Universe

Dynamic Road Hazard Detection Computer Vision Model

byBrijTask:
Object Detection
License:CC BY 4.0

How to use the Dynamic Road Hazard Detection Detection API

Try This Model

Drop an image here or click to upload

Or try a test image 

Code Snippets

from inference_sdk import InferenceHTTPClient

CLIENT = InferenceHTTPClient(
    api_url="https://serverless.roboflow.com",
    api_key="API_KEY"
)

result = CLIENT.infer("YOUR_IMAGE.jpg", model_id="dynamic-road-hazard-detection-v8uha/1")
Give your agent everything it needs

Or, Use Free Car, Car and Truck 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": "car, Car, truck, Truck, bus"
  },
  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 
See all 13k imagesDynamic Road Hazard Detection vehicles-YOLO-v8 sample showing bus, car, microbus, motorbikeDynamic Road Hazard Detection vehicles-YOLO-v8 sampleDynamic Road Hazard Detection vehicles-YOLO-v8 sample showing truckDynamic Road Hazard Detection vehicles-YOLO-v8 sampleDynamic Road Hazard Detection vehicles-YOLO-v8 sample showing bus, car, motorbikeDynamic Road Hazard Detection vehicles-YOLO-v8 sampleDynamic Road Hazard Detection vehicles-YOLO-v8 sample showing 2, CarDynamic Road Hazard Detection vehicles-YOLO-v8 sample showing CarDynamic Road Hazard Detection vehicles-YOLO-v8 sampleDynamic Road Hazard Detection vehicles-YOLO-v8 sample showing bus, car, motorbikeDynamic Road Hazard Detection vehicles-YOLO-v8 sampleDynamic Road Hazard Detection vehicles-YOLO-v8 sample

About Dynamic Road Hazard Detection Model

Here are a few use cases for this project:

  1. Traffic Management and Surveillance: This model can be used in traffic management systems to monitor and track different vehicle types on the road, enabling real-time updates on traffic conditions and anticipating congestion.

  2. Smart Parking Solutions: The model can be employed in smart parking lots to identify vehicle types and guide drivers to suitable parking spaces accordingly. It can also help in count vehicles ensuring efficient usage of parking space.

  3. Road Safety Applications: The system can be implemented in road safety devices to identify the incoming vehicle type, providing alerts for pedestrian and driver safety (e.g., alerting pedestrians about oncoming trucks or buses).

  4. Vehicle Classification in Transportation Research: The model can serve transportation research by classifying vehicles on highways, assisting in studies related to vehicle frequency, type variation, road usage, and emission levels.

  5. Autonomous Vehicles: This vehicle-detection model can be integrated into the system of self-driving cars to identify other vehicles on the road, aiding in decision-making for safe navigation and collision avoidance.

Cite This Project

LicenseCC BY 4.0

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

@misc{ dynamic-road-hazard-detection-v8uha_dataset,
  title = { Dynamic Road Hazard Detection Dataset },
  type = { Open Source Dataset },
  author = { Brij },
  howpublished = { \url{ https://universe.roboflow.com/brij-u4fbf/dynamic-road-hazard-detection-v8uha } },
  url = { https://universe.roboflow.com/brij-u4fbf/dynamic-road-hazard-detection-v8uha },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2025 },
  month = { oct },
  note = { visited on 2026-07-29 },
}

Similar Projects

See More