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Selene

Platform and compiler support

Selene requires a compiler supporting C++17 and a respective conforming standard library implementation. As such, it can be built on the usual major platforms, as long as these requirements are satisfied.

The library is regularly tested on Linux, macOS, Windows, and, to a limited degree, Android (just compilation with the Android NDK). There are no obvious reasons why Selene could not be compiled on other platforms, such as iOS, FreeBSD, etc. However, these platforms are not within the testing scope (via continuous integration or otherwise).

Continuous integration testing

Continuous integration tests are currently being run on the following platforms, via Azure DevOps:

  • Ubuntu Linux 18.10, using the following compilers:
    • GCC 8.2
    • Clang 7.0 (both with and without AddressSanitizer & UndefinedBehaviorSanitizer)
    • Android NDK r19, Clang, arm64 (just compilation; not running unit tests, in absence of ARM platform)
  • Windows 10
    • Visual Studio 2017.

(CI testing on macOS is momentarily disabled, due to Azure DevOps not providing a macOS 10.14 image yet, for up-to-date compiler and standard library support. Once this is provided, CI testing on macOS shall be reinstated.)

Work in progress

Selene is work-in-progress and released as a preview. The library shall be extended and modified in the future; see below. As such, several changes in architecture and API are likely to be made.

Therefore, no API or ABI stability guarantees are currently given. API changes for versions less than 1.0 may occur at any time and break backwards compatibility.

That all said, adoption and usage are explicitly encouraged, bearing in mind that changes in code that uses Selene may be necessary.

Roadmap

At the moment, the project does not have a proper roadmap, as it currently just has one major contributor working on it during his spare time. (But who would love to see the library grow, mature, and be adopted. Contributions are welcome! :-))

A rough sketch of what might be planned for future releases — no guarantees given:

  • Proper allocator support
  • Fast image rescaling algorithms
  • Lazy view evaluation
  • Planar image data representation
  • Improved generic image operation algorithms
  • SIMD vectorization of operations (using helper library, e.g. Vc)