Weapons Security

Baton at a checkpoint Detection Dataset

Generate AI-labeled baton detection images at a checkpoint. Ready for YOLO, COCO, and Pascal VOC — no manual labeling required.

How to generate a baton dataset

1

Describe your object

Enter "baton" as your target object and describe the environment: "at a checkpoint".

2

Choose format & quantity

Select YOLO, COCO, or Pascal VOC. Generate 10 to 5,000 images per batch.

3

Download & train

Get a .zip with images and auto-labeled bounding boxes. Ready for Ultralytics, PyTorch, or any framework.

What's in the dataset

Images

  • AI-generated images of baton at a checkpoint
  • Varied lighting, angles, and compositions
  • High resolution suitable for model training
  • 10 to 5,000 images per job

Labels

  • Auto-generated bounding box annotations
  • Available in YOLO (.txt), COCO (.json), or Pascal VOC (.xml)
  • Python visualizer script included
  • Failed labels automatically refunded

Use cases for baton detection

A baton detection dataset is useful for training object detection models that need to identify and locate baton instances at a checkpoint. Common applications include real-time monitoring, automated counting, safety compliance, quality inspection, and autonomous systems.

Using synthetic data lets you generate edge cases and rare scenarios that are difficult to capture in the real world. Need baton at a checkpoint at different times of day, weather conditions, or angles? AI generation gives you infinite variety without the cost of manual photography and labeling.

Pricing

$0.10 per image (generation + labeling + formatting)
  • No subscriptions — prepaid wallet, pay only for what you generate
  • Failed images and labels automatically refunded
  • Minimum deposit: $5 (that's 50 images)
Start Generating →

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