Tunisian Licensed Plates

Introduction #

Achraf Khazri

The author of the following dataset present a collection of data pertaining to Tunisian Licensed Plates. This dataset has been meticulously labeled using Labelimg, making it suitable for training deep learning models focused on object detection.

Homepage

Summary #

Tunisian Licensed Plates is a dataset for an object detection task. Possible applications of the dataset could be in the automotive industry.

The dataset consists of 709 images with 709 labeled objects belonging to 1 single class (license plate).

Images in the Tunisian Licensed Plates dataset have bounding box annotations. All images are labeled (i.e. with annotations). There are 2 splits in the dataset: train (567 images) and test (142 images). The dataset was released in 2019.

Explore #

Tunisian Licensed Plates dataset has 709 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 Tunisian Licensed Plates

Sample image from Tunisian Licensed Plates

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Have a look at 709 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
license plate➔ rectangle	709	709	1	1.62%

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
license plate rectangle	709	1.62%	7.41%	0.18%	19px	1.88%	491px	38%	79px	8.96%	39px	2.75%	919px	48.47%

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 709 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 709

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➔	license plate rectangle	127.jpg	747 x 1000	69px	9.24%	118px	11.8%	1.09%
2➔	license plate rectangle	68.jpg	519 x 690	28px	5.39%	106px	15.36%	0.83%
3➔	license plate rectangle	114.jpg	747 x 1000	67px	8.97%	185px	18.5%	1.66%
4➔	license plate rectangle	101.jpg	5376 x 3024	101px	1.88%	288px	9.52%	0.18%
5➔	license plate rectangle	108.jpg	747 x 1000	77px	10.31%	244px	24.4%	2.52%
6➔	license plate rectangle	55.jpg	518 x 690	61px	11.78%	110px	15.94%	1.88%
7➔	license plate rectangle	23.jpg	514 x 690	44px	8.56%	173px	25.07%	2.15%
8➔	license plate rectangle	81.jpg	391 x 690	31px	7.93%	97px	14.06%	1.11%
9➔	license plate rectangle	136.jpg	747 x 1000	53px	7.1%	223px	22.3%	1.58%
10➔	license plate rectangle	11.jpg	548 x 851	32px	5.84%	134px	15.75%	0.92%

License #

Tunisian Licensed Plates is under ODbL v1.0 license.

Source

Citation #

If you make use of the Tunisian Licensed Plates data, please cite the following reference:

@dataset{Tunisian Licensed Plates,
  author={Achraf Khazri},
  title={Tunisian Licensed Plates},
  year={2019},
  url={https://www.kaggle.com/datasets/achrafkhazri/labeled-licence-plates-dataset}
}

Source

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

@misc{ visualization-tools-for-tunisian-licensed-plates-dataset,
  title = { Visualization Tools for Tunisian Licensed Plates Dataset },
  type = { Computer Vision Tools },
  author = { Dataset Ninja },
  howpublished = { \url{ https://datasetninja.com/tunisian-licensed-plates } },
  url = { https://datasetninja.com/tunisian-licensed-plates },
  journal = { Dataset Ninja },
  publisher = { Dataset Ninja },
  year = { 2024 },
  month = { nov },
  note = { visited on 2024-11-21 },
}

Download #

Dataset Tunisian Licensed Plates can be downloaded in Supervisely format:

As an alternative, it can be downloaded with dataset-tools package:

pip install --upgrade dataset-tools

… using following python code:

import dataset_tools as dtools

dtools.download(dataset='Tunisian Licensed Plates', dst_dir='~/dataset-ninja/')

Make sure not to overlook the python code example available on the Supervisely Developer Portal. It will give you a clear idea of how to effortlessly work with the downloaded dataset.

The data in original format can be downloaded here.

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Disclaimer #

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