Universe

Sign Classification Computer Vision Dataset

byHirushiharanTask:
Object Detection
License:CC BY 4.054 views4 downloads
See all 4.2k imagesSign Classification 40 sample showing right curveSign Classification 40 sample showing busSign Classification 40 sample showing left laneSign Classification 40 sample showing busSign Classification 40 sample showing left laneSign Classification 40 sample showing left redSign Classification 40 sample showing busSign Classification 40 sample showing cross blueSign Classification 40 sample showing left laneSign Classification 40 sample showing busSign Classification 40 sample showing cross blueSign Classification 40 sample showing right red

About Sign Classification Dataset

Here are a few use cases for this project:

  1. Traffic Management Systems: The "Sign Classification" model can be integrated into smart city traffic management systems to identify and interpret various road signs. This assists in understanding and predicting traffic flow and patterns to improve road safety and efficiency.

  2. Autonomous Vehicles: Autonomous vehicles could use this model to identify and interpret traffic signs in real-time, helping the vehicle to navigate effectively and follow the road rules, thus enhancing the safety level.

  3. Augmented Reality Navigation Apps: This model can be employed in AR-based GPS systems to identify street signs, which can then be enhanced or flagged in the user's view to provide additional context and ensure the user is following the correct directions.

  4. Wildlife Conservation Projects: The "Sign Classification" model can be used to identify signs of wildlife such as elephants in areas where they are expected to cross regularly. This data could assist in identifying migration patterns or traffic danger zones for wildlife in order to develop appropriate safety measures.

  5. Road Infrastructure Mapping: The model can assist in creating a detailed map of the road infrastructure, including speed limit zones, areas of specific traffic regulations, possible dangers (e.g. curves, lanes), or unusual road uses (like bus lanes). This data can be useful for urban planning, logistics, and emergency services.

Use Free Bus, Elephant and 40 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": "bus, elephant, 40, cross blue, cross yellow"
  },
  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{ sign-classification_dataset,
  title = { Sign Classification Dataset },
  type = { Open Source Dataset },
  author = { Hirushiharan },
  howpublished = { \url{ https://universe.roboflow.com/hirushiharan/sign-classification } },
  url = { https://universe.roboflow.com/hirushiharan/sign-classification },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2023 },
  month = { feb },
  note = { visited on 2026-07-29 },
}

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