Universe

A Besar Computer Vision Model

byMaskimTask:
Object Detection
License:CC BY 4.0204 views10 downloads

How to use the A Besar Detection API

Try This Model

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Code Snippets

from inference_sdk import InferenceHTTPClient

CLIENT = InferenceHTTPClient(
    api_url="https://serverless.roboflow.com",
    api_key="API_KEY"
)

result = CLIENT.infer("YOUR_IMAGE.jpg", model_id="a-besar/23")
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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": "A, B, D, E, G"
  },
  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 
See all 604 imagesA Besar Letters sample showing NA Besar Letters sample showing OA Besar Letters sample showing EA Besar Letters sample showing TA Besar Letters sample showing WA Besar Letters sample showing DA Besar Letters sample showing VA Besar Letters sample showing UA Besar Letters sample showing OA Besar Letters sample showing VA Besar Letters sample showing UA Besar Letters sample showing E

About A Besar Model

Here are a few use cases for this project:

  1. Educational Applications: "A Besar" can be used in educational software and apps to help young children learn the alphabet and improve their letter recognition skills. By analyzing images of handwritten or printed letters, the model can provide feedback on correct letter identification or even guide children in writing the correct letter shapes.

  2. Optical Character Recognition (OCR): Companies dealing with large amounts of printed or handwritten text can use "A Besar" to automate the process of digitizing documents. This can save time, reduce manual errors, and facilitate easy data storage and retrieval.

  3. Assistance for Those with Visual Impairments: "A Besar" can be used to develop tools to aid individuals with visual impairments in daily reading tasks. By recognizing letter shapes within the visual environment, an app or device could provide audio feedback or translate text to braille for easier access to information.

  4. License Plate Recognition: The model can be leveraged for an automated license plate recognition system that helps in identifying vehicle registration plate numbers. This can be particularly beneficial for security, parking management, and traffic control applications.

  5. Sign Language Recognition: "A Besar" can be integrated into a system that recognizes finger-spelled letters in sign language, enabling a more seamless communication experience for those who rely on sign language to express themselves. By analyzing images or videos of finger-spelled letters, the model can help interpret the intended message and provide real-time translation assistance.

Cite This Project

LicenseCC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{ a-besar_dataset,
  title = { A Besar Dataset },
  type = { Open Source Dataset },
  author = { Maskim },
  howpublished = { \url{ https://universe.roboflow.com/maskim/a-besar } },
  url = { https://universe.roboflow.com/maskim/a-besar },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2022 },
  month = { jun },
  note = { visited on 2026-07-29 },
}

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