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Tracefinity

Tracefinity is a self-hosted tool that generates 3D-printable Gridfinity bins from photos of your tools, tracing outlines automatically and producing custom…

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  • Tools & Utilities
Tracefinity is a self-hosted tool that generates 3D-printable Gridfinity bins from photos of your tools, tracing outlines automatically and producing custom bin models for hobbyists and workshop organizers who want printable storage, with a local object-detection model by default, optional Gemini support, and optional NVIDIA graphics processing unit acceleration.

    Platform availability

    Available on 2 of 9 platforms

    • Unraid
    • TrueNAS
    • Umbrel (not listed)
    • ZimaOS (not listed)
    • Proxmox (not listed)
    • Helm (not listed)
    • Mac (not listed)
    • Windows (not listed)
    • Linux (not listed)

    Health score?A 0-100 score computed nightly from four factors: maintained (40%: recent commits and steady activity), popular (25%: GitHub stars, log scale), easy to install (20%: platforms, install notes, setup guides, Docker image) and light to run (15%: minimum RAM, ARM support). When the source code has been checked, a fifth factor, security check (20%: automated scan for committed secrets, unsafe desktop-app settings, known-vulnerable dependencies and project hygiene; any serious finding caps it at 20), is added. Factors without data are left out and the rest are rescaled.

    71/100 Good

    Maintained
    100last commit 8 days ago
    Popular
    57682 GitHub stars
    Easy to install
    452 install platforms, install notes, Docker image
    Light to run
    502 GB minimum RAM

    Availability: platform listings confirmed today, links checked 17 days ago

    GitHub stars
    682
    Open issues
    18
    Last commit
    2026-10-07
    Latest release
    0.10.0
    License
    MIT
    Activity
    declining

    Checked 8 days ago - source: GitHub (tracefinity/tracefinity)

    Resources & Compatibility

    Minimum requirements: 2 GB RAM.

    Checked 17 days ago - source: Docker Hub image tags and published docs

    First-install notes

    • Optional detection backend and graphics processing unit acceleration A local object-detection model is used by default. Gemini can be enabled with an optional Google application programming interface (API) key, and NVIDIA graphics processing unit settings can accelerate local image processing. source
    • Docker quick start Run the default local-model container with: docker run -p 3000:3000 -v ./data:/app/storage ghcr.io/tracefinity/tracefinity source

    Fetched 7 days ago - each note links to its source

    Alternatives (1)

    • Tooltrace - Take a picture of your tools and instantly get custom shadowbox foam or gridfinity inserts.

    Checked 14 days ago - source: AlternativeTo

    Common questions

    Why might the Docker container fail to launch from the registry?

    The container may not launch without building locally first. The issue may be a repository or package visibility problem rather than a code change. The release and dev workflows tag the images correctly.

    Does enabling a remote tracer send my tool photos off my server?

    Remote tracers offload the saliency step to a hosted GPU. All OpenCV processing stays local. User photos transit the provider when a remote tracer is active.

    Are the documented RAM figures for one component or multiple components?

    The RAM figures are combined for the tracer and the U2-Net paper detection model. They were tested in Linux containers.

    Does auto-size grid preserve manual tool placement?

    Auto-size grid silently forces re-centring. There is no way to auto-fit the grid but place tools manually.

    Answers sourced from github.com, github.com, tracefinity.github.io

    Community

    Collected 16 days ago - public community threads