Brothers and sisters into AI video, AI 3D, and Three.js! I went through every repo I’ve starred — here they are, 8 in total. Bookmark them!

1. img2threejs (~18,600 stars) Rebuilds objects from a reference image as code-only three.js 3D objects — with quality gates, and ready for animation right out of the box. https://github.com/img2threejs/img2threejs…

2. Motion2MixamoRig (~1,400 stars) Retargets human motion from video onto 3D characters rigged with Mixamo. A budget-friendly stand-in for motion capture. https://github.com/MaxLiu22/Motion2MixamoRig…

3. dsh-blender-plugin (~1,000 stars) A plugin that lets AI drive Blender modeling in real time — comes with 15 modeling tools and modeling skills built in. https://github.com/sixtysevenlf/dsh-blender-plugin…

4. dioramas (~420 stars) An open-source framework for building cinematic, interactive 3D websites from AI-generated assets. Built on three.js and WebGL. https://github.com/blendi-remade/dioramas…

5. video-shotcraft (~12,800 stars) Video skills for Claude Code and Codex. Produces cinematic product videos entirely through Remotion code — ships with 152 shot recipe cards. https://github.com/Vincentwei1021/video-shotcraft…

6. lemo-opuscar (~5,000 stars) A short-film skill that needs no video model. Pick a style and generate the film purely in code — 51 cinematic styles to choose from. https://github.com/lemomo-ai/lemo-opuscar…

7. jianying-headless (~3,600 stars) A headless editor and exporter for JianYing (CapCut) drafts, packaged as an Agent Skill. Batch-processes drafts without ever opening the app. https://github.com/mcncarl/jianying-headless…

8. mg-styles-15 (~1,700 stars) 15 MG motion graphics styles — finished videos, prompts, and source code all included. Reverse-engineer them to learn. https://github.com/Vincentwei1021/mg-styles-15…

img2threejs/img2threejs

Source: https://github.com/img2threejs/img2threejs

img2threejs

Rebuild the object in a reference image as a code-only, procedural Three.js model. Quality-gated, animation-ready, and deliberately token-efficient — reconstruction-by-code, not photogrammetry, mesh extraction, or downloaded art packs.

License: Apache 2.0 · Version · PRs welcome

Runtime · Tooling · Sponsor · Scripts

Sponsored by Atlas Cloud · Sponsored by Tripo · Sponsored by Hyper3D

DAILY · WEEKLY · Python · All languages

Reference images reconstructed in code as animation-ready Three.js models, running live in the browser.

→ Open the Live Demo Gallery

Every model in the gallery is generated code, running in your browser. No mesh files, no downloads.

Live demos

Reconstructions built entirely from primitives, procedural shaders, and generated geometry. Open any model to orbit it, inspect its reference, and read the generated source.

The newest finished demos, generated from the gallery’s demos.json by scripts/ci/showcase_table.py. The gallery also has work in progress.

Built with is the version tag in each demo’s own generatedWith record (— when it names none).

The gallery source lives in img2threejs/img2threejs-showcase.

If this project is useful, a star on this repo helps others find it.

What it does

You give it one reference image of an object. It produces a THREE.Group factory written in TypeScript that recreates that object from primitives, procedural shaders, and generated geometry — with a runtime hierarchy (pivots, sockets, colliders) so the result is ready to animate, not an inert lump.

It runs under Hermes, Claude Code, Codex, or OpenCode. It is agent-agnostic: wherever the docs say “agent vision” or “agent browser tool”, it uses whatever the host provides — native image reading, a browser MCP, the project preview, or a user-supplied screenshot.

Subjects and detail accuracy

• Objects and characters. Each subject is classified object, character, or hybrid. Objects follow the hard-surface pipeline; characters route through an anatomy-aware track (head-unit proportions, facial landmarks, pose) documented in grimoire/character/reconstruction.md.
• Detail-first analysis. Before code generation the pipeline enumerates a detailInventory of identity-defining small details (gloss, bevel/rounding, screws/rivets, engraved or painted linework, contours, stains and wear). Every detail must map to a real component or material entry, and a strict-quality gate blocks generation until the inventory is complete. Taxonomy: grimoire/intake/detail_inventory.md.
• Maximum likeness for a specific person or character. An opt-in projection-first path fits a parametric template to image landmarks, de-lights the photo, camera-matches the render, and projects the reference onto the mesh. A single image cannot guarantee 100 percent likeness, so the pipeline reports per-region confidence and asks for more views when it matters. Details: grimoire/character/likeness_maximization.md.
• Multi-view silhouette carving. An opt-in geometryDescriptor.visualHull intersects at least two deterministic orthographic binary silhouettes into a bounded, welded voxel mesh. It records unseen areas as low-confidence rather than inventing hidden detail. Schema and runtime check: grimoire/scripts.md.
• CS2 weapon review gates. Knife and Glock-18 routes use family-specific component contracts. The review records exactness tier, family identity, painted-region and projection coverage, per-region confidence, approximation notes, and versioned review-scene metadata; component-coverage and map-stripped blockout gates prevent a convincing texture from standing in for real structure. Ships with the CS2 domain plugin; see its docs/cs2/review-gates.md.
• Resumable local workflow. forge/state.py records an ordered, evidence-backed intake/pass checklist for the generic profile and every registered domain (in-repo character, plus installed domain plugins such as CS2 and animated-character from plugin-character). forge/next.py --state resumes from that checklist while the existing spec, render, and review gates remain authoritative.
• Material reference pipeline. Every visible material region can be cropped, analyzed, resolved against the versioned Three.js material registry, fitted into ObjectSculptSpec, rendered from controlled camera views, and accepted only after a per-region comparison gate. See docs/materials/README.md.
• Python-assisted browser rendering. Python may orchestrate camera batches, hashes, manifests, and deterministic diagnostics, but the target browser Three.js route remains the rendering authority. See grimoire/build/python_threejs_render_bridge.md.

