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  license: gpl-2.0
 
 
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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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  ---
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+
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+ # ✨ PanCollection
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+
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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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+
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+
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+ ## Recommendations
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+
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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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+
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+ ### Deploy
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+
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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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+
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+ ## How to Get Started with the Model
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+
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+
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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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+
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+ ## Training Details
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+
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+ See [Google Colab](https://colab.research.google.com/drive/1KpWWj1lVUGllZCws01zQfd6CeURuGL2O) for quick start.
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+
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+ See [Github Project](https://github.com/XiaoXiao-Woo/PanCollection) for coding details.
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+
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+ ## Evaluation
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+
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+ See the [Leaderboard](https://paperswithcode.com/dataset/worldview-3-pancollection) for model results.
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+
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+ See the [PanCollection Paper](https://liangjiandeng.github.io/papers/2022/deng-jig2022.pdf) for early results.
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+
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+
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+
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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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+
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+
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+ ## Citation
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+
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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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+ ```
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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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+ ```
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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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+
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+
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+ ## License
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+
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+ PanCollection is made available under the GPLv2.0 license.
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+
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+ ## Contact
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+
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