Graph Digitizer

Many teachers encounter graphs in textbooks, reports, or PDFs that lack the underlying numbers. Graph Digitizer is a compact, easy-to-use GUI that sits between a quick demo and a full-featured extractor: it provides a simple point-and-click workflow (load an image, calibrate axes, click or auto-trace points) for non-technical users while still offering optional advanced features when needed.

Graph Digitizer v1.1 — Java 21 Edition

This project has moved to a modern Java 21 / JavaFX implementation. The release available in this repo is a Java-based desktop application (version 1.0) intended for teachers and researchers who need an easy way to extract numeric data from raster images of graphs.

If you prefer a quick run without building from source, Windows users can download a pre-built x64 executable from the GitHub release page — no Java installation required. Developers and power users can build and run the application locally (see commands below).

Documentation and downloads

The project includes comprehensive documentation covering all aspects of the tool:

User Documentation:

• Quick Reference Guide: QUICK_REFERENCE.md — keyboard shortcuts and common tasks
• Accessibility docs: ACCESSIBILITY.md, ACCESSIBILITY_QUICK_START.md, ACCESSIBILITY_IMPLEMENTATION_COMPLETE.md (audit fixes applied), and ACCESSIBILITY_CHECKLIST.md

Developer Documentation:

• Developer Guide: DEVELOPER.md — architecture, patterns, and extension guide
• Project Summary: PROJECT_SUMMARY.md — complete project overview
• Documentation Index: INDEX.md — comprehensive index of all documentation

Advanced Topics:

• Packaging & Distribution: packaging/README.md — instructions for AppImage/DEB/RPM/DMG/EXE/MSI installers
• jlink/jpackage Guide: docs/JPACKAGE.md — runtime images, cross-architecture builds, and native packaging
• Packaging Scripts: scripts/README.md — helper scripts including Windows MSI generation

API Documentation:

• Latest Javadoc: API Documentation — generated from current main branch
• Versioned archives available per release (e.g., /1.1/, /1.2/)

You can run the packaged JAR (after building) with:

java -jar target/graph_digitizer_1.0-beta.jar

Or run directly from Maven while developing:

mvn javafx:run

If you want a single distributable for end users, see the Packaging & Distribution docs for jlink + jpackage recipes, or download the pre-built Windows executable from the releases page.

Quick start (teacher-friendly)

For Windows users with the pre-built executable:

1. Visit the GitHub release page
2. Download the Windows x64 executable
3. Run it directly — no installation or Java setup required
4. Skip to step 3 below

For other platforms or building from source:

1. Install Java 21 (or later) on your computer. If you don’t have Java installed, the packaging instructions describe creating a self-contained installer so end users don’t need Java installed.
   • For Windows 11, the easiest way is:
     • Open your terminal or command prompt
     • Type the following command and press enter:

       winget install Microsoft.OpenJDK.21
     

     • After installation is complete, verify Java is installed by typing:

      java -version
     

   • For macOS: brew install openjdk@21
   • For Linux: Use your package manager (e.g., apt-get install openjdk-21-jdk)

2. Download or clone the repository and follow the README to build the app:

   mvn clean package
   java -jar target/graph_digitizer_1.0-beta.jar
   

Digitizing your graph (all platforms):

1. Load a PNG or JPEG of the graph and press Calibrate to set four known points on the axes.
2. Select a dataset color and click points on a curve (or use Auto-trace for clearly colored lines).
3. Export to CSV to use in Excel/Google Sheets, or save the project as JSON to preserve axis metadata and colors.

This workflow is made to avoid command-line steps for everyday classroom use — teachers can run the packaged app and use the GUI only.

A quick screenshot of the application is shown below to give a sense of the interface (calibration controls at left, image/canvas in the center, and dataset controls at the right).

Screenshot shows a sample session. Associated sample files: Sample_Graph_20251119-073453.json and Sample_Graph_20251119-073453.csv.

Example outputs and sample files

Below are small sample files you can download and open to see the exact formats produced by Graph Digitizer. They live in the assets/data folder of this site.

• General example (six datasets, 5 points each): graph_digitizer_example.json and graph_digitizer_example.csv
• Log-scale example (x axis logarithmic): graph_digitizer_example_log.json and graph_digitizer_example_log.csv
• Missing values example (nulls / empty cells): graph_digitizer_example_missing.json and graph_digitizer_example_missing.csv

Short CSV preview (first three rows of the general example):

x,Dataset_1,Dataset_2,Dataset_3,Dataset_4,Dataset_5,Dataset_6
0.0,0.5,0.8,0.2,1.0,0.4,0.6
1.0,1.2,1.5,0.9,1.9,0.7,1.1

Use the JSON files if you want full project metadata (axis ranges, log flags, colors) and the CSV files for quick spreadsheet analysis.

First example dataset (JSON excerpt):

{
  "name": "Dataset 1",
  "color": "#1f77b4",
  "points": [[0.0, 0.5], [1.0, 1.2], [2.0, 2.4], [3.0, 3.1], [4.0, 4.0]]
}

Key features

• Load PNG/JPEG images and view them on a zoomable canvas.
• Non-blocking calibration with four anchor points and numeric axis ranges (linear & logarithmic support).
• Point-and-click capture plus drag-to-adjust and delete operations.
• Auto-trace for automatically extracting color-distinct curves.
• Multiple datasets (up to 6 color-coded) with independent visibility toggles.
• Linear & log scale support for both axes independently.
• Export formats: CSV (tabular, spreadsheet-compatible) and JSON (full metadata with colors and log flags).
• Responsive UI: Modern JavaFX 21 interface with intuitive controls.
• Accessibility first: Full support for screen readers, keyboard navigation, and low-vision themes (see accessibility docs for details).

Architecture highlights

The application is built with clean architecture principles:

• Core package (com.digitizer.core): Pure business logic with no GUI dependencies — coordinate transforms, color operations, and data models. All core logic can be tested and reused independently.
• Image package (com.digitizer.image): Image loading and automatic curve extraction.
• IO package (com.digitizer.io): JSON and CSV export with full format support.
• UI package (com.digitizer.ui): JavaFX-based graphical interface.

This modular design makes the tool easy to extend and embed in other applications.

Packaging options (for IT / power users)

The project includes multiple distribution options:

• Pre-built Windows x64 executable (recommended for most Windows users) — download from releases page
• Fat JAR using Maven Shade plugin — single JAR file (requires Java 21 installed)
• Native installers (MSI for Windows, DMG/PKG for macOS, DEB/RPM/AppImage for Linux) using jlink + jpackage
• Self-contained app images for each platform using jpackage

See packaging/README.md and scripts/README.md for platform-specific commands and signing instructions. The unified Maven command simplifies cross-platform builds:

mvn clean package -Dnative

Want to contribute or test?

• Browse the repo: Graph Digitizer (Java) repository
• Report issues, request features, or share classroom examples via GitHub Issues
• Read the Developer Guide for architecture details and extension points

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