pixcull 2.45.1

Local-first AI photo culling for professional photographers — 6-axis rubric, XMP/IPTC export, Lightroom & Capture One ready.

PixCull

Local-first AI photo culling for working photographers. Six calibrated scoring axes · burst folding · style-aware personalization · Lightroom / Capture One round-trip. No photo ever leaves your disk.

本地优先的 AI 摄影分拣:6 轴评分 · 连拍折叠 · 个性化学习 · Lr/C1 双向 round-trip, 原图永远不离开你的硬盘。

Install

pip install pixcull

Python 3.11–3.12. First run downloads the optional scoring models to ~/.pixcull/models/ (everything runs on-device; Apple-silicon accelerated).

Quickstart

# score a folder of photos (JPG / RAW) — keep/maybe/cull + per-axis rubric
pixcull run /path/to/photos -o ./out

# write the decisions back as XMP sidecars for Lightroom / Capture One
pixcull export ./out --xmp

# score a video → temporal windows + reel candidates
pixcull video clip.mp4 -o ./out

# fold near-duplicates, build a contact sheet, learn your taste, …
pixcull --help

# open the review workspace in your browser (v2.31 — now packaged)
pixcull serve

The pip package ships the full scoring engine, the CLI and the interactive review workspace: keyboard-first grid, ⌘K palette, per-axis "why" explanations, n-way compare, maybe-resolution queue, XMP export. pixcull serve stores runs under ~/.pixcull/runs by default (--root to change, --host 0.0.0.0 to share on a trusted LAN).

Highlights

• Glass-box scoring — every keep/cull carries a per-axis breakdown (technical / subject / composition / light / moment / aesthetic) and a plain-language "why", not just a number.
• Learns your taste — corrections feed a personal profile that tilts the axis weights toward what you demonstrably value.
• Burst & near-dup folding — stacks collapse to the peak frame with a one-key compare.
• Video too — temporal scoring, audio events (laughter / applause / music), reel-candidate detection with the same glass-box treatment.
• 13 UI languages, dark/light studio-neutral themes, WCAG-conscious.
• Local-first, always — no uploads, no cloud, no telemetry.

Links

• GitHub + full README
• Releases
• ModelScope mirror

MIT © Chris Chen