How it works

A staged sculpting pipeline turns the reference image into a spec, then generates and vision-reviews one build pass at a time — blockout → structural → form → material → surface → lighting → interaction → optimization — self-correcting until every identity-defining feature clears its threshold. Deterministic Python scripts handle validation and gating; model tokens are spent only on visual judgment and code.

→ Full pipeline diagram, gates, self-correction logic, script reference, and the token-efficiency design: docs/ARCHITECTURE.md

Quick start

Needs Node.js ≥ 18, Git and Python ≥ 3.10, and one of Claude Code, Codex, OpenCode or Hermes.

1. Install the base skill

npx --yes img2threejs@latest install        # links the skill into every agent it finds
npx --yes img2threejs@latest doctor         # one line per agent: "managed" means installed

Hermes users, also link the skill into your profile (the installer only writes ~/.hermes/skills/):

ln -sfn ~/.hermes/skills/img2threejs ~/.hermes/profiles/${HERMES_ACTIVE_PROFILE:-img2threejs}/skills/img2threejs

Then restart your agent and go to step 4.

Prefer to let your agent install it, want a manual or single-agent install, or something failed: docs/INSTALL.md (paste-to-agent prompt, expected output, troubleshooting, update and uninstall, other agents such as Cursor).

2. Install the plugin harness, if needed

Skip this unless you need a plugin from the table below. Plugins come from a separate CLI, the img2 harness (~/.img2); install it once:

npx --yes @img2threejs/img2@latest install --yes
npx --yes @img2threejs/img2@latest plugins   # the live catalog

It links an img2 command if ~/.local/bin, /opt/homebrew/bin or /usr/local/bin is on your PATH; otherwise use the npx --yes @img2threejs/img2@latest form, or alias img2='npx --yes @img2threejs/img2@latest'.

What it changes on your machine: docs/INSTALL.md §3.

3. Choose plugins — do not install everything by default

The table above is generated from the live catalog (scripts/ci/plugin_table.py); list all plugins with img2 plugins. Open each plugin’s linked README for its input requirements, dependencies and tool setup.

Example (the cs2 plugin; substitute any catalog id):

img2 add cs2 --yes
img2 list
img2 doctor
img2 sync --check

An installed domain plugin contributes its checklist steps, evidence collection, spec augmentation (quality floors merge raise-only), and blocking review gates. With no plugins installed, the base has generic and character profiles. A profile whose plugin is missing (cs2, animated-character) fails loud naming what is installed; it never silently downgrades.

The base skill is not a plugin: do not use img2 add to install this repository.

Private environment plugin: needs a GitHub account with access to its repository and working Git credentials. The public img2-environment installer can bootstrap the harness but does not grant that access. Hermes users link each plugin by hand (docs/INSTALL.md §3).

Why a run cannot see an installed plugin, and how plugins reach the pipeline: docs/PLUGINS.md.

To write a plugin, follow WRITING_A_PLUGIN.md.

4. Run a reconstruction in your agent

Restart the agent (or start a new session) after installing skills.

In Claude Code, attach an image or give its path and invoke:

/img2threejs Rebuild the object in ./reference.png as a procedural Three.js model. Keep its proportions, silhouette and colours. Follow the quality gates. Report the output files, render-review evidence and any inferred regions.

In another host, ask the agent to use the installed img2threejs skill with that image.

For a plugin workflow, name the profile explicitly, for example:

Use img2threejs with the installed cs2 domain and ./reference.png. Follow the cs2 profile and its family-specific reconstruction and review gates.

Use img2threejs with the installed character plugin and ./reference.png. Follow the animated-character profile. Do not claim animation readiness until its rig gates pass.

The agent validates the image, writes an assessment and spec, generates the factory pass by pass, and reviews rendered comparisons. Installation alone does none of that.

For a multi-session reconstruction, run these from the skill root:

python3 forge/state.py init --reference --profile character --spec object-sculpt-spec.json
python3 forge/next.py --state .img2threejs/state.json

5. Audit and maintain the installation

npx --yes img2threejs@latest doctor    # base-skill host/link report
img2 doctor                           # static audit of registered plugins
img2 update cs2 --check               # read-only check for a newer plugin version
img2 update cs2                       # install a newer available plugin version
img2 remove cs2                       # unlink owned links and back up the managed checkout

Neither doctor command proves visual likeness or animation quality; those require the reconstruction’s render and domain gates. img2 update --check exits 1 when an update is pending, not only on errors. Local --link checkouts are live and are not fetched by update.

Symptoms and fixes: docs/INSTALL.md §6; plugin audit exit codes and replacement behaviour: the [img2 README](https://github.com/img2threejs/img2#refs-replacement-and-common-refus