README.md

---
dataset_info:
  features:
  - name: question_id
    dtype: string
  - name: question
    dtype: string
  - name: image
    dtype: image
  - name: image_id
    dtype: string
  - name: image_classes
    sequence: string
  - name: flickr_original_url
    dtype: string
  - name: flickr_300k_url
    dtype: string
  - name: image_width
    dtype: int64
  - name: image_height
    dtype: int64
  - name: set_name
    dtype: string
  - name: image_name
    dtype: string
  - name: image_path
    dtype: string
  - name: caption_id
    sequence: int64
  - name: caption_str
    sequence: string
  - name: reference_strs
    sequence: string
  splits:
  - name: train
    num_bytes: 6201208209.0
    num_examples: 21953
  - name: val
    num_bytes: 919878416.0
    num_examples: 3166
  - name: test
    num_bytes: 959971875.0
    num_examples: 3289
  download_size: 8064165124
  dataset_size: 8081058500.0
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: val
    path: data/val-*
  - 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`

🏠 [Homepage](https://lmms-lab.github.io/) | 📚 [Documentation](docs/README.md) | 🤗 [Huggingface Datasets](https://huggingface.co/lmms-lab)

# This Dataset

This is a formatted version of [TextCaps](https://textvqa.org/textcaps/). It is used in our `lmms-eval` pipeline to allow for one-click evaluations of large multi-modality models.

```
@inproceedings{sidorov2019textcaps,
    title={TextCaps: a Dataset for Image Captioningwith Reading Comprehension},
    author={Sidorov, Oleksii and Hu, Ronghang and Rohrbach, Marcus and Singh, Amanpreet},
    journal={European Conference on Computer Vision},
    year={2020}
}
```