This repository contains
- itl2 project, a C++ Image analysis Template Library (version 2). It contains a small number of parallelized algorithms for processing 3D volume images e.g. from computed tomography scanners.
- pi2 program (Process Image 2) that exposes functionality of itl2 library for end users. It also adds the possibility to distribute processing of large images to a cluster.
- pi2py and pi2cs libraries that are used to access pi2 functionality from Python and C# environments.
- nr_stitcher Python program that can be used for non-rigid stitching or terabyte-scale volume image mosaics.
Pi2 is not intended to be a replacement for huge libraries like ITK and VTK. Instead, it is meant to be simple, performant, and easily extensible program well suitable for original author's own algorithm development and analysis tasks. It has been very useful for the author during the last years but... your mileage may vary.
The user-oriented help of pi2, including examples, can be read at ReadTheDocs.
Pre-built binaries for Windows can be downloaded from the releases page.
- Compactness: Compact package such that the version of the program used to process the data can be archived along the data - at least in principle.
- Simplicity: Everything must be as simple and understandable as possible. Therefore, "C with classes" approach is chosen. Every operation is preferably a simple function call. Only a minimal number of stateful objects is used.
- No black/gray boxes: Where possible, implementations of algorithms are not hidden behind multiple levels of derived classes and template specializations. Implementation must be as readable as possible even for inexperienced developers.
- Performance: All algorithms should be as performant as possible and parallelized, but optimization efforts must be focused towards bottlenecks. OpenMP has been chosen as threading library. Code should be written such that automatic SIMD compilation is easy. For the original author this point is easier to ensure if iteration is explicit and not hidden inside iterator objects. Therefore, iteration is made using explicit loops.
- When there are multiple possibilities, the library should automatically choose the most performant algorithm.
- Algorithms are designed for 2D and 3D images unless nD implementation is simpler than implementation bound to specific image dimensions.
- Complex operations are not hidden inside operator overloads. If a calculation might take long time for a big image, it should be initiated using a function call.
When building from the source, consider using branch 'experimental'. The most recent, but possibly buggy, changes are there.
Build instructions for different platforms can be found here:
This software is licensed under GNU General Public License v3.0.
Some external parts of the software (that might be statically or dynamically linked depending on configuration) are licensed under their respective licenses. Please run pi2 license for most up-to-date information.
The source code repository is divided into two main branches: master and experimental. The master branch contains the latest 'stable' and therefore more tested version. The experimental branch contains work in progress.
Versions are indicated using tags in the form "vX.Y.Z", e.g. v4.6.17. Version numbers that do not contain third part (.Z) are 'stable' versions and snapshots of the master branch in some well-selected state. Version numbers that contain the third number (.Z) correspond to experimental branch in some usable but no thoroughly tested state (e.g., new functionality, quick bug fixes).
Version numbers below v4.4.2 may not follow the above conventions.