Non-Metal Lighter Target Detection Under X-Ray

Summary #

Non-Metal Lighter Target Detection Under X-Ray is a dataset for an object detection task. Possible applications of the dataset could be in the security industry.

The dataset consists of 883 images with 769 labeled objects belonging to 1 single class (non-metal lighter).

Images in the Non-Metal Lighter Target Detection Under X-Ray dataset have bounding box annotations. There are 177 (20% of the total) unlabeled images (i.e. without annotations). There are 2 splits in the dataset: train (706 images) and test (177 images). The dataset was released in 2021.

Explore #

Non-Metal Lighter Target Detection Under X-Ray dataset has 883 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 Non-Metal Lighter Target Detection Under X-Ray

Sample image from Non-Metal Lighter Target Detection Under X-Ray

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Have a look at 883 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
non-metal lighter➔ rectangle	706	769	1.09	0.8%

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
non-metal lighter rectangle	769	0.74%	4.66%	0.1%	30px	2.88%	184px	17.69%	83px	7.94%	28px	1.5%	174px	51.43%

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 769 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 769

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➔	non-metal lighter rectangle	003723301009804.jpg	1040 x 652	141px	13.56%	80px	12.27%	1.66%
2➔	non-metal lighter rectangle	001666601012151.jpg	1040 x 1032	79px	7.6%	84px	8.14%	0.62%
3➔	non-metal lighter rectangle	000350901017294.jpg	1040 x 1256	50px	4.81%	122px	9.71%	0.47%
4➔	non-metal lighter rectangle	005983401003635.jpg	1040 x 1796	55px	5.29%	109px	6.07%	0.32%
5➔	non-metal lighter rectangle	002289301000908.jpg	1040 x 676	92px	8.85%	142px	21.01%	1.86%
6➔	non-metal lighter rectangle	006219601025157.jpg	1040 x 668	92px	8.85%	102px	15.27%	1.35%
7➔	non-metal lighter rectangle	003689901009470.jpg	1040 x 1280	73px	7.02%	88px	6.88%	0.48%
8➔	non-metal lighter rectangle	001313301009918.jpg	1040 x 2000	45px	4.33%	101px	5.05%	0.22%
9➔	non-metal lighter rectangle	004564401007032.jpg	1040 x 1892	58px	5.58%	74px	3.91%	0.22%
10➔	non-metal lighter rectangle	004564401007032.jpg	1040 x 1892	91px	8.75%	47px	2.48%	0.22%

License #

Non-Metal Lighter Target Detection Under X-Ray is under GNU GPL 2.0 license.

Citation #

If you make use of the Lighter detection under x-ray data, please cite the following reference:

@dataset{Lighter detection under x-ray,
  author={Voler},
  title={Non-metal lighter target detection under X-ray},
  year={2021},
  url={https://www.kaggle.com/datasets/voler2333/lighter-detection-under-xray}
}

Source

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

@misc{ visualization-tools-for-lighter-detection-dataset,
  title = { Visualization Tools for Non-Metal Lighter Target Detection Under X-Ray Dataset },
  type = { Computer Vision Tools },
  author = { Dataset Ninja },
  howpublished = { \url{ https://datasetninja.com/lighter-detection } },
  url = { https://datasetninja.com/lighter-detection },
  journal = { Dataset Ninja },
  publisher = { Dataset Ninja },
  year = { 2024 },
  month = { nov },
  note = { visited on 2024-11-21 },
}

Download #

Dataset Non-Metal Lighter Target Detection Under X-Ray 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='Non-Metal Lighter Target Detection Under X-Ray', 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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