Drowiness Computer Vision Dataset

bytestingTask:
Object Detection
License:CC BY 4.0

About Drowiness Dataset

Overview

The Drowsiness dataset is a collection of images of a person in a vehicle (Ritesh Kanjee, of Augmented Startups) simulating "drowsy" and "awake" facial postures. This dataset can easily be used as a benchmark for a "driver alertness" or "driver safety" computer vision model.

Example Footage!

Distracted Driver Model - Example Footage

Training and Deployment

The Drowsiness model has been trained with Roboflow Train, and available for inference on the Dataset tab. We have also trained a YOLOR model for robust detection and tracking of a fatigued driver. You can learn more here: https://augmentedstartups.info/YOLOR-Get-Started

About Augmented Startups

We are at the forefront of Artificial Intelligence in computer vision. With over 94k subscribers on YouTube, we embark on fun and innovative projects in this field and create videos and courses so that everyone can be an expert in this field. Our vision is to create a world full of inventors that can turn their dreams into reality.

Use Free Awake and Drowsy Detection API

Powered by general detection model

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": "awake, drowsy"
  },
  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 

Cite This Project

LicenseCC BY 4.0

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

@misc{ drowiness-dw7gi-530tb_dataset,
  title = { Drowiness Dataset },
  type = { Open Source Dataset },
  author = { testing },
  howpublished = { \url{ https://universe.roboflow.com/testing-slbda/drowiness-dw7gi-530tb } },
  url = { https://universe.roboflow.com/testing-slbda/drowiness-dw7gi-530tb },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2025 },
  month = { jan },
  note = { visited on 2026-07-29 },
}

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