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ShotSieve
What it is
ShotSieve is a free, open-source application for reviewing local photo folders and deciding which images to keep or reject. It uses learned image-quality models, with TOPIQ as the default and CLIPIQA and Q-ReAlign Mini also supported. Users can compare models on one library before a larger culling pass. Review tools filter and sort by score, format, resolution, file size, and metadata completeness, with batch actions. Listed capabilities include RAW photo support, blur detection, and AI quality scoring. Processing is local: the review interface runs on loopback at 127.0.0.1:8765 by default, while the photo library remains on the user’s machine. Releases target Windows, Linux, and Apple Silicon macOS. CPU is a fallback when accelerator requirements are not met. The application uses AGPLv3 or later; its PyIQA dependency and model checkpoints have separate commercial-use terms.
For and against
For
- Local-first photo review workflow
- Multiple learned quality models available
- Filters and sorts by several attributes
- Supports RAW photos and blur detection
- Runs on Windows, Linux, and macOS
Against
- Model weights require separate downloads
- Accelerator support depends on matching hardware
- Dependency and model licenses need review
- No third-party integrations are listed
The verdict
ShotSieve provides local, model-assisted culling with broad filtering and comparison tools. Review licensing terms and download requirements before commercial or offline use.
Who it suits
ShotSieve suits photographers and hobbyists narrowing large local photo folders while keeping libraries on their own machines. It supports users who want model comparison and batch review tools.
Plans and prices
Free and open source
AGPLv3+ · learned-IQA dependencies and model weights have separate terms
Read 4 Oct 2026 · github.com
On the record
- Compare
- Users can compare learned models on the same library before using one for a larger culling pass.github.com · read 4 Oct 2026
- Download platforms
- Packaged releases are listed for Windows, Linux, and Apple Silicon macOS, with CPU and supported accelerator runtime options.github.com · read 4 Oct 2026
- Hardware support
- Accelerator support depends on matching hardware, operating system, drivers, model, and runtime; CPU is the fallback when an accelerator is unavailable.github.com · read 4 Oct 2026
- Integrations
- No third-party service integrations are listed; model assets are obtained through the learned-IQA backend and stored in configured upstream caches.github.com · read 4 Oct 2026
- Intended users
- The project is aimed at photographers and hobbyists who want help narrowing large photo folders while keeping the workflow local.github.com · read 4 Oct 2026
- Licensing
- The application is licensed under AGPLv3 or later, while the pinned PyIQA package is PolyForm Noncommercial and model checkpoints have separate terms to review before commercial use.github.com · read 4 Oct 2026
- Local processing
- The project says the review UI runs on loopback and the photo library stays on the user's machine.github.com · read 4 Oct 2026
- Models
- The supported model catalog includes TOPIQ as the default, CLIPIQA for quick comparisons, and Q-ReAlign Mini.github.com · read 4 Oct 2026
- Notable limit
- Model weights are not bundled in release archives and must be downloaded separately when preparing or first using a model.github.com · read 4 Oct 2026
- Review tools
- Review supports filtering and sorting by score, format, resolution, file size, and metadata completeness, plus batch actions.github.com · read 4 Oct 2026
- Security and privacy
- The README describes a local-first workflow, with the review server binding to 127.0.0.1:8765 by default.github.com · read 4 Oct 2026
- What it does
- ShotSieve analyzes local photo folders with learned image-quality models and helps photographers review keep or reject decisions.github.com · read 4 Oct 2026
