Invoice01 Object Detection Dataset and Pre-Trained Model by National Yang Ming Chiao Tung University

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Explore Dataset

Here are a few use cases for this project:

Digitizing Paper Invoices: The "Invoice01" model can be used to automate the process of converting physical invoices into digital format. This can significantly reduce the time and effort required in manual data entry, making it useful for businesses dealing with a large volume of transactions.
Data Extraction for Accounting Software: The model can be helpful for accounting applications to extract important details like date, items, and price from the invoices. The information could be directly imported into software systems for further processing and analysis, improving business operations.
Automated Expense Management: For companies looking to manage employee expenses efficiently, this model can be beneficial. Employees can simply upload photos of their invoices and the model can automatically extract data such as date and price to facilitate quicker and more accurate expense reporting.
Inventory Management: The model can be utilized within the retail sector for efficient inventory management. By recognizing and recording the purchased items, the model can help keep track of stock levels, identify patterns in sales, and plan for inventory restocking.
Tech Store Management: Given the model's ability to identify 'GIGABYTE', it could be particularly useful in electronics or tech-related stores for detecting hardware items mentioned in the invoice for more streamlined gadget/hardware inventory analysis and management.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            invoice01_dataset,
                            title = { Invoice01 Dataset },
                            type = { Open Source Dataset },
                            author = { National Yang Ming Chiao Tung University },
                            howpublished = { \url{ https://universe.roboflow.com/national-yang-ming-chiao-tung-university/invoice01 } },
                            url = { https://universe.roboflow.com/national-yang-ming-chiao-tung-university/invoice01 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { sep },
                            note = { visited on 2024-04-25 },
                            }