BLITZ

TL;DR

BLITZ is a matrix-based image viewer designed for handling massive datasets (25+ GB) quickly and efficiently, but also works well for single images. (i.e. it can load 21,000 images (~25GB) in 35 seconds on a gaming laptop).

Download

Download the latest release for Windows

Overview

BLITZ (Bulk Loading and Interactive Time series Zonal analysis) is an open-source image viewer developed at INP Greifswald. It is designed for rapid loading and processing of large image datasets, but is equally effective for single-image analysis.

Key Features:

• Fast Data Handling: Handles very large datasets efficiently (i.e. 21,000 images (~25GB) in just 35 seconds on a standard gaming laptop).
• Easy Data Handling: Drag-and-drop functionality for various image and video formats, including NUMPY matrices (*.npy).
• Easy-to-use: Automatic resource management for large and small datasets.
• User-Friendly Interface: Intuitive GUI with mouse-based navigation and shortcut capabilities.
• Advanced Image Processing: Matrix-based processing, with fast statistical calculations (i.e. Mean image of the 21k dataset: 1.7 seconds).
• Built on Python, with Qt and PyQtGraph for high performance and flexibility

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Documentation

• Quick Start Guide
• Core Functionalities

Development

To compile and develop locally:

1. Clone the repository:

   git clone https://github.com/CodeSchmiedeHGW/BLITZ.git
   cd BLITZ

2. Set up a virtual environment and install dependencies:

   pip install poetry
   poetry install
   poetry run python -m blitz

3. To create a binary executable:

   pyinstaller --onefile --noconsole --icon=./resources/icon/blitz.ico blitz_main.py

Additional Resources

• Example Dataset: KinPen Science Example Set
• Explore more datasets or contribute your own on INPTDAT.

License

BLITZ is licensed under the GNU General Public License v3.0.