Weapon Detection

Weapon detection is the need of today. It plays a crucial role in many applications, such as hostage scenes, surveillance of sensitive areas, anti-terrorist operations, etc. To make the weapon detection model more efficient, we introduce a weapon dataset, named IITP-W, that captures the following properties: a) images depicting real-world scenarios, including complex backgrounds, diverse lighting conditions, object occlusions, and varying image resolutions, b) images having large and small weapons, c) absence of images sharing identical information, and d) exclusion of synthetic images. The dataset includes three types of weapons: (1) Short gun (2) long guns and (3) knife. The IITP-W dataset consists of 4292 instances of short guns, 1047 instances of knifes and 5447 instances of long guns with complex backgrounds, varied sizes, different lightening conditions and different resolutions. The short gun category includes images of real guns belonging to 30 different types in different firing statuses. Similarly, long gun category includes images of real gun belonging 61 different types. Figure 2 depicts images from existing and proposed datasets, highlighting the differences. Additionally, Table 1 furnishes details such as data size, image count with plain backgrounds and synthetic images for both existing and proposed datasets. The dataset is available for download at: www.iitp.ac.in/~halder/Prj/Dataset/IITP-W.rar