Automate Handwritten Code Evaluation with AI and OCR
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This n8n workflow automates the evaluation of handwritten codes extracted from images. It leverages AI for accurate text extraction and calculates a similarity score against expected outputs, streamlining quality control processes.
About This Workflow
This powerful n8n template automates the tedious task of evaluating handwritten codes. By integrating Optical Character Recognition (OCR) powered by AI and robust string similarity algorithms, it accurately extracts handwritten codes from images and compares them against a predefined dataset of expected outputs. The workflow calculates a character-by-character text similarity score, where a score of 1 indicates a perfect match. This ensures high precision in quality control and data validation. The process begins by fetching a dataset of code images and their expected values, then uses an AI model to extract the handwritten code, calculates the Levenshtein distance, and finally sets a similarity metric. This template is ideal for scenarios requiring automated verification of handwritten data entries or quality checks on scanned documents containing codes.
Key Features
- AI-powered handwritten code extraction from images using advanced language models.
- Precise character-by-character similarity scoring against expected codes.
- Integration with Google Sheets for seamless dataset management.
- Webhook trigger for real-time processing and integration with other systems.
- Customizable code format validation to ensure data integrity.
How To Use
- Set up Google Sheets: Ensure your dataset of handwritten code images (with their URLs) and expected outputs is properly formatted in a Google Sheet and accessible via the provided link. Update the
When fetching a dataset rownode with your specific Google Sheet URL and ensure your n8n has the necessary Google Sheets credentials. - Configure AI Model: In the
Extract code from imagenode, ensure your OpenAI API key is configured and select your preferred model (e.g.,gpt-4o). Adjust the prompt to precisely match the format and constraints of your handwritten codes. - Connect Webhook (Optional): If you intend to trigger this workflow externally, configure the
Webhooknode and set up a corresponding endpoint in your external application. TheMatch webhook formatnode will help structure the incoming request. - Review and Run: Review the connections between nodes, especially the data flow from image download to AI extraction and then to the string distance calculation. Run the workflow to test its accuracy with your dataset.
Apps Used
Workflow JSON
{
"id": "f93a290f-e163-4fb8-8513-e8e97f62c108",
"name": "Automate Handwritten Code Evaluation with AI and OCR",
"nodes": 24,
"category": "DevOps",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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ID: f93a290f-e163...
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