Datasets:
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---
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 with bounding boxes for [`synthdog-en`](https://huggingface.co/datasets/naver-clova-ix/synthdog-en) generated with [PaddleOcr](https://github.com/PaddlePaddle/PaddleOCR).
This dataset contains annotations where the bounding boxes have 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
* `4_coord_norm`: [(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}
}
``` |