CV alternatives and similar packages
Based on the "AI" category.
Alternatively, view CV alternatives based on common mentions on social networks and blogs.
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tensor-safe
A Haskell framework to define valid deep learning models and export them to other frameworks like TensorFlow JS or Keras. -
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. -
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HaVSA
HaVSA (Have-Saa) is a Haskell implementation of the Version Space Algebra Machine Learning technique described by Tessa Lau. -
Etage
A general data-flow framework featuring nondeterminism, laziness and neurological pseudo-terminology.
InfluxDB - Power Real-Time Data Analytics at Scale
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README
About
This is a machine vision package that is implemented on top of the OpenCV C library library.
How To Install
The main installation instructions are detailed in the [Project Wiki]. In short, install
GHC >= 7.4.1, cabal install, c2hs and c version of opencv and your good to go.
According to the OpenCV version you are using, you may need to run the installation
process with one of these two flags -fopencv23 or -fopencv24, like so:
cabal install -fopencv24
There is also an [example installation transcript with all the gory details] in the wiki.
How To Use
The Documentation is available at http://aleator.github.com/CV/
Screenshots? Examples?
There are some screenshots at http://aleator.github.com/CV/ and the examples directory of
this project contains a plenty of small sample programs.
Changelog
- 0.3.0.2 - Workaround for compiling with OS X 10.6 & fixed errors about M_PI .