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.

You can read more information about these dataset in Weapon detection Open Data, and related works in Weapon detection for security and video surveillance project.

Pistol classification

Pistol detection

Knife classification

Knife_detection

Weapons and similar handled objects