Dataset Ninja LogoDataset Ninja:

Tunisian Licensed Plates Dataset

70911454
Tagsurveillance
Taskobject detection
Release YearMade in 2019
LicenseODbL v1.0
Download145 MB

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.

Dataset LinkHomepage

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.

Dataset Poster

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.

OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
OpenSample annotation mask from Tunisian Licensed PlatesSample image from Tunisian Licensed Plates
πŸ‘€
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.

Search
Rows 1-1 of 1
Class
γ…€
Images
γ…€
Objects
γ…€
Count on image
average
Area on image
average
license plateβž”
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.

Search
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.

Spatial Heatmap

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.

Search
Rows 1-10 of 709
Object ID
γ…€
Class
γ…€
Image name
click row to open
Image size
height x width
Height
γ…€
Height
γ…€
Width
γ…€
Width
γ…€
Area
γ…€
1βž”
license plate
rectangle
127.jpg
747 x 1000
69px
9.24%
118px
11.8%
1.09%
2βž”
license plate
rectangle
68.jpg
519 x 690
28px
5.39%
106px
15.36%
0.83%
3βž”
license plate
rectangle
114.jpg
747 x 1000
67px
8.97%
185px
18.5%
1.66%
4βž”
license plate
rectangle
101.jpg
5376 x 3024
101px
1.88%
288px
9.52%
0.18%
5βž”
license plate
rectangle
108.jpg
747 x 1000
77px
10.31%
244px
24.4%
2.52%
6βž”
license plate
rectangle
55.jpg
518 x 690
61px
11.78%
110px
15.94%
1.88%
7βž”
license plate
rectangle
23.jpg
514 x 690
44px
8.56%
173px
25.07%
2.15%
8βž”
license plate
rectangle
81.jpg
391 x 690
31px
7.93%
97px
14.06%
1.11%
9βž”
license plate
rectangle
136.jpg
747 x 1000
53px
7.1%
223px
22.3%
1.58%
10βž”
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 = { feb },
  note = { visited on 2024-02-24 },
}

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.

. . .

Disclaimer #

Our gal from the legal dep told us we need to post this:

Dataset Ninja provides visualizations and statistics for some datasets that can be found online and can be downloaded by general audience. Dataset Ninja is not a dataset hosting platform and can only be used for informational purposes. The platform does not claim any rights for the original content, including images, videos, annotations and descriptions. Joint publishing is prohibited.

You take full responsibility when you use datasets presented at Dataset Ninja, as well as other information, including visualizations and statistics we provide. You are in charge of compliance with any dataset license and all other permissions. You are required to navigate datasets homepage and make sure that you can use it. In case of any questions, get in touch with us at hello@datasetninja.com.