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labelforocrlpV1 Computer Vision Dataset

bybasev15Task:
Object Detection
License:CC BY 4.0145 views19 downloads
See all 4.8k imageslabelforocrlpV1 0 samplelabelforocrlpV1 0 sample showing 0, 1, 2, 4, 6, 9, ElabelforocrlpV1 0 sample showing 2, 5, 6, 7, 9, ElabelforocrlpV1 0 sample showing 0, 1, 2, 4, 9, ElabelforocrlpV1 0 sample showing 1, 2, 3, 7, 8, 9, BlabelforocrlpV1 0 sample showing 2, 3, 5, 7, 9, AlabelforocrlpV1 0 sample showing 0, 2, 3, 4, 8, ElabelforocrlpV1 0 sample showing 0, 1, 2, 3, 6, 9, BlabelforocrlpV1 0 sample showing 1, 2, 3, 7, 9, ClabelforocrlpV1 0 sample showing 1, 2, 4, 6, 9, MlabelforocrlpV1 0 sample showing 0, 1, 2, 5, 6, 7, 9, ElabelforocrlpV1 0 sample showing 0, 2, 3, 8, Z

About labelforocrlpV1 Dataset

Here are a few use cases for this project:

  1. "Character Recognition in Document Digitization": This computer vision model could be employed to develop an Optical Character Recognition (OCR) system to recognize and digitize printed or handwritten documents for better information management and retrieval.

  2. "License Plate Detection": Use this model to build a system to identify and interpret vehicle license plates. This could be used in various sectors, for example, law enforcement, parking management, or automated toll collection.

  3. "Automatic Data Entry": Businesses can use this model to extract text from various forms of inputs (printed documents, receipts etc.) and automatically populate databases, reducing human error and improving efficiency.

  4. "Accessible Reading Tools": The model could be utilized to build applications for visually impaired people, converting text into speech by recognizing and interpreting characters from a variety of objects or documents.

  5. "Educational Programs": The model could be used to develop interactive educational software where children can learn alphabets and numbers by recognizing and identifying them from a variety of mediums.

Use Free 0, 1 and 2 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": "0, 1, 2, 3, 4"
  },
  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{ labelforocrlpv1_dataset,
  title = { labelforocrlpV1 Dataset },
  type = { Open Source Dataset },
  author = { basev15 },
  howpublished = { \url{ https://universe.roboflow.com/basev15/labelforocrlpv1 } },
  url = { https://universe.roboflow.com/basev15/labelforocrlpv1 },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2023 },
  month = { jun },
  note = { visited on 2026-07-29 },
}

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