opencv
hip
Our great sponsors
| opencv | hip | |
|---|---|---|
| 1 | - | |
| 152 | 113 | |
| 0.0% | - | |
| 0.0 | 0.0 | |
| 7 months ago | 4 months ago | |
| Haskell | Haskell | |
| BSD 3-clause "New" or "Revised" 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.
opencv
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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.
hip
We haven't tracked posts mentioning hip yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
caer - High-performance Vision library in Python. Scale your research, not boilerplate.
reflex-gloss
hnn - haskell neural network library
friday - Fast image IO and transformations.
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.
typed-spreadsheet - Typed and composable spreadsheets
csp - Constraint satisfaction problem (CSP) solvers for Haskell
xcffib - A drop-in replacement for xpyb based on cffi
tensor-safe - A Haskell framework to define valid deep learning models and export them to other frameworks like TensorFlow JS or Keras.
graphviz - Haskell bindings to the Graphviz toolkit
heukarya - genetic programming in haskell
yampa-canvas - Blank Canvas backend for Yampa