Universe

Weapon-Detection-Test Computer Vision Dataset

byPublic securityTask:
Object Detection
License:CC BY 4.02 views

How to use the Weapon-Detection-Test Detection API

Try This Model

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Or try a test image 

Code Snippets

from inference_sdk import InferenceHTTPClient

CLIENT = InferenceHTTPClient(
    api_url="https://serverless.roboflow.com",
    api_key="API_KEY"
)

result = CLIENT.infer("YOUR_IMAGE.jpg", model_id="public-security/weapon-detection-test-zmk0t-instant-1")
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Code
pip install inference-sdk
# 1. Import the library
from inference_sdk import InferenceHTTPClient

# 2. Connect to your workspace
client = InferenceHTTPClient(
  api_url="https://serverless.roboflow.com",
  api_key="API_KEY"
)

# 3. Run your workflow on an image
result = client.run_workflow(
  workspace_name="<YOUR_WORKSPACE>",
  workflow_id="<YOUR_WORKFLOW_ID>",
  images={
    "image": "YOUR_IMAGE.jpg"  # Path to your image file
  },
  parameters={
    "classes": "phone, object, wallet, firearm, melee_weapon"
  },
  use_cache=True  # cache workflow definition for 15 minutes
)

# 4. Get your results
print(result)

Run on custom image

Drop an image here or click to upload

Detecting classes:
Or try a test image 
See all 25k imagesWeapon-Detection-Test weapons sample showing objectWeapon-Detection-Test weapons sample showing firearmWeapon-Detection-Test weapons sample showing phoneWeapon-Detection-Test weapons sample showing melee_weaponWeapon-Detection-Test weapons sample showing melee_weaponWeapon-Detection-Test weapons sample showing melee_weaponWeapon-Detection-Test weapons sample showing melee_weaponWeapon-Detection-Test weapons sample showing object, phoneWeapon-Detection-Test weapons sample showing firearmWeapon-Detection-Test weapons sample showing firearmWeapon-Detection-Test weapons sample showing objectWeapon-Detection-Test weapons sample showing object

About Weapon-Detection-Test Model

Dataset personalizado para detección de objetos peligrosos y objetos distractores en entornos de videovigilancia mediante visión por computadora. El conjunto de datos fue construido a partir de la combinación y reorganización de múltiples datasets públicos disponibles en Roboflow Universe, integrando clases relacionadas con armas de fuego, armas blancas y objetos cotidianos comúnmente confundidos con armas.

El dataset fue diseñado específicamente para entrenamiento de modelos YOLO orientados a aplicaciones de seguridad y monitoreo en tiempo real. Las clases fueron reorganizadas y unificadas para mejorar la generalización del modelo y reducir falsos positivos en escenarios reales de CCTV.

Las categorías finales utilizadas son:

firearm: pistolas, rifles, escopetas y armas de fuego similares. melee_weapon: cuchillos, navajas y armas blancas. object: herramientas y objetos distractores como taladros, destornilladores, llaves, martillos, mochilas, laptops, botellas y controles remotos. phone: teléfonos celulares y dispositivos móviles. wallet: billeteras, monederos, tarjetas y objetos similares.

El dataset incluye imágenes en distintos contextos y condiciones:

armas en mano, distintos ángulos y escalas, iluminación variable, fondos complejos, escenas tipo CCTV.

Cite This Project

LicenseCC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{ weapon-detection-test-zmk0t_dataset,
  title = { Weapon-Detection-Test Dataset },
  type = { Open Source Dataset },
  author = { Public security },
  howpublished = { \url{ https://universe.roboflow.com/public-security/weapon-detection-test-zmk0t } },
  url = { https://universe.roboflow.com/public-security/weapon-detection-test-zmk0t },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2026 },
  month = { apr },
  note = { visited on 2026-07-29 },
}

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