document-ocr

Effortlessly Classify Persian Handwritten Digits with AI

26 Apr 2025
Effortlessly Classify Persian Handwritten Digits with AI

The Persian Digit Detector is a powerful tool designed to help developers seamlessly integrate digit recognition capabilities into their applications. By utilizing advanced Optical Character Recognition (OCR) technology, this service allows you to detect and classify single Persian (Farsi) handwritten digits from images. The benefits of using this service include speed, accuracy, and the ability to simplify the digit recognition process, making it an invaluable asset for applications in education, finance, and data entry.

Common use cases for the Persian Digit Detector include automating data entry from handwritten forms, enhancing educational tools for Persian language learners, and improving accessibility for users who rely on handwritten inputs. Whether you’re building a mobile app or a web-based solution, this service provides an efficient way to interpret handwritten digits without extensive manual intervention.

Prerequisites

To get started with the Persian Digit Detector, you will need a Cognitive Actions API key and a basic understanding of making API calls.

Classify Persian Handwritten Digit

The "Classify Persian Handwritten Digit" action is designed to detect and classify single Persian handwritten digits by processing an uploaded photo. This action addresses the challenge of recognizing Persian digits from images, enabling developers to incorporate digit recognition into their applications easily.

Input Requirements

To use this action, you must provide an input image that is accessible via a valid URI. The input schema requires the following:

  • Image: A string that represents a valid URI pointing to the image location.

Example input:

{
  "image": "https://replicate.delivery/pbxt/Ix2YOFLCHGWq28maJELHDWWhd9Sap7Yac1A8SLOdgTwGVQdz/8sample.png"
}

Expected Output

The output of this action will be a processed image that displays the classified digit along with any relevant annotations. The output will be a URI pointing to the processed image.

Example output:

https://assets.cognitiveactions.com/invocations/250a228b-e639-42f1-b39d-053a30ce4ac6/b48d3e11-c55b-48aa-b710-a08c76bf1254.png

Use Cases for this Specific Action

This action is particularly useful in scenarios where handwritten Persian digits need to be converted into a machine-readable format. Here are a few specific use cases:

  • Data Entry Automation: Streamline the data entry process for forms filled with handwritten Persian digits, reducing the need for manual input.
  • Education Applications: Enhance learning tools that require digit recognition, allowing students to interactively engage with Persian numerals.
  • Financial Applications: Improve accuracy in financial applications that process handwritten checks or invoices, ensuring reliable digit recognition.
import requests
import json

# Replace with your actual Cognitive Actions API key and endpoint
# Ensure your environment securely handles the API key
COGNITIVE_ACTIONS_API_KEY = "YOUR_COGNITIVE_ACTIONS_API_KEY"
# This endpoint URL is hypothetical and should be documented for users
COGNITIVE_ACTIONS_EXECUTE_URL = "https://api.cognitiveactions.com/actions/execute"

action_id = "7d884014-21c8-4d6d-9741-aa1c64f88e93" # Action ID for: Classify Persian Handwritten Digit

# Construct the exact input payload based on the action's requirements
# This example uses the predefined example_input for this action:
payload = {
  "image": "https://replicate.delivery/pbxt/Ix2YOFLCHGWq28maJELHDWWhd9Sap7Yac1A8SLOdgTwGVQdz/8sample.png"
}

headers = {
    "Authorization": f"Bearer {COGNITIVE_ACTIONS_API_KEY}",
    "Content-Type": "application/json",
    # Add any other required headers for the Cognitive Actions API
}

# Prepare the request body for the hypothetical execution endpoint
request_body = {
    "action_id": action_id,
    "inputs": payload
}

print(f"--- Calling Cognitive Action: {action.name or action_id} ---")
print(f"Endpoint: {COGNITIVE_ACTIONS_EXECUTE_URL}")
print(f"Action ID: {action_id}")
print("Payload being sent:")
print(json.dumps(request_body, indent=2))
print("------------------------------------------------")

try:
    response = requests.post(
        COGNITIVE_ACTIONS_EXECUTE_URL,
        headers=headers,
        json=request_body
    )
    response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx)

    result = response.json()
    print("Action executed successfully. Result:")
    print(json.dumps(result, indent=2))

except requests.exceptions.RequestException as e:
    print(f"Error executing action {action_id}: {e}")
    if e.response is not None:
        print(f"Response status: {e.response.status_code}")
        try:
            print(f"Response body: {e.response.json()}")
        except json.JSONDecodeError:
            print(f"Response body (non-JSON): {e.response.text}")
    print("------------------------------------------------")

Conclusion

The Persian Digit Detector provides developers with an efficient and reliable way to classify handwritten Persian digits. With its straightforward API integration, this service opens the door to numerous applications, from educational tools to automated data processing systems. By leveraging this technology, you can enhance user experiences and streamline your workflows. As a next step, consider exploring how this action can be integrated into your existing applications to unlock new functionalities and improve digit recognition capabilities.

← Back to All Articles