huangserva/3DCellForgePublic

AI-powered interactive 3D model generation, inspection, and presentation studio.

AI summary: An open-source toolkit for generating and analyzing 3D cellular models from microscopy data.

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JavaScriptMITCreated May 10, 2026Last push 2mo ago+9 stars this week+11 this month

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since May 10, 2026
01K2KMay 2026Jun 2026Jul 2026Aug 2026
2.6K stars as of Aug 7, 2026, tracked back to May 10, 2026. Historical curve reconstructed from public GitHub event archives, calibrated to the current total.

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23 commits in the last yearLessMore

Signals and awards

derived from tracked data
  • Permissive license

    MIT

What 3DCellForge does

3DCellForge is a software suite designed for computational biologists and researchers working with 3D microscopy images. It provides algorithms to segment, reconstruct, and analyze individual cells in three dimensions. The toolkit can extract morphological features, track cell movement over time, and generate synthetic cellular environments for simulation. It aims to streamline the complex pipeline of processing large-scale 3D biological data.

Computational biologists, bioinformaticians, and microscopy researchers. Requires familiarity with Python and scientific computing libraries.

  • 3D Segmentation: Accurately identifies cell boundaries in volumetric data.
  • Morphological Analysis: Extracts features like volume, surface area, and shape descriptors.
  • Cell Tracking: Follows individual cells across time-lapse 3D datasets.
  • Synthetic Generation: Creates realistic 3D cell models for algorithm testing.
  • Extensible API: Allows researchers to integrate their own processing algorithms.

Where teams use it

Biomedical Research

Analyze cell behavior in 3D environments like tissue models.

Drug Discovery

Quantify the effects of compounds on cell morphology.

Computational Biology

Generate synthetic data to train new machine learning models.

Microscopy Image Processing

Automate the analysis of large 3D image datasets.

Getting started: pip install 3dcellforge

README

main branch

3D Model Studio

English | 中文

AI-powered interactive 3D model generation, inspection, and presentation studio.

3D Model Studio is a React + Three.js prototype for turning uploaded reference images or GLB files into a polished interactive 3D workspace. It supports live WebGL orbit controls, a left model library / center stage / right tools workbench, screenshots, GLB export, collapsed upload history, demo presentation mode, a generation queue, and optional image-to-3D providers for generating real 3D models from uploaded reference images.

Demo

3D Model Studio demo

Open the demo video: Demo MP4

Features

  • Interactive model viewer built with React Three Fiber.
  • Three-column workbench: Model Library on the left, WebGL stage in the center, asset/generation tools on the right.
  • Drag to rotate, scroll to zoom, isolate structure parts, inspect model details, and export the current scene.
  • Object-aware inspector with inferred category, source, provider state, material focus, demo value, and tags for vehicles, aircraft, vessels, products, artifacts, and organic specimens.
  • Model quality score for generated GLBs, including file size, triangle count, texture count, and demo readiness.
  • Demo Mode for screenshots and screen recordings: hides side panels, uses object-aware cinematic camera paths, and shows a clean presentation overlay.
  • Productized Model Library drawer with source thumbnails, provider/status, task id, GLB URL actions, comparison, and delete controls.
  • Saved Assets stays collapsed by default, while the active generated/imported asset stays pinned and clickable.
  • Generated/imported models are restored after refresh through IndexedDB, with localStorage as a compact fallback.
  • Generic part detail drawer, asset references, comparison panel, notes, gallery actions, logs, saved projects, and a compact generation queue.
  • Hyper3D, Tripo, Fal.ai, Hunyuan3D, JS Depth, and Local GLB generation/import modes.
  • Cached demo GLB models for offline-friendly screenshots and demos.
  • Auxiliary Khronos glTF reference models for GLB loader and PBR material checks.
  • API key stays server-side in .env.local; it is never exposed to the frontend bundle.

Tech Stack

  • React
  • Vite
  • Three.js
  • React Three Fiber
  • Drei
  • Framer Motion
  • Tripo API optional backend
  • Fal.ai optional backend
  • Hunyuan3D local API optional backend

Quick Start

npm install
npm run dev

Open the Vite URL shown in the terminal.

