---
dataset_info:
  features:
  - name: image_id
    dtype: int64
  - name: image
    dtype: image
  - name: width
    dtype: int32
  - name: height
    dtype: int32
  - name: file_name
    dtype: string
  - name: annotations
    struct:
    - name: id
      list: int64
    - name: image_id
      list: int64
    - name: category_id
      list:
        class_label:
          names:
            '0': Quadruped Head
            '1': Quadruped Body
            '2': Quadruped Foot
            '3': Quadruped Tail
            '4': Biped Head
            '5': Biped Body
            '6': Biped Arm
            '7': Biped Leg
            '8': Biped Tail
            '9': Fish Head
            '10': Fish Body
            '11': Fish Fin
            '12': Fish Tail
            '13': Bird Head
            '14': Bird Body
            '15': Bird Wing
            '16': Bird Foot
            '17': Bird Tail
            '18': Snake Head
            '19': Snake Body
            '20': Reptile Head
            '21': Reptile Body
            '22': Reptile Foot
            '23': Reptile Tail
            '24': Car Body
            '25': Car Tire
            '26': Car Side Mirror
            '27': Bicycle Body
            '28': Bicycle Head
            '29': Bicycle Seat
            '30': Bicycle Tire
            '31': Boat Body
            '32': Boat Sail
            '33': Aeroplane Head
            '34': Aeroplane Body
            '35': Aeroplane Engine
            '36': Aeroplane Wing
            '37': Aeroplane Tail
            '38': Bottle Mouth
            '39': Bottle Body
    - name: category_name
      list: string
    - name: area
      list: float32
    - name: bbox
      list:
        list: float32
        length: 4
    - name: iscrowd
      list: int8
    - name: segmentation
      list:
        list: string
  splits:
  - name: train
    num_bytes: 1084245428
    num_examples: 8828
  - name: val
    num_bytes: 63772194
    num_examples: 519
  - name: test
    num_bytes: 121295570
    num_examples: 1040
  download_size: 1256961967
  dataset_size: 1269313192
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: val
    path: data/val-*
  - split: test
    path: data/test-*
task_categories:
- image-segmentation
pretty_name: d
---

# Dataset Card: PartInventory

## Summary
PartInventory is a fine-grained hierarchical instance-segmentation dataset derived from **SPIN** (built on **PartImageNet**). It provides detailed part annotations and serves as a **proof of concept** for exploring new annotation workflows and more efficient storage formats for large-scale instance segmentation.

## Citation
Please cite **SPIN and PartImageNet**:

**SPIN**  
```

@misc{myersdean2024spinhierarchicalsegmentationsubpart,
      title={SPIN: Hierarchical Segmentation with Subpart Granularity in Natural Images}, 
      author={Josh Myers-Dean and Jarek Reynolds and Brian Price and Yifei Fan and Danna Gurari},
      year={2024},
      eprint={2407.09686},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2407.09686}, 
}

```

**PartImageNet**  
```
@article{he2021partimagenet,
title={PartImageNet: A Large, High-Quality Dataset of Parts},
author={He, Ju and Yang, Shuo and Yang, Shaokang and Kortylewski, Adam and Yuan, Xiaoding and Chen, Jie-Neng and Liu, Shuai and Yang, Cheng and Yuille, Alan},
journal={arXiv preprint arXiv:2112.00933},
year={2021}
}

```

## Description
PartInventory refines SPIN annotations with more granular labels and updated hierarchies. It is intended to support research on part-level segmentation, hierarchical understanding, and efficient dataset representations (e.g., Parquet/Arrow).  

This release is an early, **proof-of-concept** version. Further expansions are planned.
```