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PaddleRS has collected and summarized the most commonly used open source datasets in the field of remote sensing, providing the following information for each data set: dataset description, image information, annotation information, source address, and AI Studio backup link. According to the task type, these data sets can be divided into image classification, image segmentation, change detection, object detection, object tracking, multi-label classification, image generation, and other types. Currently, the collected remote sensing datasets include:
- 32 image classification datasets;
- 40 object detection datasets;
- 70 image segmentation datasets;
- 28 change detection datasets;
- 7 instance segmentation datasets;
- 3 multi-label classification datasets;
- 9 object tracking datasets;
- 3 image caption datasets;
- 8 image generation datasets.
Visit Remote Sensing Data Set Summary for more information.
- The CHN6-CUG dataset is provided by Professor Qiqi Zhu from China University of Geosciences. Please refer to this website for more information.