If you’ve ever dealt with a pile of receipts and wished for an easier way to manage them, you’re in the right place! In this article, we will explore how to convert receipt images into JSON format using Optical Character Recognition (OCR) and ChatML. This method helps automate data entry, saving you time and effort.

What You Need

• Access to a receipt image
• The Paddle-OCR library for text recognition
• Knowledge of JSON format
• An environment to run code such as Jupyter Notebook

Setup Instructions

To start converting receipt images to JSON, follow these steps:

1. Install PaddleOCR: This library is essential for text recognition in images. You can install it via pip.
2. Prepare Your Image: Ensure your receipt image has good lighting and is clear.
3. Load the Model: Use the model ID mychen76mistral_ocr2json_v3_chatml.
4. Run the OCR Process: Use the code to extract text boxes from the receipt.

Understanding the Code

The following code snippet illustrates how to extract and transform the receipt data into a structured JSON format:

receipt_boxes = extract_receipt_boxes(image) # Function to get OCR boxes
result = {
    "store_name": "The Lone Pine",
    "store_address": "43 Manchester Road",
    "city": "Brisbane",
    "country": "Australia",
    "phone": "617-3236-6207",
    "invoice_number": "08000008",
    "invoice_date": "090408",
    ...
    "items": [
        {"item_name": "Carlsberg Bottle", "quantity": 2, "price": 16.00},
        {"item_name": "Heineken Draft Half Liter.", "quantity": 1, "price": 15.20},
        ...
    ],
    "total": 376.40
}

Imagine the data extraction process as sorting through a messy drawer full of receipts. Each receipt is unique, just like the items in your drawer. This code acts as a digital assistant that carefully goes through the receipts, picking out relevant information—such as store name, total amount, and item details—and placing them into a manageable JSON structure, which is like neatly organizing your receipts into a file system.

Using ChatML for Output Generation

To format the output into ChatML, follow the structure and ensure that your extracted data adheres to ChatML standards.

Troubleshooting

If you encounter issues while converting receipt images to JSON, consider these troubleshooting tips:

• Check OCR Accuracy: Ensure the receipt image is clear and well-lit. OCR works best on legible text.
• Model Compatibility: Verify that you are using the correct model ID mychen76mistral_ocr2json_v3_chatml.
• Data Structure Validation: Make sure the JSON output is well-formed. Use online JSON validators to check for syntax errors.
• Inspect Coding Errors: Look through your code for any common programming mistakes like indentation or missing commas.
• For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Conclusion

Converting receipts from images to JSON using OCR and ChatML is a powerful method to automate tedious tasks. With just a few lines of code, you can streamline your data management process and save precious time.

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.