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Commercial
Weapon Detection Dataset
High-quality weapon detection dataset containing 10,000 annotated images of staged individuals with visible weapons, collected from public CCTV footage and internet sources for training weapon detection models. This surveillance dataset includes bounding box annotations and rich metadata for weapons detection, small object detection, and real-time security systems across CCTV and camera-based monitoring scenarios.
-
- Images
- 10,000
- Computer Vision
- Machine learning
- Crime
- Public Safety
- Object Detection
- Computer Vision
- Machine learning
- Crime
- Public Safety
- Object Detection
High-quality weapon detection dataset containing 10,000 annotated images of staged individuals with visible weapons, collected from public CCTV footage and internet sources for training weapon detection models. This surveillance dataset includes bounding box annotations and rich metadata for weapons detection, small object detection, and real-time security systems across CCTV and camera-based monitoring scenarios.
- Computer Vision
- Machine learning
- Crime
- Public Safety
- Object Detection
-
- Images
- 10,000
Dataset Info
| Characteristic | Data |
| Description | Images of staged individuals with weapons sourced from the internet and CCTV footage. |
| Data types | Video |
| Tasks | Public Safety, Computer Vision |
| Total number of files | 10,000 |
| Labeling | Metadata (fps, resolution, has_audio, environment_type, time_of_day, weather, camera_motion, participants_count, weapon_presence) |
Technical
Characteristics
| Characteristic | Data |
| Image extension | JPG |
| Extensions of labeling file | XML, JSON |
Dataset Use Cases
FAQs
What types of annotations are provided in this dataset?
Annotations include structured metadata such as FPS, resolution, environment type, camera motion, and weapon presence. Label files are available in XML and JSON formats, supporting integration with detection systems and training pipelines.
Can I request a sample of Weapon Detection Dataset before purchase?
Yes, a free sample of the weapon detection dataset can be requested for evaluation and testing purposes. This allows you to assess image quality, annotation structure, and suitability for weapons detection and object detection models.
What are the sources of data for Unidata Weapon Detection datasets?
The dataset consists of images and videos collected from public CCTV footage and internet archives. These sources provide realistic surveillance scenarios commonly used in video surveillance and security systems.
How are Unidata datasets licensed?
Unidata datasets follow a dual-licensing model, providing free samples for testing, while full datasets are available exclusively for purchase. This approach supports evaluation before deployment in production detection systems.
How are Unidiata datasets stored and delivered?
All datasets are securely stored on AWS cloud infrastructure with high availability and scalability. Storage practices align with ISO 27001 and ISO 27701 standards to ensure data security and privacy.
How long does it take to receive Weapon Detection Dataset?
After submitting a request, Unidata reviews the requirements and completes the necessary documentation. Once the agreement is signed and payment is confirmed, the dataset will be delivered within 3–10 business days.
Is this a real-world dataset or synthetic data?
This is a real-world dataset based on actual CCTV footage and internet-sourced surveillance content.
How can this weapon detection dataset improve security AI systems?
The dataset helps train computer vision models to recognize weapons in visual scenes and support automated security monitoring. It can be used to improve AI-powered surveillance systems designed for threat detection and situational awareness.
Why are weapon bounding box annotations important for AI training?
Bounding box annotations allow models to learn the exact location and size of weapons within images. This improves object localization accuracy and helps develop detection systems capable of identifying small or partially visible objects.
Still have questions about using Unidata datasets?
Read our user-guides
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