Streamlining Invoice Classification with LayoutMLv3 and Label-Studio: Simplifying Data Labeling for Precise Results
Hey folks,I’m diving into a project that involves using LayoutMLv3 for sorting through invoices. Since I’m still getting my feet wet in this area, I could really use some advice. My aim is to pull out specific details from invoices accurately, and to help me with that, I’ve turned to Label-Studio. Here’s what I’ve got planned out:Step 1: Getting the basic info from the invoices.Step 2: Teaching the machine learning model to recognize different types of invoices by analyzing their content.But, here come the questions:So, if I’ve already got all the data I need for Step 1 (and maybe even for Step 2), can I skip the manual labeling part and just use that data straight up?Let’s say I’ve got to label around 7-9 things per invoice. Do I only need to mark down the value I’m interested in, or do I have to include the key pair too?Can I plug LayoutMLv3 directly into Label-Studio so it learns as I label each invoice, or do I have to go through the extra step of converting to JSON and training it with a separate script?What’s the best way to train the model for Step 2, where it learns to classify invoices based on their content?Any tips or tricks would be awesome. Thanks a bunch in advance!