# Asset Library Unified robotics and simulation asset library. This repository stores normalized reusable assets from RoboCasa, Discoverse, TinyForge, Hunter, and third-party asset sites. It is designed to be hosted as a Hugging Face Dataset. ## Layout Default normalized asset layout: ```text assets///// ``` Example: ```text assets/robocasa/fixtures/dishwashers/Dishwasher031/ ``` Collection-level imports are allowed when an upstream repository has many internal relative references: ```text assets/// ``` Current example: ```text assets/discoverse/models/ ``` Top-level repository structure: ```text . ├── AGENTS.md ├── README.md ├── assets/ │ ├── discoverse/ │ ├── hunter/ │ ├── robocasa/ │ ├── third_party/ │ └── tinyforge/ ├── docs/ │ ├── naming_spec.md │ ├── placement_asset_notes.md │ ├── source_notes/ │ └── storage_spec.md ├── manifest/ │ ├── assets.jsonl │ ├── licenses.yaml │ └── sources.yaml └── scripts/ ``` Naming rule: ```text ... ``` Example: ```text robocasa.fixtures.dishwashers.Dishwasher031 ``` ## Current seed assets - RoboCasa dishwasher fixtures: 25 MJCF assets under `assets/robocasa/fixtures/dishwashers/` - RoboCasa dishwasher support files: - fixture registry: `assets/robocasa/fixtures/fixture_registry/dishwasher.yaml` - implementation reference: `docs/source_notes/robocasa/dishwasher_fixture.py` - DISCOVERSE models collection: upstream `models/` tree under `assets/discoverse/models/` - stored as a collection-level asset to preserve internal relative references - includes MJCF, URDF, mesh, and reference image files Placement-related notes and candidate external links are tracked in: ```text docs/placement_asset_notes.md docs/source_notes/third_party.md ``` ## Index The global asset index is: ```text manifest/assets.jsonl ``` Each asset directory also contains a local `metadata.yaml`. ## Validate ```bash python scripts/validate_asset.py assets/robocasa/fixtures/dishwashers/Dishwasher031 python scripts/validate_asset.py --all ``` Current expected result: ```text validated_assets=26 ``` ## Upload to Hugging Face Login first: ```bash export HF_ENDPOINT=https://hf-mirror.com hf auth login ``` Create the dataset repo if needed: ```bash hf repo create / --type dataset --private ``` Upload: ```bash cd /path/to/asset-library scripts/upload_to_hf.sh / ``` ## Download from Hugging Face ```bash export HF_ENDPOINT=https://hf-mirror.com scripts/download_from_hf.sh / ./asset-library ```