Shine Stacker
ShineStacker is a focus stacking tool with an interactive GUI and a Python API, designed for advanced image processing workflows in macro photography and microscopy.
Key Features
- 🪟 Cross-Platform GUI: Native app built with Qt6, available for Windows, macOS, and Linux.
- 🚀 Batch Processing: Automatically align, balance, and stack hundreds of images — perfect for macro or microscopy datasets.
- 🧩 Modular Architecture: Combine configurable modules for alignment, normalization, and blending to build custom workflows.
- 🖌️ Retouch Editor: Interactively refine your stacked image by painting in details from individual frames.
- 📊 Jupyter & Python Integration: Use Shine Stacker as a library inside your Python or Jupyter workflows.
- 🎞️ Supported formats: TIFF 8-16 bits, PNG 8-16 bits, JPEG, most RAW formats via
rawpy.
Interactive GUI
The graphical interface makes complex stacking tasks simple:
- Project View – Configure, preview, and run stacking workflows with optional intermediate results.
- Retouch View – Manually refine the final image by blending details from selected frames and applying filters.
Ideal for users who want the power of scripting and the comfort of a modern UI.
Get Started
Demo video
Short demo of the new user interface introduced in Shine Stacker, release 1.13.0.
Resources
🌍 Website on WordPress • 📖 Main documentation • 📝 Changelog
Installation
See the main documentation for detailed installation instructions.
Platform notes:
- Windows: If you download the installer or ZIP archive, you may need to whitelist the app in your antivirus software.
- macOS: See the installation note for macOS users.
Acknowledgements & References
The first version of the core focus stack algorithm was inspired by the Laplacian pyramids method implementation by Sami Jawhar, used under permission. The implementation in the latest releases was rewritten from the original code.
Key references:
- Pyramid Methods in Image Processing, E. H. Adelson, C. H. Anderson, J. R. Bergen, P. J. Burt, J. M. Ogden, RCA Engineer, 29-6, Nov/Dec 1984 Pyramid methods in image processing
- A Multi-focus Image Fusion Method Based on Laplacian Pyramid, Wencheng Wang, Faliang Chang, Journal of Computers 6 (12), 2559, December 2011
License
-
Code: The software is provided as is under the GNU Lesser General Public License v3.0. See LICENSE for details.
-
Logo: The Shine Stacker logo was designed by Alessandro Lista. Copyright © Alessandro Lista. All rights reserved. The logo is not covered by the LGPL-3.0 license of this project.
Attribution request
📸 If you publish images created with Shine Stacker, please consider adding a note such as:
Created with Shine Stacker – https://github.com/lucalista/shinestacker
This is not mandatory, but highly appreciated.
Developed and maintained by Luca Lista. 💡 Contributions, feedback, and feature suggestions are warmly welcome. If you enjoy Shine Stacker, consider giving it a ⭐️ on GitHub — it really helps visibility!
1 maintainer
Metadata
1 maintainer
Release files for shinestacker 1.17.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| shinestacker-1.17.0.tar.gz | 30.1 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| shinestacker-1.17.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 30.7 MB
Release files / shinestacker-1.17.0.tar.gz
| Download URL | shinestacker-1.17.0.tar.gz |
|---|---|
| Size | 30.1 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.7
|
Release files / shinestacker-1.17.0-py3-none-any.whl
| Download URL | shinestacker-1.17.0-py3-none-any.whl |
|---|---|
| Size | 655.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.7
|
