Just a few months ago I went off on a new journey in search of new experiences in Portugal! However, during the initial months of my stay, I encountered unexpected challenges, such as the lack of financial control…
Like many others who move to a new country, I found myself caught up in a big net of activities and emotions. From finding accommodation (if you’re dealing with that too, check these articles about how to find accommodation in Lisbon and Porto!) to dealing with bureaucratic processes and adjusting to a new culture, my attention was divided between various tasks. So much so that I neglected the importance of maintaining proper organization and efficient expense tracking.
The absence of accurate tracking of my expenses made it challenging to understand where my money was being allocated and that made me take poor financial decisions. Fortunately, that experience gave me an idea, a simple program utilizing image recognition through artificial intelligence that could track supermarket expenses, providing expenses data for a clear and organized view of spending for people moving here.
In this article, I will share with you the steps to implement this solution. You will discover how to use image recognition to read supermarket receipts and potentially integrate this data into a finance management program that can bring significant benefits to tracking your personal finances in Portugal.
Step-by-Step Guide: Automating Expense Tracking with Receipt Recognition
1. Extracting Text from Receipts Using OCR
To begin with, we implement Optical Character Recognition (OCR) techniques to extract text from supermarket receipts. This is possible thanks to the powerful pytesseract library. By using OpenAI’s ChatGPT, an advanced language model, we have crafted the code below to execute this task:
2. Processing Extracted Text and Extracting Products
Once the text is extracted, it goes through further processing to extract relevant information, such as the purchased products. This can be done with various methods, including regular expressions (Regex) or other text processing techniques. In this example, we output the extracted products as a list of strings:
3. Converting Products to JSON Format
To facilitate data integration with potential finance management programs, the extracted products are converted into JSON format. JSON (JavaScript Object Notation) provides a standardized way to structure and exchange data. Here is the code snippet for this:
The main code finishes wrapping every method implemented:
Automating Expense Tracking with Receipt Recognition: Final Thoughts
Controlling your finances when moving to Portugal is crucial for a smooth transition and a solid financial foundation. The code provided in this article offers an initial solution using image recognition to read supermarket receipts and extract product data. This data can easily be integrated into various finance management programs, giving individuals and businesses tools to track expenses, make informed financial decisions, and simplify accounting tasks.
It’s important to note that the solution presented here is not the final product, but a starting point for further development. As someone who has experienced the challenges of managing finances during a relocation, I understand the importance of flexibility and customization. In addition, as an advocate of open-source code, I believe in the power of collaboration and the freedom to modify and improve upon existing solutions. By utilizing the code snippets provided and tailoring them to your specific needs, you can create a personalized finance management system that truly fits your requirements and maybe help others colleagues.
Looking ahead, there are countless possibilities of integrating this code into a diverse array of projects. A personal budgeting application that empowers you to take charge of your finances, or an AI-powered financial assistant that guides you towards financial success.
Here you can find the code for forking and testing on github.
