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2020 NMLO Competition Six Dataset

117611
Tagsurveillance
Taskobject detection
Release YearMade in 2020
Licenseunknown

Introduction #

The 2020 NMLO Competition Six dataset is specifically designed for object detection tasks, featuring 1176 images with annotations centered around a singular class β€” car. As an integral segment of the NMLO contest, part 6, this dataset is geared towards training object detectors utilizing the YOLO model architecture to detect custom objects within a series of images.

The dataset primarily consists of images depicting cars on roads, captured from a side-view-mounted camera on a vehicle. The training data includes annotations exclusively focusing on the car class or background (nothing), with bounding boxes specified to precisely train models to identify and locate cars within the images, providing a targeted resource for object detection model development.

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Dataset LinkHomepageDataset LinkKaggle

Summary #

2020 NMLO Competition Six is a dataset for an object detection task. It is used in the surveillance industry.

The dataset consists of 1176 images with 559 labeled objects belonging to 1 single class (car).

Images in the 2020 NMLO Competition Six dataset have bounding box annotations. There are 821 (70% of the total) unlabeled images (i.e. without annotations). There are 2 splits in the dataset: train (1001 images) and test (175 images). The dataset was released in 2020 by the Thomas Jefferson High School for Science and Technology Machine Learning Club, USA.

Dataset Poster

Explore #

2020 NMLO Competition Six dataset has 1176 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 2020 NMLO Competition SixSample image from 2020 NMLO Competition Six
OpenSample annotation mask from 2020 NMLO Competition SixSample image from 2020 NMLO Competition Six
OpenSample annotation mask from 2020 NMLO Competition SixSample image from 2020 NMLO Competition Six
OpenSample annotation mask from 2020 NMLO Competition SixSample image from 2020 NMLO Competition Six
OpenSample annotation mask from 2020 NMLO Competition SixSample image from 2020 NMLO Competition Six
OpenSample annotation mask from 2020 NMLO Competition SixSample image from 2020 NMLO Competition Six
OpenSample annotation mask from 2020 NMLO Competition SixSample image from 2020 NMLO Competition Six
OpenSample annotation mask from 2020 NMLO Competition SixSample image from 2020 NMLO Competition Six
OpenSample annotation mask from 2020 NMLO Competition SixSample image from 2020 NMLO Competition Six
OpenSample annotation mask from 2020 NMLO Competition SixSample image from 2020 NMLO Competition Six
OpenSample annotation mask from 2020 NMLO Competition SixSample image from 2020 NMLO Competition Six
OpenSample annotation mask from 2020 NMLO Competition SixSample image from 2020 NMLO Competition Six
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Have a look at 1176 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.

Search
Rows 1-1 of 1
Class
γ…€
Images
γ…€
Objects
γ…€
Count on image
average
Area on image
average
carβž”
rectangle
355
559
1.57
3.15%

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
car
rectangle
559
2.03%
15.53%
0.16%
18px
4.74%
138px
36.32%
46px
12.11%
20px
2.96%
300px
44.38%

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 559 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 559
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
vid_4_1760.jpg
380 x 676
46px
12.11%
113px
16.72%
2.02%
2βž”
car
rectangle
vid_4_1940.jpg
380 x 676
31px
8.16%
71px
10.5%
0.86%
3βž”
car
rectangle
vid_4_1940.jpg
380 x 676
41px
10.79%
57px
8.43%
0.91%
4βž”
car
rectangle
vid_4_12200.jpg
380 x 676
26px
6.84%
35px
5.18%
0.35%
5βž”
car
rectangle
vid_4_12200.jpg
380 x 676
54px
14.21%
46px
6.8%
0.97%
6βž”
car
rectangle
vid_4_6320.jpg
380 x 676
41px
10.79%
104px
15.38%
1.66%
7βž”
car
rectangle
vid_4_6320.jpg
380 x 676
42px
11.05%
91px
13.46%
1.49%
8βž”
car
rectangle
vid_4_1040.jpg
380 x 676
41px
10.79%
65px
9.62%
1.04%
9βž”
car
rectangle
vid_4_12080.jpg
380 x 676
39px
10.26%
57px
8.43%
0.87%
10βž”
car
rectangle
vid_4_16120.jpg
380 x 676
48px
12.63%
131px
19.38%
2.45%

License #

License is unknown for the 2020 NMLO Competition Six dataset.

Source

Citation #

If you make use of the 2020 NMLO Competition Six data, please cite the following reference:

@dataset{2020 NMLO Competition Six,
  organization={Thomas Jefferson High School for Science and Technology Machine Learning Club},
  title={2020 NMLO Competition Six},
  year={2020},
  url={https://tjmachinelearning.com/2020/comp_six}
}

Source

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

@misc{ visualization-tools-for-2020-nmlo-dataset,
  title = { Visualization Tools for 2020 NMLO Competition Six Dataset },
  type = { Computer Vision Tools },
  author = { Dataset Ninja },
  howpublished = { \url{ https://datasetninja.com/2020-nmlo-6 } },
  url = { https://datasetninja.com/2020-nmlo-6 },
  journal = { Dataset Ninja },
  publisher = { Dataset Ninja },
  year = { 2024 },
  month = { jun },
  note = { visited on 2024-06-21 },
}

Download #

Please visit dataset homepage to download the data.

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