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- Classification |
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- Object Detection |
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--- |
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<div align="center"> |
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<h1 style="font-size:40px;font-weight:bold">DRAFTS</h1> |
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_✨ Deep learning-based RAdio Fast Transient Search pipeline✨_ |
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<img src="https://counter.seku.su/cmoe?name=APOD&theme=r34" /><br> |
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</div> |
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## <div align="center">Description</div> |
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Here is the model repository for the Deep learning-based RAdio Fast Transient Search pipeline ([DRAFTS](https://github.com/SukiYume/DRAFTS)). |
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We invite you to stay tuned for updates on the remaining components and different versions of the models. |
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## <div align="center">Usage</div> |
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There are four `.pth` files in this repository. |
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### Object Detection |
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The files starting with `cent` are the trained model checkpoints for the object detection models in the [DRAFTS](https://github.com/SukiYume/DRAFTS) project. |
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To load the object detection model |
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```python |
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import torch |
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from centernet_model import centernet |
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base_model = 'resnet18' # 'resnet50' |
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model = centernet(model_name=base_model) |
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model.load_state_dict(torch.load('cent_{}.pth'.format(base_model))) |
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model.eval() |
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``` |
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### Binary Classification |
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The files starting with `class` are the trained model checkpoints for the classification models in the [DRAFTS](https://github.com/SukiYume/DRAFTS) project. |
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To load the classification detection model |
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```python |
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import torch |
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from binary_model import BinaryNet |
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base_model = 'resnet18' # 'resnet50' |
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model = BinaryNet(base_model, num_classes=2) |
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model.load_state_dict(torch.load('class_{}.pth'.format(base_model))) |
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model.eval() |
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``` |
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## <div align="center">Contributing</div> |
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We welcome contributions to the DRAFTS project! If you have any suggestions, bug reports, or feature requests, please open an issue or submit a pull request on our [GitHub repository](https://github.com/SukiYume/DRAFTS). |
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## <div align="center">Contact</div> |
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For any questions or inquiries, please contact us at [email protected] or [email protected] |
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<div align="center"> |
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✨ Thank you for using DRAFTS! ✨ |
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</div> |
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