Upload folder using huggingface_hub
Browse files- .gitattributes +5 -0
- README.md +111 -1
- data/index.sqlite +3 -0
- data/vectors/index.faiss +3 -0
- data/vectors/vectors.f32 +3 -0
- extra/extra.sqlite +3 -0
- extra/vectors/vectors.f32 +3 -0
.gitattributes
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# Video files - compressed
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*.mp4 filter=lfs diff=lfs merge=lfs -text
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# Video files - compressed
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*.mp4 filter=lfs diff=lfs merge=lfs -text
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*.webm filter=lfs diff=lfs merge=lfs -text
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data/index.sqlite filter=lfs diff=lfs merge=lfs -text
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data/vectors/index.faiss filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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language:
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- en
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tags:
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- 3d
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- text-retrieval
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- asset-metadata
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- sqlite
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- faiss
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---
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# ObjectAtlas Data
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A prebuilt asset index and vector library for searching individual 3D objects with natural language. Descriptions from Cap3D, MARVEL-40M+, and TRELLIS-500K are grouped by asset, preserving their annotation sources and original fields.
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This bundle contains metadata and description embeddings. Model files can be obtained through the download locations stored in the asset records.
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## Contents
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| File | Purpose | Size |
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|---|---|---:|
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| `data/index.sqlite` | Asset metadata, captions, and vector ID mappings | 13.17 GiB |
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| `data/vectors/index.faiss` | FAISS index for description retrieval | 1.43 GiB |
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| `data/vectors/vectors.f32` | Full precision description vectors for reranking | 39.46 GiB |
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| `extra/extra.sqlite` | Extra asset metadata, archive manifest, and vector ID mappings | 0.14 GiB |
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| `extra/vectors/vectors.f32` | Precomputed description vectors for extra assets | 0.29 GiB |
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The five files total approximately **54.49 GiB**. Keep each collection's metadata and vector files together to preserve their ID mappings.
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| Collection | Assets | Description vectors |
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|---|---:|---:|
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| Main database | 1,842,649 | 13,792,908 |
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| Extra database | 10,840 | 102,896 |
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```text
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artifacts/
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README.md
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data/
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index.sqlite
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vectors/
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index.faiss
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vectors.f32
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extra/
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extra.sqlite
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vectors/
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vectors.f32
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```
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## Use with ObjectAtlas
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Place this bundle under the ObjectAtlas code directory as `artifacts/`, keeping the layout above. Install the dependencies listed in the code project's `requirements.txt`, then run from that project directory:
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```bash
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python scripts/search.py --text "a wooden dining chair" --top-k 10
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```
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If the data is stored elsewhere, use `--data` to specify the directory containing `data/`. Search results contain the asset record, similarity score, and best matching caption. The code project's README describes all search parameters.
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The first text query may download the encoder. After it is cached, `--local-files-only` enables offline queries.
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## Asset metadata
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The `assets` table in `data/index.sqlite` contains five fields:
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| Field | Description |
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|---|---|
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| `uuid` | Stable local asset identifier |
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| `source_dataset` | Original asset dataset, such as `objaverse`, `objaverse_xl`, or `abo` |
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| `original_id` | Original model ID, stored as a string with leading zeros and case preserved |
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| `captions` | Descriptions grouped under `cap3d`, `marvel_40m_plus`, and `trellis_500k`; each item contains `text` and the original `field` |
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| `download_urls` | Individual asset file locations |
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`captions` and `download_urls` are stored as JSON text in SQLite. Missing caption sources use empty lists. The search script decodes these fields into objects and arrays.
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Assets are matched by their confirmed original dataset and model identity. Similar captions, names, or categories do not establish asset identity. A single asset can have multiple description vectors, and search returns each asset once using its highest matching score.
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## Vector format
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| Setting | Value |
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|---|---|
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| Encoder | `sentence-transformers/all-mpnet-base-v2` |
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| Model revision | `e8c3b32edf5434bc2275fc9bab85f82640a19130` |
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| Dimensions | `768` |
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| Maximum sequence length | `384` tokens |
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| Normalization | Unit length |
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| Raw format | Headerless, row-major, little-endian float32 (`<f4`) |
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| Similarity | Cosine similarity |
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The SQLite caption table and vector segment metadata link vector IDs to assets and their descriptions. Use the supplied search script to retrieve candidates from FAISS and rerank them with the full precision vectors.
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## Optional extra data
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The main database can be searched independently. The included extra collection supports Toys4k, OmniObject3D, and selected ShapeNet categories whose models are distributed in archives.
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To install extra assets, use the code project's `extra/run_extra.py` to download official archives, extract them, verify local assets, and merge passing records and their vectors into the main database. Original extra records are retained. Merged file locations use `file://` URLs computed for the user's machine.
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## Sources and licenses
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Descriptions come from [Cap3D](https://huggingface.co/datasets/tiange/Cap3D), [MARVEL-40M+](https://huggingface.co/datasets/sankalpsinha77/MARVEL-40M), and [TRELLIS-500K](https://huggingface.co/datasets/JeffreyXiang/TRELLIS-500K).
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| Original asset source | Official resource |
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|---|---|
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| Objaverse / Objaverse-XL | [Objaverse](https://objaverse.allenai.org/), [Objaverse-XL metadata](https://huggingface.co/datasets/allenai/objaverse-xl) |
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| ABO | [Amazon Berkeley Objects](https://amazon-berkeley-objects.s3.amazonaws.com/index.html) |
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| GSO | [Google Scanned Objects](https://research.google/blog/scanned-objects-by-google-research-a-dataset-of-3d-scanned-common-household-items/) |
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| HSSD | [HSSD models](https://huggingface.co/datasets/hssd/hssd-models) |
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| ShapeNet | [ShapeNetCore v2](https://huggingface.co/datasets/ShapeNet/ShapeNetCore), [ShapeNetCore GLB](https://huggingface.co/datasets/ShapeNet/shapenetcore-glb) |
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| Toys4k (extra) | [Official project](https://github.com/rehg-lab/lowshot-shapebias/tree/main/toys4k) |
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| OmniObject3D (extra) | [Official project](https://github.com/omniobject3d/OmniObject3D), [OpenXLab](https://openxlab.org.cn/datasets/omniobject3d/OmniObject3D-New) |
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The MIT license for ObjectAtlas runtime code does not replace the licenses of the underlying data. Metadata, descriptions, models, and vectors remain subject to the applicable source licenses and attribution requirements. Cap3D annotations are listed under ODC-By, MARVEL under CC BY-NC-SA 4.0, and TRELLIS metadata under MIT; original models remain subject to their publishers' and authors' terms.
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Review source licenses before using or redistributing this bundle, including any noncommercial restrictions and attribution requirements. Users are responsible for obtaining access to restricted sources such as ShapeNet and the official Toys4k downloads.
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