Local AI Culling
Local AI Culling is an open-source, offline image-culling application designed for professional photographers.
What Local AI Culling is
Local AI Culling is an open-source, offline image-culling application designed for professional photographers. It analyzes photo shoots and sorts images into KEEP, REVIEW, and REJECT folders for later editing in Lightroom or another editor. It groups visually identical shots taken close together, identifies high-speed bursts, and ranks frames within each burst. Its scoring covers focus, noise, composition, facial expressions, and editability. A local web dashboard lets photographers review selections, change thresholds, and see why a decision was made. By default, export uses hardlinks to organize files without copying or changing the originals; copy mode is configurable. The project says photos are not uploaded, cloud APIs are not used for image or metadata processing, and usage telemetry is not collected or transmitted. It supports Windows, macOS, and Linux, with acceleration depending on the system. Installation requires Python 3.10 or later, with Python 3.11 recommended. The project recommends 500–2,000 images per run; collections over 5,000 may increase memory use and slow duplicate processing.
Good
- Works offline without uploading images or telemetry.
- Sorts images into KEEP, REVIEW, and REJECT folders.
- Ranks frames in high-speed bursts.
- Dashboard explains decisions and allows threshold changes.
- Hardlink export leaves originals unmodified.
Watch out
- Requires Python 3.10 or later.
- CR3, compressed ARW, and HEIC support may be incomplete.
- Runs above 5,000 images may strain memory and slow processing.
- Lightroom Classic integration and video culling are postponed.
Who it suits
It suits professional photographers who want offline assistance sorting shoots before editing. Users should be comfortable installing Python and working within the documented image-format and batch-size limits.
Verdict
Local AI Culling combines offline image analysis, burst ranking, duplicate grouping, and a review dashboard for photographers preparing shoots for editing. Check its installation requirements, format support, and batch-size guidance before choosing it; it does not edit Lightroom catalogs or generate XMP sidecars.
The facts
Each one read from Local AI Culling's own pages, with the date it was checked.
What it does
- Burst ranking
- It identifies high-speed bursts and selects the best frame in each burst.checked 30 Sep 2026
- Culling features
- It detects duplicates and bursts, ranks burst frames, and assesses focus, noise, composition, and facial expressions.checked 30 Sep 2026
- Dataset limits
- The project recommends 500–2,000 images per run and warns that datasets over 5,000 images may use substantially more memory and process duplicates more slowly.checked 30 Sep 2026
- Dataset size
- The project recommends 500 to 2,000 images per run and warns that datasets over 5,000 images may cause memory pressure and slower duplicate processing.checked 30 Sep 2026
- Duplicate detection
- It groups visually identical photos taken moments apart.checked 30 Sep 2026
- Editor workflow
- The README says organized images can be edited in Adobe Lightroom or a preferred editor, while the limitations page says Lightroom Classic plugin integration is postponed.checked 30 Sep 2026
- Export
- The default hardlink export organizes files without duplicating or modifying the originals; copy mode is also configurable.checked 30 Sep 2026
- Feedback dashboard
- A local web dashboard lets photographers review decisions, adjust thresholds, and see why the AI made a decision.checked 30 Sep 2026
- Image evaluation
- Its scoring evaluates technical quality including focus, noise, composition, expressions, and editability.checked 30 Sep 2026
- Image-format limits
- Supported formats include JPG, JPEG, PNG, CR2, and NEF; CR3, compressed ARW, and HEIC may have incomplete support or metadata extraction.checked 30 Sep 2026
- Image formats
- Documented supported formats include JPG, JPEG, PNG, and standard CR2 and NEF RAW; CR3, compressed ARW, and HEIC may have incomplete support.checked 30 Sep 2026
- Installation
- Installation requires Python 3.10 or later, with Python 3.11 recommended, and an SSD is highly recommended.checked 30 Sep 2026
- Integration limits
- The documented v1.0 limitations say Lightroom Classic plugin integration and video culling are postponed, and the app does not edit Lightroom catalogs or generate XMP sidecars.checked 30 Sep 2026
- Intended users
- The application is built specifically for professional photographers.checked 30 Sep 2026
- License and fees
- The repository identifies the project as open source under the MIT License and says local operation eliminates subscription fees.checked 30 Sep 2026
- Other limitations
- The project says it does not edit Lightroom catalogs or generate XMP ratings, and video culling is postponed.checked 30 Sep 2026
- Privacy
- The security policy says images are not uploaded, cloud APIs are not used for image processing or metadata analysis, and usage telemetry is not collected or transmitted.checked 30 Sep 2026
- Purpose
- Local AI Culling is an open-source, offline AI-assisted image culling application built for professional photographers.checked 30 Sep 2026
- Support
- The project directs users to its documentation and GitHub Issues for help, bug reports, and feature requests.checked 30 Sep 2026
- Supported systems
- The README lists Windows, macOS, and Linux support, with platform-dependent CUDA, Metal/MPS, or CPU acceleration.checked 30 Sep 2026
- Workflow
- It analyzes photo shoots and organizes images into KEEP, REVIEW, and REJECT folders for editing in Lightroom or another editor.checked 30 Sep 2026
Where it runs
- Platforms
- The README lists Windows, macOS, and Linux support, with hardware acceleration where available and CPU fallback.checked 30 Sep 2026
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