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Driver Drowsiness Detection & Monitoring Dataset (Synthetic)
Synthetic data for testing Driver Monitoring Systems. Compliant with Euro NCAP & GSR safety standards.
Description:
Building AI that detects if a driver is tired or distracted is difficult. Real-world data is messy, and humans often make mistakes when labeling exactly how "closed" an eye is. This is a free sample dataset (150+ images) generated by Simuletic. We created this to show how synthetic data can solve the problem of accuracy. Since the images are computer-generated, we know exactly where the driver is looking and how open their eyes are—down to the pixel. Download the full 10k+ images dataset: Visit https://simuletic.com
What is in this sample?
Perfect Labels: No guessing. The data contains exact values for where the head is turning and where the eyes are looking. Safety Standard Ready: The data is labeled to help you meet Euro NCAP and GSR (General Safety Regulation) rules. Microsleep Detection: We include the "PERCLOS" score, which measures exactly how drowsy the driver is. Simple Format: You get standard .jpg images and easy-to-read .json files with the data.
What you get:
/images: The raw frames of the driver. /labels: The data files (JSON) telling you head pose, eye state, and gaze zone.
Need more data? This sample is just for testing. If you need to train a full production model, our Enterprise Dataset at simuletic.com includes: 50,000+ Images Night Mode (Infrared/NIR simulation) Edge Cases: Drivers wearing sunglasses, masks, and hats.
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