Drowsiness Detection Computer Vision Dataset
About Drowsiness Detection 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!
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
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Use Free Awake and Drowsy Detection API
Powered by general detection model
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
Tell the agent what you want to build.
Cite This Project
LicenseCC BY 4.0If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{ drowsiness-detection-cntmz-lprt8_dataset,
title = { Drowsiness Detection Dataset },
type = { Open Source Dataset },
author = { Zeus },
howpublished = { \url{ https://universe.roboflow.com/zeus-qix39/drowsiness-detection-cntmz-lprt8 } },
url = { https://universe.roboflow.com/zeus-qix39/drowsiness-detection-cntmz-lprt8 },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { nov },
note = { visited on 2026-07-29 },
}