No. 18 of 29 ·AI Photo Culling Software

ShotSieve

Windows · Mac · Linux

Freedom report

Two barsScore 5.3

Free tierA free tier is on its own pricing page
Open codeNo open-source code on record
Runs widely3 of 6 device platforms
DocumentedThinly documented

ShotSieve is ranked #18 of 29 in AI photo culling software on Freedom251. It runs on Linux, macOS, Windows. There is a free plan.

ShotSieve plans and pricing

All plans

Free and open source Free AGPLv3+ · learned-IQA dependencies and model weights have separate terms github.com · 4 Oct 2026

Compared on AI photo culling software

AI quality scoring: Yes
RAW photo support: Yes
Blur detection: Yes

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The record

What it does: ShotSieve analyzes local photo folders with learned image-quality models and helps photographers review keep or reject decisions.
Local processing: The project says the review UI runs on loopback and the photo library stays on the user's machine.
Models: The supported model catalog includes TOPIQ as the default, CLIPIQA for quick comparisons, and Q-ReAlign Mini.
Review tools: Review supports filtering and sorting by score, format, resolution, file size, and metadata completeness, plus batch actions.
Compare: Users can compare learned models on the same library before using one for a larger culling pass.
Integrations: No third-party service integrations are listed; model assets are obtained through the learned-IQA backend and stored in configured upstream caches.
Security and privacy: The README describes a local-first workflow, with the review server binding to 127.0.0.1:8765 by default.
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.
Download platforms: Packaged releases are listed for Windows, Linux, and Apple Silicon macOS, with CPU and supported accelerator runtime options.
Notable limit: Model weights are not bundled in release archives and must be downloaded separately when preparing or first using a model.
Hardware support: Accelerator support depends on matching hardware, operating system, drivers, model, and runtime; CPU is the fallback when an accelerator is unavailable.
Intended users: The project is aimed at photographers and hobbyists who want help narrowing large photo folders while keeping the workflow local.
Price from: Free

Where it ranks on Freedom251

Best AI Photo Culling Software in 2026#18 of 29

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Sources

github.com/cfelicio/ShotSieve· checked 4 Oct 2026