starnet2 vs Shottr
Side-by-side comparison for macOS
starnet2
7.0Removes stars from astrophotography images using ML models
Shottr
8.0Screenshot measurement and annotation tool
| Metric | starnet2 | Shottr |
|---|---|---|
| Category | Media & Design | Media & Design |
| AI Score | 7.0 | 8.0 |
| 30-day Installs | 8 | 2.8K |
| 90-day Installs | 19 | 7.3K |
| 365-day Installs | 77 | 21.1K |
| Version | 02,2023 | 1.9.1 |
| Auto-updates | No | Yes |
| Deprecated | No | No |
| GitHub Stars | — | 21 |
| GitHub Forks | — | - |
| Open Issues | — | 1 |
| License | — | GPL-3.0 |
| Language | — | — |
| Last GitHub Commit | — | 1y ago |
| First Seen | Feb 24, 2024 | Aug 9, 2023 |
Reviews
starnet2
starnet2 is a specialized app for astrophotographers that uses machine learning to remove stars from images, allowing users to focus on nebulas and galaxies. It is designed for those seeking advanced image processing in astrophotography.
Removes stars from astrophotography images using machine learning models.
Pros
- + Specialized for astrophotography, addressing a specific niche need.
- + Uses machine learning for effective and automated star removal.
- + Optimized for macOS, providing a tailored experience.
Cons
- - Lack of auto-updates may indicate limited maintenance.
- - Very niche, with low adoption and community support.
Shottr
Shottr is a screenshot measurement and annotation tool designed for precision and ease of use. It offers features like pixel-perfect measurements, customizable annotations, and integration with Alfred for workflow efficiency. Ideal for designers, developers, and anyone needing detailed screenshot analysis.
Shottr allows users to take screenshots, measure pixel distances, and annotate images with precision.
Pros
- + Integration with Alfred for efficient workflow
- + Active development and regular updates
- + Precise measurement and annotation features
- + User-friendly interface for screenshot management
Cons
- - Limited community discussion outside of Hacker News
- - Niche appeal may limit broad adoption