Summary #
Vietnamese Traffic Signs Detection and Recognition Dataset is a dataset for an object detection task. It is used in the automotive industry.
The dataset consists of 1170 images with 2841 labeled objects belonging to 29 different classes including one way prohibition, speed limit, no parking, and other: intersection danger, indication, no stopping and parking, other prohibition, vehicle permission lane, road danger, direction, slow warning, no turn left, pedestrian danger, no truck entry/turning, no car entry/turning, pedestrian crossing, no motorbike entry/turning, no turn right, vehicle and speed permission lane, other warning, other, height limit, no u turn, no more prohibition, construction danger, no u and left turn, weight limit, no u and right turn, and overpass route.
Images in the Vietnamese Traffic Signs dataset have bounding box annotations. There are 6 (1% of the total) unlabeled images (i.e. without annotations). There are 3 splits in the dataset: train (900 images), val (180 images), and test (90 images). The dataset was released in 2023.
Explore #
Vietnamese Traffic Signs dataset has 1170 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.
Class balance #
There are 29 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.
Class ã…¤ | Images ã…¤ | Objects ã…¤ | Count on image average | Area on image average |
---|---|---|---|---|
one way prohibitionâž” rectangle | 264 | 310 | 1.17 | 0.1% |
speed limitâž” rectangle | 214 | 301 | 1.41 | 0.18% |
no parkingâž” rectangle | 197 | 216 | 1.1 | 0.14% |
intersection dangerâž” rectangle | 176 | 180 | 1.02 | 0.13% |
indicationâž” rectangle | 173 | 183 | 1.06 | 0.11% |
no stopping and parkingâž” rectangle | 154 | 169 | 1.1 | 0.24% |
other prohibitionâž” rectangle | 152 | 180 | 1.18 | 0.18% |
vehicle permission laneâž” rectangle | 136 | 199 | 1.46 | 0.34% |
road dangerâž” rectangle | 132 | 141 | 1.07 | 0.21% |
directionâž” rectangle | 113 | 156 | 1.38 | 0.38% |
Co-occurrence matrix #
Co-occurrence matrix is an extremely valuable tool that shows you the images for every pair of classes: how many images have objects of both classes at the same time. If you click any cell, you will see those images. We added the tooltip with an explanation for every cell for your convenience, just hover the mouse over a cell to preview the description.
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.
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
one way prohibition rectangle | 310 | 0.09% | 1.5% | 0% | 5px | 0.8% | 132px | 21.09% | 23px | 3.69% | 6px | 0.37% | 120px | 7.4% |
speed limit rectangle | 301 | 0.13% | 1.06% | 0.01% | 9px | 1.44% | 107px | 17.09% | 31px | 4.93% | 9px | 0.55% | 108px | 6.66% |
no parking rectangle | 216 | 0.13% | 1.11% | 0.01% | 8px | 1.28% | 110px | 17.57% | 31px | 4.95% | 9px | 0.55% | 102px | 6.29% |
vehicle permission lane rectangle | 199 | 0.23% | 3.34% | 0.01% | 10px | 1.6% | 159px | 25.4% | 40px | 6.35% | 5px | 0.31% | 223px | 13.75% |
indication rectangle | 183 | 0.1% | 1.12% | 0% | 6px | 0.96% | 114px | 18.21% | 24px | 3.86% | 7px | 0.43% | 112px | 6.91% |
other prohibition rectangle | 180 | 0.15% | 1.94% | 0.01% | 7px | 1.12% | 140px | 22.36% | 31px | 4.99% | 9px | 0.55% | 141px | 8.69% |
intersection danger rectangle | 180 | 0.12% | 1.53% | 0.01% | 9px | 1.44% | 104px | 16.61% | 27px | 4.38% | 8px | 0.49% | 149px | 9.19% |
no stopping and parking rectangle | 169 | 0.22% | 5.55% | 0.01% | 8px | 1.28% | 200px | 31.95% | 38px | 6.03% | 7px | 0.43% | 282px | 17.39% |
direction rectangle | 156 | 0.27% | 4.21% | 0.01% | 8px | 1.28% | 289px | 46.17% | 36px | 5.72% | 9px | 0.55% | 219px | 13.5% |
road danger rectangle | 141 | 0.2% | 2.71% | 0.01% | 10px | 1.6% | 204px | 32.59% | 35px | 5.55% | 13px | 0.8% | 135px | 8.32% |
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 2841 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.
Object ID ã…¤ | Class ã…¤ | Image name click row to open | Image size height x width | Height ã…¤ | Height ã…¤ | Width ã…¤ | Width ã…¤ | Area ã…¤ |
---|---|---|---|---|---|---|---|---|
1âž” | other prohibition rectangle | frame_44.png | 626 x 1622 | 69px | 11.02% | 70px | 4.32% | 0.48% |
2âž” | speed limit rectangle | frame_44.png | 626 x 1622 | 32px | 5.11% | 37px | 2.28% | 0.12% |
3âž” | road danger rectangle | frame_44.png | 626 x 1622 | 28px | 4.47% | 37px | 2.28% | 0.1% |
4âž” | vehicle permission lane rectangle | frame_44.png | 626 x 1622 | 36px | 5.75% | 33px | 2.03% | 0.12% |
5âž” | no stopping and parking rectangle | frame_44.png | 626 x 1622 | 31px | 4.95% | 30px | 1.85% | 0.09% |
6âž” | other warning rectangle | frame_44.png | 626 x 1622 | 25px | 3.99% | 31px | 1.91% | 0.08% |
7âž” | no parking rectangle | frame_44.png | 626 x 1622 | 15px | 2.4% | 12px | 0.74% | 0.02% |
8âž” | other warning rectangle | frame_44.png | 626 x 1622 | 12px | 1.92% | 13px | 0.8% | 0.02% |
9âž” | slow warning rectangle | frame_44.png | 626 x 1622 | 12px | 1.92% | 15px | 0.92% | 0.02% |
10âž” | vehicle permission lane rectangle | frame_44.png | 626 x 1622 | 23px | 3.67% | 26px | 1.6% | 0.06% |
License #
License is unknown for the Vietnamese traffic signs detection and recognition dataset dataset.
Citation #
If you make use of the vietnamese traffic signs data, please cite the following reference:
@dataset{vietnamese traffic signs,
author={Dat Nguyen},
title={Vietnamese traffic signs detection and recognition dataset},
year={2023},
url={https://www.kaggle.com/datasets/jaydenguyenx/vietnamese-traffic-signs-detection-and-recognition}
}
If you are happy with Dataset Ninja and use provided visualizations and tools in your work, please cite us:
@misc{ visualization-tools-for-vietnamese-traffic-signs-dataset,
title = { Visualization Tools for Vietnamese Traffic Signs Dataset },
type = { Computer Vision Tools },
author = { Dataset Ninja },
howpublished = { \url{ https://datasetninja.com/vietnamese-traffic-signs } },
url = { https://datasetninja.com/vietnamese-traffic-signs },
journal = { Dataset Ninja },
publisher = { Dataset Ninja },
year = { 2024 },
month = { dec },
note = { visited on 2024-12-07 },
}
Download #
Please visit dataset homepage to download the data.
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.