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// Custom Allocator for OpenCV's cv::Mat
// this code samples writen by facebook.com/matsuda.kazuki and published under public domain.
// You can copy and use this code in any situation under any license.


#ifndef __CVUT_ALLOCATOR__
#define __CVUT_ALLOCATOR__ 1

#include <opencv2/core/core.hpp>

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/**
 * Fast non-maximum suppression in C, port from  
 * http://quantombone.blogspot.com/2011/08/blazing-fast-nmsm-from-exemplar-svm.html
 *
 * @blackball (bugway@gmail.com)
 */

#include <stdio.h>
#include <stdlib.h>
#include <limits.h>

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// convert an OpenCV multi-channel matrix to Armadillo cube. A copy is made
template <typename T, int NC>
Cube<T> to_arma(const cv::Mat_<cv::Vec<T, NC>> &src)
{
  vector<cv::Mat_<T>> channels;
  Cube<T> dst(src.cols, src.rows, NC);
  for (int c = 0; c < NC; ++c)
    channels.push_back({src.rows, src.cols, dst.slice(c).memptr()});
  cv::split(src, channels);	
  return dst;

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// Just before switching jobs:
// Add one of these.
// Preferably into the same commit where you do a large merge.
//
// This started as a tweet with a joke of "C++ pro-tip: #define private public",
// and then it quickly escalated into more and more evil suggestions.
// I've tried to capture interesting suggestions here.
//
// Contributors: @r2d2rigo, @joeldevahl, @msinilo, @_Humus_,
// @YuriyODonnell, @rygorous, @cmuratori, @mike_acton, @grumpygiant,

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// Accept any number of args >= N, but expand to just the Nth one.
// Here, N == 6.
#define _GET_NTH_ARG(_1, _2, _3, _4, _5, N, ...) N

// Define some macros to help us create overrides based on the
// arity of a for-each-style macro.
#define _fe_0(_call, ...)
#define _fe_1(_call, x) _call(x)
#define _fe_2(_call, x, ...) _call(x) _fe_1(_call, __VA_ARGS__)
#define _fe_3(_call, x, ...) _call(x) _fe_2(_call, __VA_ARGS__)

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#!/usr/bin/env python
from glob import glob                                                           
import cv2 
pngs = glob('./*.png')

for j in pngs:
    img = cv2.imread(j)
    cv2.imwrite(j[:-3] + 'jpg', img)

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#!/usr/bin/env python
from glob import glob                                                           
import cv2 

jpgs = glob('./*.jpg')
shapes = [cv2.imread(f).shape for f in jpgs]
a = [list(i) for i in shapes]
width = [row[1] for row in a]
height = [row[0] for row in a]
print 'width min:', min(width), ', max:', max(width), '; height min:', min(height), ', max:', max(height)

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cmake -DWITH_CUDA=ON -DWITH_CUFFT=ON -DWITH_CUBLAS=ON -DCMAKE_BUILD_TYPE=Release -DOPENCV_EXTRA_MODULES_PATH=../../opencv_contrib/modules -DBUILD_TESTS=OFF -D BUILD_PERF_TESTS=OFF -D BUILD_DOCS=OFF -DCUDA_ARCH_BIN=3.0 -DCUDA_ARCH_PTX=3.0 -DPYTHON2_LIBRARY=$(python-config --prefix)/lib/libpython2.7.dylib -DPYTHON2_INCLUDE_DIR=$(python-config --prefix)/include/python2.7 ..

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# create new build dir
rm -rf build
cd build
cmake .. # some options
cmake --build . --config release --target install # build install
cmake --build . --config releasee --target clean # cleanup

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/**
 * @brief     Image enchancement and Hough transform example
 * @author    Eugene Khvedchenya <ekhvedchenya@gmail.com>
 * @copyright computer-vision-talks.com/articles/how-to-detect-circles-in-noisy-image/
 */



#include <opencv2/opencv.hpp>