opencv
| inline-c | opencv | |
|---|---|---|
| 4 | 1 | |
| 282 | 152 | |
| 0.0% | 0.0% | |
| 6.8 | 0.0 | |
| 4 months ago | 7 months ago | |
| Haskell | Haskell | |
| MIT License | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
inline-c
-
Help needed for FFI (presumable segmentation fault)
Check out https://github.com/fpco/inline-c
-
Will I suffer attempting to use Haskell in a company that mainly uses c++
Learn inline-c and inline-c-cpp really well. You will feel enabled if you can call the power of C++ from Haskell. You can find some examples in the opencv package.
-
Passing a Haskell object over to a C++ program
As mentioned by /u/0xab inline-c can also do C++ and is the solution for low-level interop with C++. Its C++ support was made for the opencv binding, and in contrast to normal FFI, it allows you to use templated code and so on, splicing Haskell variables in via TH quasiquoters/antiquoters.
opencv
-
Will I suffer attempting to use Haskell in a company that mainly uses c++
Learn inline-c and inline-c-cpp really well. You will feel enabled if you can call the power of C++ from Haskell. You can find some examples in the opencv package.
What are some alternatives?
hpp - hpp - A Haskell Preprocessor
caer - High-performance Vision library in Python. Scale your research, not boilerplate.
bliplib - A bytecode compiler for Python 3
hnn - haskell neural network library
clone-all - clone all the github repositories of a particular user.
moo - Genetic algorithm library for Haskell. Binary and continuous (real-coded) GAs. Binary GAs: binary and Gray encoding; point mutation; one-point, two-point, and uniform crossover. Continuous GAs: Gaussian mutation; BLX-α, UNDX, and SBX crossover. Selection operators: roulette, tournament, and stochastic universal sampling (SUS); with optional niching, ranking, and scaling. Replacement strategies: generational with elitism and steady state. Constrained optimization: random constrained initialization, death penalty, constrained selection without a penalty function. Multi-objective optimization: NSGA-II and constrained NSGA-II.
castle - A tool to manage shared cabal-install sandboxes.
hip - Haskell Image Processing Library
bumper - Haskell tool to automatically bump package versions transitively.
csp - Constraint satisfaction problem (CSP) solvers for Haskell
inline-java - Haskell/Java interop via inline Java code in Haskell modules.
tensor-safe - A Haskell framework to define valid deep learning models and export them to other frameworks like TensorFlow JS or Keras.