🫐 GRAPES — GReylevel Analysis of ParticlES

GRAPES is a Python toolkit for quantitative analysis of grey-level intensities in X-ray tomograms of particles. It was originally developed for studying core–shell behavior, internal cracking, and void formation within individual particles extracted from tomographic datasets.

Reference / Methodology:

For detailed example use cases, see the papers:

👉 Demonstrating Faster Multi-Label Grey-Level Analysis for Crack Detection in Ex Situ and Operando Micro-CT Images of NMC Electrode

👉 Non-linear cracking response to voltage revealed by operando X-ray tomography in polycrystalline NMC811

Features

• Automated particle property extraction into a Pandas DataFrame

• Radial analysis of grey-level intensities using the GREAT2 method

• Batch processing of large particle datasets

• Utility functions for plotting, file I/O, and visualization

• Designed for high-throughput analysis of tomographic data

Core Concept

At the heart of GRAPES is the radial layer analysis: Each particle is divided into concentric layers, and properties such as mean grey-level intensity, standard deviation, and radial gradients are computed. This enables quantitative comparison of features like shell thickness, internal cracks, and material heterogeneity across thousands of particles.

Cloud Notebooks

You can explore GRAPES directly in your browser — no installation required!
Click the badges below to launch the example notebooks on Binder.

Example	Description	Binder Link
Example 1	Micro-CT example
Example 2	Nano-CT example

💡 Tip: Binder can take a minute or two to start — once loaded, the notebooks will open in JupyterLab with all dependencies preinstalled.

Repository Structure

GRAPES/
│
├── GRAPES.py          # Core analysis functions and utilities
├── examples_data/      # (Optional) Example particle datasets
├── examples/          # Example scripts and workflows
├── README.md          # Project overview (this file)
└── requirements.txt   # Python dependencies

Installation

git clone https://github.com/MPJ-Imaging/GRAPES.git
cd GRAPES
pip install -r requirements.txt

License

See the MIT License