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---
dataset_info:
  features:
  - name: idx
    dtype: string
  - name: Question
    dtype: string
  - name: Image
    dtype: image
  - name: Groundtruth
    dtype: string
  - name: Task
    dtype: string
  splits:
  - name: full
    num_bytes: 171585064.0
    num_examples: 490
  - name: HiddenText
    num_bytes: 107144174.0
    num_examples: 150
  - name: 3DCaptcha
    num_bytes: 399420.0
    num_examples: 150
  - name: Colorblind
    num_bytes: 11984769.0
    num_examples: 150
  - name: ChineseLigature
    num_bytes: 52056701.0
    num_examples: 40
  download_size: 343068512
  dataset_size: 343170128.0
configs:
- config_name: default
  data_files:
  - split: full
    path: data/full-*
  - split: HiddenText
    path: data/HiddenText-*
  - split: 3DCaptcha
    path: data/3DCaptcha-*
  - split: Colorblind
    path: data/Colorblind-*
  - split: ChineseLigature
    path: data/ChineseLigature-*
---
## Data Description
The Turing Eye Test (TET) as presented in Paper 'Pixels, Patterns, But No Poetry: To See the World Like Humans'.

This benchmark includes four tasks:
- HiddenText: comprises scale-variant items where text is rendered as shapes within the figure, appearing as text when reduced and resolving into a complete image when magnified, which contains 150 images.
- 3DCaptcha: involves recognition challenges constructed with curved characters in the three-dimensional space, which consists of 150 Captchas.
- ColorBlind: similar to Ishihara tests, but augmented with confounding colored dots that are chromatically similar to the central character to increase difficulty. We generate 150 such test images.
- ChineseLigatures: features complex glyphs synthesized through character decomposition, morphological transformation, and fusion of multiple Chinese characters, which includes different words or phrases.

## Citation
If you find this dataset is useful in your work, please cite our paper:
<pre><code>@misc{gao2025pixelspatternspoetryworld,
      title={Pixels, Patterns, but No Poetry: To See The World like Humans}, 
      author={Hongcheng Gao and Zihao Huang and Lin Xu and Jingyi Tang and Xinhao Li and Yue Liu and Haoyang Li and Taihang Hu and Minhua Lin and Xinlong Yang and Ge Wu and Balong Bi and Hongyu Chen and Wentao Zhang},
      year={2025},
      eprint={2507.16863},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2507.16863}
}
</code></pre>