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Traffic Vehicles Object Detection Dataset

120171
Tagsurveillance
Taskobject detection
Release YearMade in 2021
Licenseunknown

Introduction #

Saumya Patel

The Traffic Vehicles Object Detection dataset is a valuable resource containing 1,201 images capturing the dynamic world of traffic, featuring 11,134 meticulously labeled objects. These objects are classified into seven distinct categories, including common vehicles like car, two_wheeler, as well as blur_number_plate, and other essential elements such as auto, number_plate, bus, and truck. The dataset’s origins lie in the collection of training images from traffic scenes and CCTV footage, followed by precise object annotation and labeling, making it an ideal tool for object detection tasks in the realm of transportation and surveillance.

The dataset contains labeled images of transport vehicles and number plates using LabelImg in YOLOv5 format. Author first collected some 1000 training images of traffic, vehicles and number plates, and CCTV footage videos. Then he extracted frames from videos using OpenCV. Drew a box around each object that he want the detector to see and label each box with the object class that he would like the detector to predict. Data was collected from open-source websites.

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Dataset LinkHomepage

Summary #

Traffic Vehicles Object Detection is a dataset for an object detection task. Possible applications of the dataset could be in the smart city and surveillance industries.

The dataset consists of 1201 images with 11134 labeled objects belonging to 7 different classes including car, two_wheeler, blur_number_plate, and other: auto, number_plate, bus, and truck.

Images in the Traffic Vehicles Object Detection dataset have bounding box annotations. There are 285 (24% of the total) unlabeled images (i.e. without annotations). There are 3 splits in the dataset: train (738 images), test (278 images), and val (185 images). The dataset was released in 2021.

Here are the visualized examples for the classes:

Explore #

Traffic Vehicles Object Detection dataset has 1201 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 Traffic Vehicles Object DetectionSample image from Traffic Vehicles Object Detection
OpenSample annotation mask from Traffic Vehicles Object DetectionSample image from Traffic Vehicles Object Detection
OpenSample annotation mask from Traffic Vehicles Object DetectionSample image from Traffic Vehicles Object Detection
OpenSample annotation mask from Traffic Vehicles Object DetectionSample image from Traffic Vehicles Object Detection
OpenSample annotation mask from Traffic Vehicles Object DetectionSample image from Traffic Vehicles Object Detection
OpenSample annotation mask from Traffic Vehicles Object DetectionSample image from Traffic Vehicles Object Detection
OpenSample annotation mask from Traffic Vehicles Object DetectionSample image from Traffic Vehicles Object Detection
OpenSample annotation mask from Traffic Vehicles Object DetectionSample image from Traffic Vehicles Object Detection
OpenSample annotation mask from Traffic Vehicles Object DetectionSample image from Traffic Vehicles Object Detection
OpenSample annotation mask from Traffic Vehicles Object DetectionSample image from Traffic Vehicles Object Detection
OpenSample annotation mask from Traffic Vehicles Object DetectionSample image from Traffic Vehicles Object Detection
OpenSample annotation mask from Traffic Vehicles Object DetectionSample image from Traffic Vehicles Object Detection
πŸ‘€
Have a look at 1201 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 7 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 1-7 of 7
Class
γ…€
Images
γ…€
Objects
γ…€
Count on image
average
Area on image
average
carβž”
rectangle
737
5177
7.02
16.92%
two_wheelerβž”
rectangle
536
1869
3.49
6.14%
blur_number_plateβž”
rectangle
534
1310
2.45
0.27%
autoβž”
rectangle
413
1166
2.82
4.61%
number_plateβž”
rectangle
398
653
1.64
0.32%
busβž”
rectangle
298
415
1.39
9.8%
truckβž”
rectangle
294
544
1.85
14.21%

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.

Search
Rows 1-7 of 7
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
car
rectangle
5177
2.57%
81.09%
0.02%
9px
1.67%
751px
89.62%
130px
14.96%
12px
1.25%
1897px
100%
two_wheeler
rectangle
1869
1.87%
79.83%
0.02%
14px
2.59%
1586px
100%
107px
17.25%
5px
0.52%
1888px
93.12%
blur_number_plate
rectangle
1310
0.11%
8.93%
0%
4px
0.57%
381px
39.85%
15px
2.48%
1px
0.1%
295px
22.69%
auto
rectangle
1166
1.67%
53.81%
0.02%
12px
2.22%
681px
88.13%
73px
13.3%
6px
0.62%
786px
66.55%
number_plate
rectangle
653
0.2%
3.18%
0.01%
7px
0.47%
116px
10.85%
27px
2.83%
19px
1.6%
241px
36.24%
truck
rectangle
544
7.72%
91.73%
0.03%
11px
2.04%
2823px
100%
224px
27.07%
14px
1.46%
3565px
96.44%
bus
rectangle
415
7.06%
93.5%
0.13%
16px
2.65%
1481px
99.44%
185px
22.75%
22px
3.6%
2862px
99.87%

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 11134 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 11134
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”
car
rectangle
Video2_2.jpg
540 x 960
35px
6.48%
97px
10.1%
0.65%
2βž”
car
rectangle
Video2_2.jpg
540 x 960
99px
18.33%
93px
9.69%
1.78%
3βž”
car
rectangle
Video2_2.jpg
540 x 960
34px
6.3%
63px
6.56%
0.41%
4βž”
blur_number_plate
rectangle
Video2_2.jpg
540 x 960
11px
2.04%
29px
3.02%
0.06%
5βž”
auto
rectangle
Video2_2.jpg
540 x 960
21px
3.89%
16px
1.67%
0.06%
6βž”
bus
rectangle
Video2_2.jpg
540 x 960
34px
6.3%
47px
4.9%
0.31%
7βž”
bus
rectangle
00 (11).jpg
167 x 301
74px
44.31%
237px
78.74%
34.89%
8βž”
car
rectangle
Video5_29.jpg
540 x 960
79px
14.63%
130px
13.54%
1.98%
9βž”
car
rectangle
Video5_29.jpg
540 x 960
102px
18.89%
124px
12.92%
2.44%
10βž”
car
rectangle
Video5_29.jpg
540 x 960
134px
24.81%
146px
15.21%
3.77%

License #

License is unknown for the Traffic Vehicles Object Detection dataset.

Source

Citation #

If you make use of the Traffic Vehicles Object Detection data, please cite the following reference:

@dataset{Traffic Vehicles Object Detection,
  author={Saumya Patel},
  title={Traffic Vehicles Object Detection},
  year={2021},
  url={https://www.kaggle.com/datasets/saumyapatel/traffic-vehicles-object-detection}
}

Source

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

@misc{ visualization-tools-for-traffic-vehicles-object-detection-dataset,
  title = { Visualization Tools for Traffic Vehicles Object Detection Dataset },
  type = { Computer Vision Tools },
  author = { Dataset Ninja },
  howpublished = { \url{ https://datasetninja.com/traffic-vehicles-object-detection } },
  url = { https://datasetninja.com/traffic-vehicles-object-detection },
  journal = { Dataset Ninja },
  publisher = { Dataset Ninja },
  year = { 2024 },
  month = { jun },
  note = { visited on 2024-06-25 },
}

Download #

Please visit dataset homepage to download the data.

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