Install

focalcut needs Python 3.10 or later, with ffmpeg and ffprobe on PATH.

The GPU-free pipeline

pip install "git+https://github.com/isaacrowntree/focalcut"
focalcut --help

This installs numpy and OpenTimelineIO and nothing else. It covers contact sheets, the vision-judge library pipeline and timeline export.

Recap reels and effects

pip install "focalcut[reel] @ git+https://github.com/isaacrowntree/focalcut"

The reel extra pulls torch, transformers and the models’ dependencies (SAM 3, BiRefNet, Depth Anything V2, SigLIP 2). The subject pass and the SAM 3 effects want a CUDA GPU; two scoring workers fit a 12 GB card. Set FOCALCUT_DISABLE_CUDNN=1 if your torch build has broken cuDNN engines. Hardware covers what decodes, encodes and renders on which chip.

The SAM 3 engines

focalcut cut uses SAM 3 (facebook/sam3), a gated model. Accept its licence on Hugging Face and run hf auth login first.

pip install "focalcut[sam] @ git+https://github.com/isaacrowntree/focalcut"

SAM 3’s weights are under Meta’s own SAM Licence, separate from focalcut’s MIT licence.

The Claude Code skill

skills/focalcut is a Claude Code skill that lists each editing concept with the code behind it. It isn’t part of the pip package. To install it from a clone:

mkdir -p ~/.claude/skills && ln -s "$PWD/skills/focalcut" ~/.claude/skills/focalcut

From source

git clone https://github.com/isaacrowntree/focalcut && cd focalcut
python -m venv .venv && .venv/bin/pip install -e ".[reel,dev]"
.venv/bin/python -m pytest -q && .venv/bin/ruff check .