APEX-Net: Automatic Plot Extractor Network

TL;DR

APEX-Net is a deep learning framework designed to automatically extract raw data from 2D line plot images, significantly reducing human intervention and improving accuracy in plot data retrieval.

Contribution

The paper introduces APEX-Net, a novel deep learning approach with specialized loss functions and a large-scale dataset, APEX-1M, for automatic plot data extraction.

Findings

Achieves high accuracy on the APEX-1M test set

Successfully extracts plot shapes from unseen images

Provides a user-friendly GUI for community use

Abstract

Automatic extraction of raw data from 2D line plot images is a problem of great importance having many real-world applications. Several algorithms have been proposed for solving this problem. However, these algorithms involve a significant amount of human intervention. To minimize this intervention, we propose APEX-Net, a deep learning based framework with novel loss functions for solving the plot extraction problem. We introduce APEX-1M, a new large scale dataset which contains both the plot images and the raw data. We demonstrate the performance of APEX-Net on the APEX-1M test set and show that it obtains impressive accuracy. We also show visual results of our network on unseen plot images and demonstrate that it extracts the shape of the plots to a great extent. Finally, we develop a GUI based software for plot extraction that can benefit the community at large. For dataset and more information visit https://sites.google.com/view/apexnetpaper/.