Workbench Workflow

The default screen is intentionally quiet:

  • Pick the active generated/imported asset from the left Model Library rail.
  • Earlier generated/imported models are tucked under Saved Assets until expanded.
  • Use the right Asset Source rail to choose the generation provider or import a local .glb / .gltf.
  • Watch upload/generation/import state in the left Generation Queue panel.
  • Click Info or Inspect only when you need the part detail drawer.
  • Open top-nav Library for the full asset catalog with previews, provider state, task ids, GLB URL copy, provider comparison, and deletion.
  • Click Demo in the top navigation to enter a clean presentation mode for screenshots and recordings.
  • Check the quality card on the stage before recording; low scores usually mean the source image or provider result is not demo-ready.
  • Demo animation adapts to the model name and metadata: cars use a road push-in, aircraft use a flight pass, ships/carriers use a naval cruise, and organic/specimen assets use a studio orbit.

Useful validation commands:

npm run lint
npm run build
npm run test
npm run test:visual

npm run test:visual runs Playwright layout and screenshot regression checks for the workbench, the Model Library drawer, and Demo Mode. Use npm run test:visual:update only when an intentional UI change needs new screenshot baselines.

Optional Image-to-3D Backend

To enable image-to-3D generation, create .env.local:

cp .env.example .env.local

Then set:

TRIPO_API_KEY=your_tripo_key
FAL_API_KEY=your_fal_key
RODIN_API_KEY=your_rodin_api_key
OPENAI_API_KEY=your_openai_key
API_HOST=127.0.0.1

OPENAI_API_KEY enables optional image understanding through /api/3d/analyze. When configured, uploads are classified by vision into asset type, material focus, inspection notes, scene profile, tags, and a better image-to-3D prompt. Without it, the app keeps using local filename/metadata heuristics.

For Hunyuan3D local backup mode, start your local Hunyuan3D API server and set:

HUNYUAN_API_BASE=http://127.0.0.1:8081
HUNYUAN_CREATE_PATH=/send
HUNYUAN_STATUS_PATH=/status

The 3D generation backend supports these provider paths:

Hyper3D  Hyper3D Rodin cloud generation only (default)
Tripo    Tripo cloud generation only
Fal      Fal.ai queue generation; model is selected in Settings
Auto     Hyper3D first, then Tripo, Fal, Hunyuan, and JS Depth backup
Hunyuan  Local Hunyuan3D generation only

The upload panel exposes the full generation mode choice before picking a file:

Hyper3D     Hyper3D Rodin GLB generation
Tripo       Tripo cloud GLB generation
Fal         Fal.ai queue GLB generation
Hunyuan     Local Hunyuan3D GLB generation
JS Depth    Browser-side image relief with layered PNG fallback
Auto        Hyper3D, Tripo, Fal, Hunyuan, then JS Depth fallback
Local GLB   Import an existing .glb or self-contained .gltf

Tripo uploads use the current STS object-storage flow (/upload/sts/token) before creating an image_to_model task. Fal uploads use the official @fal-ai/client storage and queue APIs. Supported Fal models are Hunyuan3D v2, TRELLIS, TripoSR, Tripo3D v2.5, and Hyper3D Rodin. Pick the active Fal model in Settings. Rodin uploads use Hyper3D's multipart /rodin task API, then poll /status and cache the GLB returned by /download. Generated GLBs are cached by the Node backend under .generated-models/, so later views use the local copy instead of temporary provider URLs. The frontend model library is saved in IndexedDB, so successful generated/imported model records survive page refreshes.

You can also import a local .glb or self-contained .gltf from the New Upload button. Imported models become custom workspace models and are served from the same local cache.

Expected Hunyuan3D local API shape:

POST /send
GET  /status/:uid

The status response can return either a remote model URL or a base64 GLB field such as model_base64 / glb_base64. Base64 GLBs are cached under .generated-models/ and served by the Node backend.

Start the backend:

npm run dev:api

Then start the frontend:

npm run dev

The frontend talks to the local Node backend at http://127.0.0.1:8787 by default.

Demo Models

The repository includes cached generated GLB files under:

public/generated-models/

These make the demo usable without spending API credits on every run.

Reference Models

The Library panel includes remote Khronos glTF Sample Models as auxiliary references for material and loader checks:

  • Transmission Test, CC0, Adobe via Khronos.
  • Transmission Roughness Test, CC-BY 4.0, Ed Mackey / Analytical Graphics via Khronos.
  • Mosquito In Amber, CC-BY 4.0, Loic Norgeot / Geoffrey Marchal / Sketchfab via Khronos.

These are loaded from the archived Khronos sample repository and are not bundled into this repo.

Security

Do not put real API keys in frontend code. Keep secrets in .env.local, which is ignored by git.

License

MIT

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23 commits in the last 52 weeks.

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