News
* [2022-11-09] 🔥 We released PaddleRS v1.0. Please check the [Release Note](https://github.com/PaddlePaddle/PaddleRS/releases).
* [2022-05-19] 🔥 We released PaddleRS v1.0-beta. Please check the [Release Note](https://github.com/PaddlePaddle/PaddleRS/releases).
## 
Introduction
PaddleRS is an end-to-end high-efficent development toolkit for remote sensing applications based on PaddlePaddle, which helps both developers and researchers in the whole process of designing deep learning models, training models, optimizing performance and inference speed, and deploying models. PaddleRS supports multiple tasks, including **image segmentation, object detection, scene classification, and image restoration**.
Features
* 
**High-Performance Models**: PaddleRS provides 30+ deep learning models, including those reknowned in the computer vision field (e.g. DeepLab V3+, PP-YOLO) and those optimized for remote sensing tasks (e.g. BIT, FarSeg).
* **Support for Remote Sensing Tasks**: PaddleRS supports remote sensing tasks (e.g. change detection) and provides comprehensive training, deployment tutorials, as well as rich application examples.
* 
**Optimization for Large Image Tiles**: PaddleRS is optimized for the sliding window inference of large remote sensing images, using a *lazy-loading* strategy to improve performance. Also, the geospatial meta infomation for large tiles can be read and written.
* **Data Preprocessing for Geospatial Data**: PaddleRS provides preprocessing functions for multi-spectral and multi-temporal data, which are common in the remote sensing field. PaddleRS also supports the extraction and knowledge integration of more than 50 remote sensing indices.
* 
**High Efficiency**: PaddleRS provides multi-process asynchronous I/O, multi-card parallel training, evaluation, and other acceleration strategies, combined with the memory optimization function of the PaddlePaddle, which can greatly reduce the training overhead of deep learning models, all these allowing developers to train remote sensing deep learning models with a lower cost.
Community
* If you have any questions, suggestions, or feature requests, please do not hesitate to create an issue in [GitHub Issues](https://github.com/PaddlePaddle/PaddleRS/issues).
* Welcome to join PaddleRS WeChat group to communicate with us:
Overview
| Models | Data Transformation Operators | Remote Sensing Data Tools | Application Examples |
Change DetectionScene ClassificationObject DetectionImage Segmentation |
Data Preprocessing
Data Augmentation
Remote Sensing Indices
|
Data Format ConversionDataset Creation ToolData PostprocessingData Visualization |
Official ExamplesCommunity Examples |
Tutorials and Documents
* Quick Start
* [Quick start](./docs/quick_start_en.md)
* Data Preparation
* [Open-source remote sensing datasets](./docs/data/dataset_en.md)
* [Efficient interactive segmentation tool EISeg](https://github.com/PaddlePaddle/PaddleSeg/tree/release/2.7/EISeg)
* [Remote sensing data tools](./docs/data/tools_en.md)
* Introduction on Components
* [Data preprocessing tools](./docs/intro/data_prep_en.md)
* [Models](./docs/intro/model_zoo_en.md)
* [Remote sensing indices](./docs/intro/indices_en.md)
* [Data transforming operators](./docs/intro/transforms_en.md)
* [Model Training](./tutorials/train/README_EN.md)
* Model Deployment
* [Model export](./deploy/export/README.md)
* [Paddle Inference (Python)](./deploy/README.md)
* Development and Contribution
* [Contributing guides](./docs/CONTRIBUTING_EN.md)
* [Development manual](./docs/dev/dev_guide_en.md)
* [Code style guides](./docs/dev/docstring_en.md)
* [Training APIs](./docs/apis/train_en.md)
* [Inference APIs](./docs/apis/infer_en.md)
## 
Application Examples
* [Interactive intelligent interprementation tool GeoView](https://github.com/PaddleCV-SIG/GeoView)
* [Scientific research based on PaddleRS: designing a deep learning change detection model](./examples/rs_research/README.md)
* [Optimization method for semantic segmentation of small objects in remote sensing images based on PaddleRS](./examples/c2fnet/README.md)
For more application examples, please see [application examples of PaddleRS](./examples/README.md).
## License
PaddleRS is released under the [Apache 2.0 license](./LICENSE).
## 
Acknowledgement
* We would like to thank the National Earth Observation Data Center, Aerospace Information Research Institute, Beihang University, Wuhan University, China University of Petroleum, China University of geosciences, China Siwei Surveying and Mapping Technology Co., Ltd., PIESAT, GEOVIS, and SuperMap for their contributions to PaddleRS(names not listed in order).
* We appreciate the contributions of [geoyee](https://github.com/geoyee), [kongdebug](https://github.com/kongdebug), and [huilin16](https://github.com/huilin16).
## 
Citation
If you find our project useful in your research, please consider citing:
```latex
@misc{paddlers2022,
title={PaddleRS, Awesome Remote Sensing Toolkit based on PaddlePaddle},
author={PaddlePaddle Authors},
howpublished = {\url{https://github.com/PaddlePaddle/PaddleRS}},
year={2022}
}
```