README.md

---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: ground_truth
    dtype: string
  - name: 2_coord
    list:
    - name: chunk
      dtype: string
    - name: coord
      sequence:
        sequence: float64
  - name: 4_coord
    list:
    - name: chunk
      dtype: string
    - name: coord
      sequence:
        sequence: float64
  - name: 2_coord_norm
    list:
    - name: chunk
      dtype: string
    - name: coord
      sequence:
        sequence: float64
  - name: 4_coord_norm
    list:
    - name: chunk
      dtype: string
    - name: coord
      sequence:
        sequence: float64
  splits:
  - name: train
    num_bytes: 4525075938
    num_examples: 50016
  download_size: 4302364671
  dataset_size: 4525075938
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
task_categories:
- image-to-text
- object-detection
language:
- en
size_categories:
- 10K<n<100K
---

## SynthDoG detection 🐕

OCR annotations for [`synthdog-en`](https://huggingface.co/datasets/naver-clova-ix/synthdog-en) using [PaddleOcr](https://github.com/PaddlePaddle/PaddleOCR).

![image](./syndog-boxes.jpg)

This dataset contains annotations with the following formats:
  * `2_coord`: [(xmin, ymin), (xmax,ymax)] 
  * `2_coord`: [(xmin/w, ymin/h), (xmax/w,ymax/h)] normalized version of `2_coord` where (h, w) are the image height and width
  * `4_coord`: [(x1, y1), (x2,y2), (x3,y3), (x4, y4)] all corners of the rectangle enclosing the text span
  * `2_coord`: [(x1/w, y1/h), (x2/w,y2/h), (x3/w,y3/h), (x4/w, y4/h)] normalized version of `4_coord`

## Usage 
```python 
from datasets import load_dataset

ds = load_dataset("nnethercott/synthdog-en-detection", split="train[:101]")
```

to visualize the boxes 
```python
from PIL import ImageDraw

sample = ds[-1]
img, boxes = sample['image'], sample['2_coord']

draw = ImageDraw.Draw(img)
for item in boxes:
    draw.rectangle([tuple(xy) for xy in item['coord']], outline='red')

img.save('sample.jpg')
```

## How to Cite
**Always cite the original authors !** This dataset is just an annotated version of [Clova AI's](https://github.com/clovaai) synthdog dataset. If you find this work useful to you, please cite them:
```bibtex
@inproceedings{kim2022donut,
  title     = {OCR-Free Document Understanding Transformer},
  author    = {Kim, Geewook and Hong, Teakgyu and Yim, Moonbin and Nam, JeongYeon and Park, Jinyoung and Yim, Jinyeong and Hwang, Wonseok and Yun, Sangdoo and Han, Dongyoon and Park, Seunghyun},
  booktitle = {European Conference on Computer Vision (ECCV)},
  year      = {2022}
}
```