Introduction
The Safety Gear Detection application demonstrates using AI detection to identify if employees are wearing both their hard-hats and their high-visibility vests.
Benchmarks
The application includes a metrics overlay showing the camera, display, and inference timing details.
The Safety Gear Detection application contains two different models running: a person detection model and a safety-gear detection model. Statistics for each model will be noted separately where applicable. Because there are two models running, overall inference FPS is impacted.
Reported FPS and Resolutions
| Item | Frames per Second | Resolution |
| Display | 60.00 | 1920x1080 |
| Camera | 30.00 | 1920x1080 |
| Inference | 18.00 (total) | 320x320 (person detection and safety detection) |
Inference Timing Details
| Item | Timing, person detection (ms) | Timing, safety detection (ms) |
| Time to load the frame into the model | 1.81 | 7.85 |
| Running model inference on the frame | 7.95 | 40.1 |
| Decoding boxes | 0.24 | 1.67 |
Testing
The model used in this application was trained with the following specific personal protection equipment:
- Hard-hats - Pyramex Cap Style 4-Point Ratchet Suspension Bump Cap (yellow)
- High-Visibility vests - Pioneer Tear-Away Traffic High Visibility Safety Vest
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