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--- |
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datasets: |
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- PanCollection |
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language: en |
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license: gpl-2.0 |
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size_categories: |
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- 1K<n<10K |
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tags: |
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- Pytorch |
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--- |
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# ✨ PanCollection |
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🤗 To get started with PanCollection benchmark (training, inference, etc.), we recommend reading [Google Colab](https://colab.research.google.com/drive/1KpWWj1lVUGllZCws01zQfd6CeURuGL2O#scrollTo=k53dsFhAdp6n)! |
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## Recommendations |
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We recommend users to use the code-toolbox [DLPan-Toolbox](https://github.com/liangjiandeng/DLPan-Toolbox/tree/main/02-Test-toolbox-for-traditional-and-DL(Matlab)) + the dataset [PanCollection](https://drive.google.com/drive/folders/15VXUjqPybtqUN_spKfJbw40W05K4nDdY?usp=sharing) for fair training and testing! |
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### Deploy |
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PanCollection has provided complete packages. |
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``` |
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pip install pancollection --upgrade |
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``` |
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## How to Get Started with the Model |
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```python |
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import pancollection as pan |
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cfg = pan.TaskDispatcher.new(task='pansharpening', mode='entrypoint', arch='FusionNet', |
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dataset_name="gf2", use_resume=False, |
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dataset={'train': 'gf2', 'test': 'test_gf2_multiExm1.h5'}) |
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print(pan.TaskDispatcher._task) |
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pan.trainer.main(cfg, pan.build_model, pan.getDataSession) |
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``` |
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## Training Details |
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See [Google Colab](https://colab.research.google.com/drive/1KpWWj1lVUGllZCws01zQfd6CeURuGL2O) for quick start. |
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See [Github Project](https://github.com/XiaoXiao-Woo/PanCollection) for coding details. |
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## Evaluation |
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See the [Leaderboard](https://paperswithcode.com/dataset/worldview-3-pancollection) for model results. |
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See the [PanCollection Paper](https://liangjiandeng.github.io/papers/2022/deng-jig2022.pdf) for early results. |
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| **Satellite** | **Value** | **Comment** | |
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|--------------------|-----------|----------------------------------------| |
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| WorldView-3 | 2047 | | |
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| QuickBird | 2047 | | |
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| GaoFen-2 | 1023 | | |
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| WorldView-2 | 2047 | | |
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## Citation |
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To learn more about the PanCollection dataset, see the [Github Pages](https://github.com/liangjiandeng/PanCollection). |
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``` |
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@ARTICLE{dengjig2022, |
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author={邓良剑，冉燃，吴潇，张添敬}, |
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journal={中国图象图形学报}, |
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title={遥感图像全色锐化的卷积神经网络方法研究进展}, |
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year={2022}, |
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volume={}, |
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number={9}, |
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pages={}, |
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doi={10.11834/jig.220540} |
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} |
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``` |
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``` |
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@ARTICLE{deng2022vivone, |
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author={L. -J. Deng, G. Vivone, M. E. Paoletti, G. Scarpa, J. He, Y. Zhang, J. Chanussot, and A. Plaza}, |
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journal={IEEE Geoscience and Remote Sensing Magazine}, |
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title={Machine Learning in Pansharpening: A Benchmark, from Shallow to Deep Networks}, |
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year={2022}, |
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volume={10}, |
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number={3}, |
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pages={279-315}, |
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doi={10.1109/MGRS.2022.3187652} |
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} |
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``` |
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## License |
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PanCollection is made available under the GPLv2.0 license. |
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## Contact |
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[email protected] |
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[email protected] |
