Universe

final Computer Vision Dataset

byJagadeeswarTask:
Object Detection
License:CC BY 4.032 views2 downloads
See all 1.5k imagesfinal car samplefinal car sample showing Carfinal car sample showing busfinal car sample showing Carfinal car sample showing Carfinal car sample showing Truckfinal car sample showing Truckfinal car sample showing Carfinal car samplefinal car sample showing busfinal car sample showing busfinal car sample showing Truck

About final Dataset

Here are a few use cases for this project:

  1. Traffic Surveillance: With its ability to identify various vehicle types, the "final" model can be used for real-time traffic monitoring - detecting and classifying vehicles on the road. This data can provide valuable insights for managing traffic flow and congestion, thus improving urban planning and infrastructure development.

  2. Vehicle Inventory Management: Companies like car dealerships and transport fleets can use the model to automate the inventory check process. It can quickly identify and classify vehicles, providing updates on their current state.

  3. Emergency Situations Response: Public safety departments and emergency responders can use the information provided by the model to assess the type of vehicles involved in an incident. It could help dispatch the appropriate response team more efficiently (fireengine for fire, ambulance for medical emergencies).

  4. Autonomous Vehicles: The model can be integrated into autonomous driving technology to help self-driving cars identify and differentiate between various vehicle types - a critical feature for making informed decisions on movement and navigation.

  5. Urban Planning Research: Municipalities and city planners can benefit from the accurate assessment of vehicle types on the road at different times and locations. This data can aid in infrastructure development and public transport planning.

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, Bike, ambulance"
  },
  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{ final-pihsh_dataset,
  title = { final Dataset },
  type = { Open Source Dataset },
  author = { Jagadeeswar },
  howpublished = { \url{ https://universe.roboflow.com/jagadeeswar-jlqdr/final-pihsh } },
  url = { https://universe.roboflow.com/jagadeeswar-jlqdr/final-pihsh },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2022 },
  month = { sep },
  note = { visited on 2026-07-29 },
}

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