table-extraction

<div align="center">
<img width="640" alt="keremberke/table-extraction" src="https://huggingface.co/datasets/keremberke/table-extraction/resolve/main/thumbnail.jpg">
</div>

### Dataset Labels

```
['bordered', 'borderless']
```

### Number of Images

```json
{'test': 34, 'train': 238, 'valid': 70}
```

### How to Use

- Install [datasets](https://pypi.org/project/datasets/):

```bash
pip install datasets
```

- Load the dataset:

```python
from datasets import load_dataset

ds = load_dataset("keremberke/table-extraction", name="full")
example = ds['train'][0]
```

### Roboflow Dataset Page
[https://universe.roboflow.com/mohamed-traore-2ekkp/table-extraction-pdf/dataset/2](https://universe.roboflow.com/mohamed-traore-2ekkp/table-extraction-pdf/dataset/2?ref=roboflow2huggingface)

### Citation

```

```

### License
CC BY 4.0

### Dataset Summary
This dataset was exported via roboflow.com on January 18, 2023 at 9:41 AM GMT

Roboflow is an end-to-end computer vision platform that helps you
* collaborate with your team on computer vision projects
* collect & organize images
* understand and search unstructured image data
* annotate, and create datasets
* export, train, and deploy computer vision models
* use active learning to improve your dataset over time

For state of the art Computer Vision training notebooks you can use with this dataset,
visit https://github.com/roboflow/notebooks

To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com

The dataset includes 342 images.
Data-table are annotated in COCO format.

The following pre-processing was applied to each image:
* Auto-orientation of pixel data (with EXIF-orientation stripping)

No image augmentation techniques were applied.

<div align="center">
<img width="640" alt="keremberke/table-extraction" src="https://huggingface.co/datasets/keremberke/table-extraction/resolve/main/thumbnail.jpg">
</div>

### 数据集标签

['带边框（bordered）', '无边框（borderless）']

### 图像数量

json
{'test': 34, 'train': 238, 'valid': 70}

### 使用方法

- 安装[datasets](https://pypi.org/project/datasets/)库：

bash
pip install datasets

- 加载该数据集：

python
from datasets import load_dataset

ds = load_dataset("keremberke/table-extraction", name="full")
example = ds['train'][0]

### Roboflow 数据集页面
[https://universe.roboflow.com/mohamed-traore-2ekkp/table-extraction-pdf/dataset/2](https://universe.roboflow.com/mohamed-traore-2ekkp/table-extraction-pdf/dataset/2?ref=roboflow2huggingface)

### 引用

### 许可证
CC BY 4.0

### 数据集概述
本数据集于2023年1月18日格林威治标准时间上午9:41通过roboflow.com导出。

Roboflow是一款端到端计算机视觉平台，可助力您完成以下工作：
* 与团队协作开展计算机视觉项目
* 收集并整理图像素材
* 理解并检索非结构化图像数据
* 进行图像标注并构建数据集
* 导出、训练并部署计算机视觉模型
* 运用主动学习方法，随时间迭代优化数据集

若需获取适配本数据集的顶尖计算机视觉训练笔记，可访问 https://github.com/roboflow/notebooks

若需查找超过10万个其他数据集与预训练模型，可访问 https://universe.roboflow.com

本数据集共包含342张图像，所有数据表均采用COCO（Common Objects in Context）格式进行标注。

已对每张图像执行以下预处理操作：
* 自动校正像素数据方向（同时移除EXIF方向元信息）

未应用任何图像增强技术。