---
dataset_info:
  features:
  - name: are_different
    dtype: bool
  - name: best_image_uid
    dtype: string
  - name: caption
    dtype: string
  - name: created_at
    dtype: timestamp[ns]
  - name: has_label
    dtype: bool
  - name: image_0_uid
    dtype: string
  - name: image_0_url
    dtype: string
  - name: image_1_uid
    dtype: string
  - name: image_1_url
    dtype: string
  - name: jpg_0
    dtype: binary
  - name: jpg_1
    dtype: binary
  - name: label_0
    dtype: float64
  - name: label_1
    dtype: float64
  - name: model_0
    dtype: string
  - name: model_1
    dtype: string
  - name: ranking_id
    dtype: int64
  - name: user_id
    dtype: int64
  - name: num_example_per_prompt
    dtype: int64
  - name: __index_level_0__
    dtype: int64
  splits:
  - name: train
    num_bytes: 193273338802
    num_examples: 583747
  - name: validation
    num_bytes: 5638295249
    num_examples: 17439
  - name: test
    num_bytes: 4621428929
    num_examples: 14073
  - name: validation_unique
    num_bytes: 178723392
    num_examples: 500
  - name: test_unique
    num_bytes: 178099641
    num_examples: 500
  download_size: 202289408791
  dataset_size: 203889886013
---

# Dataset Card for Pick-a-Pic (v1)

## Dataset Description

- **Homepage: The web app can be found at [pickapic.io](https://pickapic.io/)**
- **Repository: The repository of [PickScore](https://github.com/yuvalkirstain/PickScore)**
- **Paper: [Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation](https://arxiv.org/abs/2305.01569).**
- **Leaderboard: TODO **
- **Point of Contact: TODO **

### Dataset Summary

The Pick-a-Pic dataset was collected with the [Pick-a-Pic web app](https://pickapic.io/) and contains over half-a-million examples of human preferences over model-generated images.
This dataset with URLs instead of the actual images (which makes it much smaller in size) can be found [here](https://huggingface.co/datasets/yuvalkirstain/pickapic_v1_no_images).

See the corresponding paper [Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation](https://arxiv.org/abs/2305.01569) for more details.

### Supported Tasks and Leaderboards

Task: Select preferred image in test-set.
| **Models** | **Test-Set Accuracy (%)** |
| --- | --- |
| [PickScore](https://arxiv.org/abs/2305.01569) | 70.2% |
| Human Expert Baseline | 68.0% |
| [HPS](https://arxiv.org/abs/2303.14420) | 66.7% |
| [ImageReward](https://arxiv.org/abs/2304.05977) | 61.1% |
| [CLIP-H](https://arxiv.org/abs/2210.03927) | 60.8% |
| [Aesthetics](https://arxiv.org/abs/2210.08402) | 56.8% |

### Data Splits

The dataset has three main splits: train, validation, validation_unique (with one example per prompt), test, and test_unique.


### Citation Information
If you find this work useful, please cite:
```bibtex
@inproceedings{Kirstain2023PickaPicAO,
  title={Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation},
  author={Yuval Kirstain and Adam Polyak and Uriel Singer and Shahbuland Matiana and Joe Penna and Omer Levy},
  year={2023}
}
```

### LICENSE
MIT License

Copyright (c) 2021

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