Drownsy Dectetion v2 Computer Vision Dataset
About Drownsy Dectetion v2 Dataset
This is a model which detects the status of people' alertness. To train this model, we cloned images of two exampled models which are: Dowsiness Image and Dowsiness Detection. Then, we changed and catergorised these images' labels into two kinds: 'buonngu' and 'tinhtao' . The results of this models can apply into detecting status of drivers' alertness and warning whenever the status describes 'buonngu'. However, this model just provides for our project purpose and there are some limitiations.
Use Free Buon_Ngu and Tinh_Tao 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": "Buon_Ngu, Tinh_Tao"
},
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
Roboflow Agent
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{ drownsy-dectetion-v2-iewns_dataset,
title = { Drownsy Dectetion v2 Dataset },
type = { Open Source Dataset },
author = { DMSTEST },
howpublished = { \url{ https://universe.roboflow.com/dmstest/drownsy-dectetion-v2-iewns } },
url = { https://universe.roboflow.com/dmstest/drownsy-dectetion-v2-iewns },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2025 },
month = { apr },
note = { visited on 2026-07-29 },
}