Universe

Vehicle Dataset Computer Vision Dataset

byAVDTask:
Object Detection
License:CC BY 4.099 views6 downloads
See all 4.6k imagesVehicle Dataset Vehicles sample showing Car, LimousineVehicle Dataset Vehicles sample showing Car, TruckVehicle Dataset Vehicles sample showing LimousineVehicle Dataset Vehicles sample showing CarVehicle Dataset Vehicles sample showing SegwayVehicle Dataset Vehicles sample showing Car, TaxiVehicle Dataset Vehicles sample showing CarVehicle Dataset Vehicles sample showing Car, TaxiVehicle Dataset Vehicles sample showing BusVehicle Dataset Vehicles sample showing VanVehicle Dataset Vehicles sample showing BusVehicle Dataset Vehicles sample showing Truck

About Vehicle Dataset Dataset

Here are a few use cases for this project:

  1. Traffic Management Systems: Computer Vision models can analyze real-time traffic information by identifying the type and number of vehicles on roads. This could help devise better traffic light timings to reduce congestion, especially during peak hours.

  2. Smart Parking Solutions: These models could identify vehicle types to allow real-time tracking and management of available parking spaces in public areas, parking lots, and high-traffic urban areas.

  3. Road Safety Enhancements: By detecting and classifying types of vehicles, the model could be used by road safety authorities to monitor traffic rules adherence. For instance, identifying whether motorbikes or bicycles are using the designated lanes.

  4. Automated Surveillance: The model can be used in surveillance systems to detect unusual activity, such as a high number of specific vehicles (like fire trucks or ambulances) indicative of an emergency situation.

  5. Autonomous Vehicle Systems: This model could function as a subsystem within broader autonomous vehicle AI to help such vehicles understand and navigate their surroundings by recognizing other vehicles around them. This can contribute to safer and more effective self-driving technology.

Use Free Car, Truck and Bus 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, Truck, Bus, Bicycle, Motorcycle"
  },
  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{ vehicle-dataset-pv0zn_dataset,
  title = { Vehicle Dataset Dataset },
  type = { Open Source Dataset },
  author = { AVD },
  howpublished = { \url{ https://universe.roboflow.com/avd/vehicle-dataset-pv0zn } },
  url = { https://universe.roboflow.com/avd/vehicle-dataset-pv0zn },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2021 },
  month = { dec },
  note = { visited on 2026-07-29 },
}

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