naiveHobo/InvoiceNet
Deep neural network trained on Keras/TensorFlow that parses invoice PDFs and images to extract structured billing fields.
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InvoiceNet is a deep learning system for extracting structured information from invoice documents. It uses convolutional neural networks built with Keras and TensorFlow to process PDF and image inputs, identify key fields like amounts, dates, and vendor information, and output structured data. The project includes a GUI for viewing invoices and annotating training data, along with scripts for preparing datasets and training custom models on domain-specific invoice formats.
Frequently asked
- What is naiveHobo/InvoiceNet?
- Deep neural network trained on Keras/TensorFlow that parses invoice PDFs and images to extract structured billing fields.
- Is InvoiceNet open source?
- Yes — naiveHobo/InvoiceNet is open source, released under the MIT license.
- What language is InvoiceNet written in?
- naiveHobo/InvoiceNet is primarily written in Python.
- How popular is InvoiceNet?
- naiveHobo/InvoiceNet has 2.7k stars on GitHub.
- Where can I find InvoiceNet?
- naiveHobo/InvoiceNet is on GitHub at https://github.com/naiveHobo/InvoiceNet.