Universe

Total_Text_database Computer Vision Dataset

byEssamHaiderTask:
Object Detection
License:CC BY 4.0167 views16 downloads
See all 1.2k imagesTotal_Text_database Text sample showing TextTotal_Text_database Text sample showing TextTotal_Text_database Text sample showing TextTotal_Text_database Text sample showing TextTotal_Text_database Text sample showing TextTotal_Text_database Text sample showing TextTotal_Text_database Text sample showing TextTotal_Text_database Text sample showing TextTotal_Text_database Text sample showing TextTotal_Text_database Text sample showing TextTotal_Text_database Text sample showing TextTotal_Text_database Text sample showing Text

About Total_Text_database Dataset

Here are a few use cases for this project:

  1. Advertising Analysis: The model can be utilized by advertisers or marketing firms to analyze and understand the outreach and placement of their brand logos, catchphrases, and names in outdoor and indoor settings.

  2. Graffiti Detection and Analysis: Municipalities or law enforcement agencies can use this tool to identify and catalog instances of graffiti, helping in tracking vandalism and understanding patterns in urban environments.

  3. Assistive Technology: The model can be incorporated into applications to help visually impaired individuals identify and understand text in their surroundings, enhancing their ability to navigate independently.

  4. Urban Planning and Infrastructure Maintenance: City planners or infrastructure management teams can use this tool to spot check and audit signage in a city for visibility, clarity, and compliance with local regulations.

  5. Retail and Commercial Analysis: Retailers could use this model to analyze how effectively their store logos, signs, or advertisements are positioned and whether they are easily viewable or identifiable in various settings.

Use Free Text 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": "Text"
  },
  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{ total_text_database_dataset,
  title = { Total_Text_database Dataset },
  type = { Open Source Dataset },
  author = { EssamHaider },
  howpublished = { \url{ https://universe.roboflow.com/essamhaider/total_text_database } },
  url = { https://universe.roboflow.com/essamhaider/total_text_database },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2022 },
  month = { aug },
  note = { visited on 2026-07-29 },
}

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