| --- |
| dataset_info: |
| features: |
| - name: image_id |
| dtype: string |
| - name: question_id |
| dtype: int32 |
| - name: question |
| dtype: string |
| - name: question_tokens |
| sequence: string |
| - name: image |
| dtype: image |
| - name: image_width |
| dtype: int32 |
| - name: image_height |
| dtype: int32 |
| - name: flickr_original_url |
| dtype: string |
| - name: flickr_300k_url |
| dtype: string |
| - name: answers |
| sequence: string |
| - name: image_classes |
| sequence: string |
| - name: set_name |
| dtype: string |
| - name: ocr_tokens |
| sequence: string |
| splits: |
| - name: train |
| num_bytes: 9839776032.652 |
| num_examples: 34602 |
| - name: validation |
| num_bytes: 1438831837.0 |
| num_examples: 5000 |
| - name: test |
| num_bytes: 1712000724.844 |
| num_examples: 5734 |
| download_size: 8097805782 |
| dataset_size: 12990608594.496 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| - split: validation |
| path: data/validation-* |
| - split: test |
| path: data/test-* |
| --- |
| |
| <p align="center" width="100%"> |
| <img src="https://i.postimg.cc/g0QRgMVv/WX20240228-113337-2x.png" width="100%" height="80%"> |
| </p> |
|
|
| # Large-scale Multi-modality Models Evaluation Suite |
|
|
| > Accelerating the development of large-scale multi-modality models (LMMs) with `lmms-eval` |
|
|
| ๐ [Homepage](https://lmms-lab.github.io/) | ๐ [Documentation](docs/README.md) | ๐ค [Huggingface Datasets](https://huggingface.co/lmms-lab) |
|
|
| # This Dataset |
|
|
| This is a formatted version of [TextVQA](https://textvqa.org/). It is used in our `lmms-eval` pipeline to allow for one-click evaluations of large multi-modality models. |
|
|
| ``` |
| @inproceedings{singh2019towards, |
| title={Towards vqa models that can read}, |
| author={Singh, Amanpreet and Natarajan, Vivek and Shah, Meet and Jiang, Yu and Chen, Xinlei and Batra, Dhruv and Parikh, Devi and Rohrbach, Marcus}, |
| booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition}, |
| pages={8317--8326}, |
| year={2019} |
| } |
| ``` |
|
|