Datasets:
Tasks:
Object Detection
Size:
< 1K
| task_categories: | |
| - object-detection | |
| tags: | |
| - roboflow | |
| - roboflow2huggingface | |
| - Documents | |
| <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. | |