Metadata-Version: 2.4
Name: hsi-preprocessing-toolkit
Version: 1.1.5.dev4
Summary: HSI Preprocessing Toolkit
Author: songyz2023
Author-email: songyz2023 <songyz2023dlut@outlook.com>
License-Expression: AGPL-3.0-only
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: Implementation :: CPython
Requires-Dist: einops>=0.8.1
Requires-Dist: gradio>=5.35.0
Requires-Dist: matplotlib>=3.10.3
Requires-Dist: rasterio>=1.4.3
Requires-Dist: rs-fusion-datasets>=0.16.0
Requires-Dist: scipy>=1.15.3
Requires-Python: >=3.13
Project-URL: Documentation, https://github.com/songyz2019/hsi-preprocessing-toolkit#readme
Project-URL: Issues, https://github.com/songyz2019/hsi-preprocessing-toolkit/issues
Project-URL: Source, https://github.com/songyz2019/hsi-preprocessing-toolkit
Description-Content-Type: text/markdown

# HSI Preprocessing Toolkit

![](asset/screenshot.jpg)


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![GitHub Created At](https://img.shields.io/github/created-at/songyz2019/hsi-preprocessing-toolkit)
![GitHub License](https://img.shields.io/github/license/songyz2019/hsi-preprocessing-toolkit)


A Hyperspectral Preprocessing Toolkit that
1. Read the raw data from the HSI camera, and convert it into `.mat` file
2. Read the `.mat` file
3. Preview HSI, and convert it to RGB `.png` file
4. Crop and rotate the HSI and preview in realtime
5. Select spectrals of interest visually and save them into a `.mat` file
6. Mix multiple HSI image with layers. (coming in v2.0.0, now availabe in git)


## Usage
### Manual
1. Download from GitHub release
2. Double click the `start.cmd` file. Make sure you have internet access during the first start.

### Install with pip
```sh
pip install hsi-preprocessing-toolkit
hsi_preprocessing_toolkit
```

### Install with uv
```sh
uvx hsi_preprocessing_toolkit
```
or install as a tool
```sh
uv tool install hsi-preprocessing-toolkit
hsi_preprocessing_toolkit
```


## Credit
1. [uv](https://docs.astral.sh/uv/) for providing a new reliable solution for Python application distribution.  
2. `gradio` for modern Python Data Science UI 
3. `rasterio` for remote sensing data reading
4. `scipy`, `numpy`, `matplotlib` and `einops`
5. For more projects, see `pyproject.toml`


## License

```text
Copyright (C) 2025  songyz2019

This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU Affero General Public License for more details.

You should have received a copy of the GNU Affero General Public License
along with this program.  If not, see <https://www.gnu.org/licenses/>.
```