Datasets:

suvadityamuk
/

amazon-berkeley-objects

license: cc-by-4.0
pretty_name: Amazon Berkeley Objects (ABO)
source_datasets:
  - original
task_categories:
  - image-classification
  - image-to-3d
tags:
  - amazon
  - products
  - 3d
  - images
  - ecommerce
  - abo
configs:
  - config_name: mvr
    data_files:
      - split: train
        path: mvr/train-*.parquet
  - config_name: listings
    data_files:
      - split: train
        path: listings/train-*.parquet
  - config_name: part_labels
    data_files:
      - split: train
        path: part_labels/train-*.parquet
  - config_name: images_small
    data_files:
      - split: train
        path: images_small/train-*.parquet
  - config_name: spins
    data_files:
      - split: train
        path: spins/train-*.parquet
  - config_name: images_original
    data_files:
      - split: train
        path: images_original/train-*.parquet
  - config_name: models_3d
    data_files:
      - split: train
        path: models_3d/train-*.parquet
  - config_name: benchmark_material
    data_files:
      - split: train
        path: benchmark_material/train-*.parquet
  - config_name: objects
    default: true
    data_files:
      - split: train
        path: objects/train-*.parquet

Amazon Berkeley Objects (ABO)

A Hugging Face packaging of the Amazon Berkeley Objects (ABO) dataset. The data content is the official CC BY 4.0 release from https://amazon-berkeley-objects.s3.amazonaws.com/index.html. This mirror changes only the packaging: files are grouped into typed Parquet shards, and every original media file is preserved byte-for-byte and never transcoded. Images use the datasets Image() feature, 3D product models use the native Mesh() feature (original GLB bytes), and part-label meshes are kept in their original .obj format — so the Hugging Face Dataset Viewer and datasets streaming APIs can consume them.

Configs

Config	Row unit	Main fields
`objects` (default)	One product	Listing summary, foreign keys, modality flags
`listings`	One product listing	Typed fields plus lossless `raw_listing_json`
`images_small`	One catalog image	256 px `Image()`, `image_id`, dimensions, path
`images_original`	One catalog image	Original-resolution `Image()`, dimensions, path
`spins`	One turntable frame	`Image()`, `spin_id`, `image_id`, `azimuth`
`models_3d`	One 3D product	Native `Mesh()` GLB and geometry/material stats
`part_labels`	One part file	Original `.obj` part-mesh bytes (verbatim) or `relation.json`; keyed by `item_id`/`part_id`
`benchmark_material`	One model-viewpoint file	Render/material `Image()` or EXR `blob`, `kind`
`mvr`	One retrieval example	Official CVPR22 multi-view-retrieval split columns

models_3d uses the native Mesh() feature (requires a recent datasets release with mesh support). Part-label meshes are stored in their original .obj format under part_labels, alongside each item's relation.json. Note: the Hugging Face Dataset Viewer does not yet render the Mesh feature; 3D models can still be previewed via the Hub's per-file viewer and loaded through datasets.

Licensing

This work is licensed under the Creative Commons Attribution 4.0 International Public License (CC BY 4.0). A verbatim copy is provided in LICENSE-CC-BY-4.0.txt; see also https://creativecommons.org/licenses/by/4.0/.

Under the following terms:

Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Changes made: the original release was repackaged into typed Parquet shards (Image()/Mesh() features) for the Hugging Face Dataset Viewer and datasets. No underlying data content was altered.

Note: the source S3 bucket root also contains a LICENSE-CC-BY-NC-4.0.txt file, but the official ABO download page licenses the released archives under CC BY 4.0, which is the license applied and mirrored here.

Attribution

Credit for the data, including all images and 3D models, must be given to:

Amazon.com

Credit for building the dataset, archives and benchmark sets must be given to:

Matthieu Guillaumin (Amazon.com), Thomas Dideriksen (Amazon.com), Kenan Deng (Amazon.com), Himanshu Arora (Amazon.com), Arnab Dhua (Amazon.com), Xi (Brian) Zhang (Amazon.com), Tomas Yago-Vicente (Amazon.com), Jasmine Collins (UC Berkeley), Shubham Goel (UC Berkeley), Jitendra Malik (UC Berkeley).

No endorsement by Amazon.com or UC Berkeley of this mirror is claimed or implied.

Citation

@article{collins2022abo,
  title={ABO: Dataset and Benchmarks for Real-World 3D Object Understanding},
  author={Collins, Jasmine and Goel, Shubham and Deng, Kenan and Luthra, Achleshwar and
          Xu, Leon and Gundogdu, Erhan and Zhang, Xi and Yago Vicente, Tomas F and
          Dideriksen, Thomas and Arora, Himanshu and Guillaumin, Matthieu and
          Malik, Jitendra},
  journal={CVPR},
  year={2022}
}