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OD-WeaponDetection: Pistol Detection Dataset

300011
Tagsecurity, surveillance
Taskobject detection
Release YearMade in 2020
LicenseCC BY-SA 4.0
Download245 MB

Introduction #

Released 2020-11-23 ·Fransco Pérez Hernandez, Alberto Castillo Lamas

Authors introduce OD-WeaponDetection: Pistol Detection dataset, a collection of 3000 images designed for object detection, specifically focused on the presence of at least one pistol. These images were sourced from the internet, including frames extracted from YouTube videos and surveillance footage. The dataset encompasses a wide variety of pistol weapons, differing in types, shapes, colors, sizes, and materials. It accounts for knives positioned at various distances from the camera, some partially occluded by hands, and objects that mimic the handling of pistol. The dataset offers a diverse range of indoor and outdoor scenarios, and additional details about this image dataset and experiment results can be found in the related publication. The OD-WeaponDetection: Pistol Detection dataset is a part of Weapon Detection Open Data.

More about Weapon Detection Open Data

The weapon datasets available here are specifically tailored for the development of intelligent video surveillance automatic systems.

An automatic weapon detection system can provide the early detection of potentially violent situations that is of paramount importance for citizens security. One way to prevent these situations is by detecting the presence of dangerous objects such as handguns and knives in surveillance videos. Deep Learning techniques based on Convolutional Neural Networks can be trained to detect this type of object.

The weapon detection task can be performed by different approaches of combining a region proposal technique with a classifier, or integrating both into one model. However, any deep learning model requires to learn a quality image dataset and an annotation according to the classification or detection tasks.

Weapon detection Open Data provides quality image datasets built for training Deep Learning models under the development of an automatic weapon detection system. Weapons datasets for image classification and object detection tasks are described and can be downloaded below. The public datasets are organized depending on the included objects in the dataset images and the target task.

Weapon Detection Open Data structure

Classification

The datasets included in this section have been designed for the classification task based on CNN deep learning models. After the training stage on these datasets, the classification models must distinguish between weapons and different common objects present in the background or handled similarly.

Detection

The datasets included in this section have been designed for the object detection task based on Deep Learning architectures with a CNN backbone. The selected images contain weapons and objects but also consider an enriched context of different background objects as well as the way objects are handled. After the training stage on these datasets, the detection models must locate and distinguish between weapons and different common objects present in the background or handled similarly.

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Dataset LinkHomepageDataset LinkResearch PaperDataset LinkBlog Post

Summary #

OD-WeaponDetection: Pistol Detection is a dataset for an object detection task. It is used in the security industry.

The dataset consists of 3000 images with 3463 labeled objects belonging to 1 single class (pistol).

Images in the OD-WeaponDetection: Pistol Detection dataset have bounding box annotations. All images are labeled (i.e. with annotations). There are no pre-defined train/val/test splits in the dataset. The dataset was released in 2020 by the University of Granada, Spain and King Abdulaziz University (KAU) Jeddah, Saudi Arabia.

Dataset Poster

Explore #

OD-WeaponDetection: Pistol Detection dataset has 3000 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 OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
OpenSample annotation mask from OD-WeaponDetection: Pistol DetectionSample image from OD-WeaponDetection: Pistol Detection
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Have a look at 3000 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
Images
Objects
Count on image
average
Area on image
average
pistol
rectangle
3000
3463
1.15
44.36%

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
pistol
rectangle
3463
38.67%
99.43%
0.06%
7px
2.33%
3226px
99.87%
203px
54.8%
7px
2%
4576px
99.9%

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 3463 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 3463
Object ID
Class
Image name
click row to open
Image size
height x width
Height
Height
Width
Width
Area
1
pistol
rectangle
armas (248).jpg
350 x 590
107px
30.57%
122px
20.68%
6.32%
2
pistol
rectangle
armas (59).jpg
192 x 256
150px
78.12%
216px
84.38%
65.92%
3
pistol
rectangle
armas (860).jpg
189 x 266
54px
28.57%
151px
56.77%
16.22%
4
pistol
rectangle
armas (1868).jpg
333 x 450
80px
24.02%
57px
12.67%
3.04%
5
pistol
rectangle
armas (1773).jpg
332 x 461
274px
82.53%
411px
89.15%
73.58%
6
pistol
rectangle
armas (2947).jpg
380 x 640
28px
7.37%
54px
8.44%
0.62%
7
pistol
rectangle
armas (2947).jpg
380 x 640
30px
7.89%
20px
3.12%
0.25%
8
pistol
rectangle
armas (1965).jpg
197 x 256
52px
26.4%
31px
12.11%
3.2%
9
pistol
rectangle
armas (629).jpg
400 x 600
90px
22.5%
178px
29.67%
6.67%
10
pistol
rectangle
armas (937).jpg
189 x 266
119px
62.96%
159px
59.77%
37.64%

License #

OD-WeaponDetection: Pistol Detection is under CC BY-SA 4.0 license.

Source

Citation #

If you make use of the OD-WeaponDetection: Pistol Detection data, please cite the following reference:

@article{OLMOS201866,
  title = {Automatic handgun detection alarm in videos using deep learning},
  journal = {Neurocomputing},
  volume = {275},
  pages = {66-72},
  year = {2018},
  issn = {0925-2312},
  doi = {https://doi.org/10.1016/j.neucom.2017.05.012},
  url = {https://www.sciencedirect.com/science/article/pii/S0925231217308196},
  author = {Roberto Olmos and Siham Tabik and Francisco Herrera},
}

Source

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

@misc{ visualization-tools-for-od-weapon-detection-pistol-detection-dataset,
  title = { Visualization Tools for OD-WeaponDetection: Pistol Detection Dataset },
  type = { Computer Vision Tools },
  author = { Dataset Ninja },
  howpublished = { \url{ https://datasetninja.com/od-weapon-detection-pistol-detection } },
  url = { https://datasetninja.com/od-weapon-detection-pistol-detection },
  journal = { Dataset Ninja },
  publisher = { Dataset Ninja },
  year = { 2024 },
  month = { jun },
  note = { visited on 2024-06-25 },
}

Download #

Dataset OD-WeaponDetection: Pistol Detection 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='OD-WeaponDetection: Pistol Detection', 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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