Universe

testdigit Computer Vision Model

byChristoph PonathTask:
Object Detection
License:CC BY 4.074 views5 downloads

How to use the testdigit Detection API

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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="testdigit/5")
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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": "-, 0, 1, 2, 2-"
  },
  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 5.1k imagestestdigit testdigit sample showing -, 1, 5, BBtestdigit testdigit sample showing -, 0, 5, BBtestdigit testdigit sample showing -, 0, 5, BBtestdigit testdigit sample showing -, 1, 4, 5, BBtestdigit testdigit sample showing -, 1, 3, 7, BBtestdigit testdigit sample showing 8, BBtestdigit testdigit sample showing -, 1, 5, BBtestdigit testdigit sample showing -, 1, 2, 4, 5, 7, BBtestdigit testdigit sample showing -, 0, 1, 6, 9, BBtestdigit testdigit sample showing -, 0, 1, 3, 6, BBtestdigit testdigit sample showing -, 1, 3, 5, BBtestdigit testdigit sample showing -, 0, 5, BB

About testdigit Model

Here are a few use cases for this project:

  1. Educational Tools: This computer vision model can be integrated into educational software, assisting students in learning numerical and symbolic comprehension. For instance, recognizing and categorizing handwritten digits and symbols to facilitate learning mathematics.

  2. Optical Character Recognition (OCR): This model can be used to recognize and categorize digits and symbols in scanned documents or photos, aiding in digitization and data extraction purposes.

  3. Handwriting Recognition Systems: It can be applied in handwriting recognition systems to identify and categorize unique handwritten digits or characters, supporting automated evaluation or data entry.

  4. Accessibility Applications: It can support the creation of tools for visually impaired individuals, by recognizing text and symbols in physical documents and producing spoken output.

  5. Automated Testing Applications: In a testing or examination scenario, the model can automatically grade multiple-choice tests or quizzes by recognizing and categorizing filled answer bubbles or handwritten digits/symbols.

Cite This Project

LicenseCC BY 4.0

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

@misc{ testdigit_dataset,
  title = { testdigit Dataset },
  type = { Open Source Dataset },
  author = { Christoph Ponath },
  howpublished = { \url{ https://universe.roboflow.com/christoph-ponath/testdigit } },
  url = { https://universe.roboflow.com/christoph-ponath/testdigit },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2023 },
  month = { jul },
  note = { visited on 2026-07-29 },
}

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