README.md

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license: cc-by-4.0
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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.