https://github.com/aveygo/astrosleuth
The (only?) free, no-strings-attached, open source astrophotgraphy upscaler toolset.
https://github.com/aveygo/astrosleuth
Last synced: 2 months ago
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The (only?) free, no-strings-attached, open source astrophotgraphy upscaler toolset.
- Host: GitHub
- URL: https://github.com/aveygo/astrosleuth
- Owner: Aveygo
- License: agpl-3.0
- Created: 2023-04-02T08:21:01.000Z (about 2 years ago)
- Default Branch: master
- Last Pushed: 2024-07-24T05:50:08.000Z (10 months ago)
- Last Synced: 2024-07-24T07:06:50.319Z (10 months ago)
- Language: Python
- Homepage:
- Size: 997 KB
- Stars: 29
- Watchers: 2
- Forks: 5
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
---
title: AstroSleuth
emoji: 🌖
colorFrom: pink
colorTo: yellow
sdk: streamlit
sdk_version: 1.17.0
app_file: app.py
pinned: false
license: gpl-3.0
---
# AstroSleuth
[](https://github.com/Aveygo/AstroSleuth "Go to GitHub repo")
[](https://github.com/Aveygo/AstroSleuth)[](https://www.python.org/downloads/release/python-399/)
The (only?) free, no-strings-attached, open source astrophotgraphy upscaler toolset. I wanted a solution that can run on almost any hardware with epic results, and I hope this repo serves you well.
If you ever want to support the project, please give the repo a star so that it's easier for others to discover it.
## Running AstroSleuth
Quick start on [colab](https://colab.research.google.com/drive/1LxiNsnokF-6OmICSxWNvTeFEEZvRM2Lp?usp=sharing), but checkout [running](results/running.md) for more details.
## Extra information
- [Tips](results/tips.md) - for image samples and potential workflow improvements
- [Training](results/training.md) - for more information on each model
## Recent changes
- AstroNEXT and AstroFAST models to replace V2 and V1 respectively. Read [training](results/training.md) for more details.
- Minor UI changes for reading model descriptions.
- Scaled the preview image for faster loading.
- Ability to 'coerce' NEXT into stars vs details. See [conditioning](results/conditioning.md).
## Known issues
- Most models convert large stars into 'star clusters'
- Diffraction spikes may turn into diffraction stars
- Fine nebula details may "smush" together (varies from image-to-image)
## Why
I started this project a regrettably long time ago. I tried different ways to share my work, got some hate, some love, and setted for what you see now.
I present an acculmination of multiple ideas, improvements, and lessons; trained on 15 thousand images of various astrophotography targets.
It is behind my works on [reddit](https://www.reddit.com/user/CodingCoda), my [youtube](https://www.youtube.com/channel/UCHode4WV0hteze-ZDEG5atQ) attempt and my [cloudy nights post](https://www.cloudynights.com/topic/816869-astrosleuth-image-denoiser-upscaler/), and I hope it leads the way for any other future attempts; for anyone.
## Concerns and Personal Notes
A lot has happend throughout this project. I guess cause it was my first machine learning application and it's been a nice distraction every now and again.
Ask for any improvements and I will likely implement them. Any feedback is appreciated, such as creating a Photoshop/Pixinsight plugin? Just open a git issue [here](https://github.com/Aveygo/AstroSleuth/issues) and I'll see to it.
This tool is presented as is, free as long as it stays free. "Scientific accuracy" was never the goal of this project - it was made to help others, and to make astronomy a little easier.
