| --- |
| license: mit |
| task_categories: |
| - image-classification |
| tags: |
| - shape-recognition |
| - benchmark |
| - 3d-objects |
| - shapenet |
| pretty_name: ShapeY |
| size_categories: |
| - 100K<n<1M |
| --- |
| |
| # ShapeY |
|
|
| ShapeY is a benchmark that tests a vision system's **shape recognition capacity**. It |
| consists of ~68k images of 200 3D objects rendered from |
| [ShapeNet](https://shapenet.org/). |
|
|
| ShapeY is **not a training set**. It validates that an object recognition system has |
| developed a genuine capacity for shape understanding, using tasks that are hard for |
| systems that rely on texture or contrast cues instead of shape. |
|
|
| Code: <https://github.com/njw0709/ShapeY> |
|
|
| ## Contents |
|
|
| | Directory | Images | Description | |
| |---|---|---| |
| | `ShapeY200/<objname>/` | 68,200 total | The standard benchmark. | |
| | `ShapeY200CR/<objname>/` | 68,200 total | Contrast-reversed counterparts, for the CR experiment. | |
|
|
| 200 objects across 20 categories (10 objects per category), each rendered in 31 |
| transformation series of 11 views: 341 images per object, 68,200 per set. |
|
|
| **Images are grouped one directory per object** (200 directories of 341 images), |
| because the Hub does not allow more than 10,000 files in a single directory. The |
| benchmark code expects a single flat directory, so |
| [`scripts/download_data.py`](https://github.com/njw0709/ShapeY/blob/main/scripts/download_data.py) |
| flattens the tree after downloading. If you fetch the files yourself, collapse the |
| per-object directories before pointing `SHAPEY_IMG_DIR` at them -- filenames are |
| globally unique, so a flat merge is lossless. |
|
|
| ## Filename convention |
|
|
| ``` |
| <category>_<shapenet_id>-<axis><NN>.png |
| ``` |
|
|
| * `<axis>` is a non-empty subset of the five transformation axes `x`, `y`, `p`, `r`, `w` |
| (translation in x and y, pitch, roll, and scale/width), always in that canonical |
| order — 31 combinations in total. |
| * `<NN>` is the view index within the series, `01`–`11`, increasing distance from the |
| reference view. |
|
|
| Example: `airplane_1021a0914a7207aff927ed529ad90a11-pr03.png` is view 3 of the combined |
| pitch+roll series for that airplane. |
|
|
| The parser for these names is `shapeymodular.utils.ImageNameHelper.parse_imgname`. |
|
|
| ## Usage |
|
|
| ```bash |
| git clone https://github.com/njw0709/ShapeY && cd ShapeY |
| uv sync |
| uv run scripts/download_data.py --variant all --out data |
| export SHAPEY_IMG_DIR=$PWD/data/ShapeY200/dataset |
| export SHAPEY_IMG_DIR_CR=$PWD/data/ShapeY200CR/dataset |
| ``` |
|
|
| Or directly: |
|
|
| ```python |
| from huggingface_hub import snapshot_download |
| |
| snapshot_download( |
| repo_id="GamGyulNN/ShapeY", |
| repo_type="dataset", |
| allow_patterns=["ShapeY200/**"], |
| local_dir="data", |
| ) |
| # -> data/ShapeY200/<objname>/<objname>-<axis><NN>.png |
| ``` |
|
|
| Note the per-object subdirectories; flatten them before use (see above). |
|
|
| ## License |
|
|
| MIT for the benchmark itself. The renders are derived from ShapeNet — please also |
| observe [ShapeNet's terms of use](https://shapenet.org/terms). |
|
|
