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---
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': image
'1': mask
splits:
- name: train
num_bytes: 1223473700.216
num_examples: 33412
- name: test
num_bytes: 86320426.0
num_examples: 2000
download_size: 797318222
dataset_size: 1309794126.216
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
# Dataset Card for Dataset Name
We used the \href{https://arxiv.org/abs/1503.02391}{ATR Dataset} for this task. The Active Template Regression (ATR) dataset comprises 18 semantic category labels, encompassing items such as face, sunglasses, hat, scarf, hair, upper clothes, left arm, right arm, belt, pants, left leg, right leg, skirt, left shoe, right shoe, bag, dress, and background. A total of 17,700 images were incorporated into the ATR dataset. 16,700 images were designated for training, and 1,000 for testing.
- **Curated by:** Xiaodan Liang, Si Liu, Xiaohui Shen, Jianchao Yang, Luoqi Liu, Jian Dong, Liang Lin, Shuicheng Yan
- **Shared by:** Xiaodan Liang, Si Liu, Xiaohui Shen, Jianchao Yang, Luoqi Liu, Jian Dong, Liang Lin, Shuicheng Yan
- **License:** MIT
# Dataset Sources
- **Repository:** https://github.com/lemondan/HumanParsing-Dataset
- **Paper:** Deep Human Parsing with Active Template Regression
# Human Parsing Labels
- 0: **background**
- 1: **hat**
- 2: **hair**
- 3: **sunglasses**
- 4: **upperclothes**
- 5: **skirt**
- 6: **pants**
- 7: **dress**
- 8: **belt**
- 9: **leftshoe**
- 10: **rightshoe**
- 11: **face**
- 12: **leftleg**
- 13: **rightleg**
- 14: **leftarm**
- 15: **rightarm**
- 16: **bag**
- 17: **scarf**
# Uses
Semantic segmentation, and more specifically, human body parsing.
# Dataset Card Authors
Christian Kotait
**BibTeX:**
@article{liang2015deep,
title={Deep human parsing with active template regression},
author={Liang, Xiaodan and Liu, Si and Shen, Xiaohui and Yang, Jianchao and Liu, Luoqi and Dong, Jian and Lin, Liang and Yan, Shuicheng},
journal={IEEE transactions on pattern analysis and machine intelligence},
volume={37},
number={12},
pages={2402--2414},
year={2015},
publisher={IEEE}
}
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