General Table Detection - Dataset Ninja

Summary #

General Table Detection is a dataset for an object detection task. Possible applications of the dataset could be in the optical character recognition (OCR) domain. The dataset presented here is not the original one. Learn more on the dataset’s homepage.

The dataset consists of 2029 images with 2835 labeled objects belonging to 1 single class (table).

Images in the General Table Detection dataset have bounding box annotations. There are 97 (5% of the total) unlabeled images (i.e. without annotations). There is 1 split in the dataset: train (2029 images). The dataset was released in 2022.

Explore #

General Table Detection dataset has 2029 images. Click on one of the examples below or open "Explore" tool anytime you need to view dataset images with annotations. This tool has extended visualization capabilities like zoom, translation, objects table, custom filters and more. Hover the mouse over the images to hide or show annotations.

Sample annotation mask from General Table Detection

Sample image from General Table Detection

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Have a look at 2029 images

Because of dataset's license preview is limited to 12 images

View images along with annotations and tags, search and filter by various parameters

Class balance #

There are 1 annotation classes in the dataset. Find the general statistics and balances for every class in the table below. Click any row to preview images that have labels of the selected class. Sort by column to find the most rare or prevalent classes.

Rows 1-1 of 1

Class ㅤ	Images ㅤ	Objects ㅤ	Count on image average	Area on image average
table➔ rectangle	1932	2835	1.47	28.19%

Images #

Explore every single image in the dataset with respect to the number of annotations of each class it has. Click a row to preview selected image. Sort by any column to find anomalies and edge cases. Use horizontal scroll if the table has many columns for a large number of classes in the dataset.

Object distribution #

Interactive heatmap chart for every class with object distribution shows how many images are in the dataset with a certain number of objects of a specific class. Users can click cell and see the list of all corresponding images.

Class sizes #

The table below gives various size properties of objects for every class. Click a row to see the image with annotations of the selected class. Sort columns to find classes with the smallest or largest objects or understand the size differences between classes.

Rows 1-1 of 1

Class	Object count	Avg area	Max area	Min area	Min height	Min height	Max height	Max height	Avg height	Avg height	Min width	Min width	Max width	Max width
table rectangle	2835	19.21%	87.94%	0.21%	15px	1.34%	3244px	98.3%	400px	26.86%	96px	13.6%	2885px	97.03%

Spatial Heatmap #

The heatmaps below give the spatial distributions of all objects for every class. These visualizations provide insights into the most probable and rare object locations on the image. It helps analyze objects' placements in a dataset.

Objects #

Table contains all 2835 objects. Click a row to preview an image with annotations, and use search or pagination to navigate. Sort columns to find outliers in the dataset.

Rows 1-10 of 2835

Object ID ㅤ	Class ㅤ	Image name click row to open	Image size height x width	Height ㅤ	Height ㅤ	Width ㅤ	Width ㅤ	Area ㅤ
1➔	table rectangle	1634_330.png	3300 x 2560	1722px	52.18%	1980px	77.34%	40.36%
2➔	table rectangle	cTDaR_t10185.jpg	1124 x 797	540px	48.04%	682px	85.57%	41.11%
3➔	table rectangle	cTDaR_t10426.jpg	1459 x 1031	479px	32.83%	455px	44.13%	14.49%
4➔	table rectangle	cTDaR_t10371.jpg	1124 x 797	675px	60.05%	685px	85.95%	51.61%
5➔	table rectangle	cTDaR_t10407.jpg	1123 x 794	202px	17.99%	707px	89.04%	16.02%
6➔	table rectangle	cTDaR_t10407.jpg	1123 x 794	110px	9.8%	707px	89.04%	8.72%
7➔	table rectangle	cTDaR_t10407.jpg	1123 x 794	78px	6.95%	707px	89.04%	6.18%
8➔	table rectangle	44_96.jpg	828 x 717	220px	26.57%	520px	72.52%	19.27%
9➔	table rectangle	62_108.jpg	741 x 493	364px	49.12%	394px	79.92%	39.26%
10➔	table rectangle	cTDaR_t10026.jpg	1078 x 794	535px	49.63%	626px	78.84%	39.13%

License #

License is unknown for the General Table Detection: composition of datasets ICDAR 19, Marmot, Github dataset.

Source

Citation #

If you make use of the General Table Detection data, please cite the following reference:

@dataset{General Table Detection,
  title={General Table Detection: composition of datasets ICDAR 19, Marmot, Github},
  year={2022},
  url={https://www.kaggle.com/datasets/rhtsingh/general-table-recognition-dataset/data}
}

Source

If you are happy with Dataset Ninja and use provided visualizations and tools in your work, please cite us:

@misc{ visualization-tools-for-general-table-detection-dataset,
  title = { Visualization Tools for General Table Detection Dataset },
  type = { Computer Vision Tools },
  author = { Dataset Ninja },
  howpublished = { \url{ https://datasetninja.com/general-table-detection } },
  url = { https://datasetninja.com/general-table-detection },
  journal = { Dataset Ninja },
  publisher = { Dataset Ninja },
  year = { 2024 },
  month = { jul },
  note = { visited on 2024-07-27 },
}

Download #

Please visit dataset homepage to download the data.

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Disclaimer #

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