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//---------------------------------------------------------------------------//
// Copyright (c) 2013-2014 Mageswaran.D <mageswaran1989@gmail.com>
//
// Distributed under the Boost Software License, Version 1.0
// See accompanying file LICENSE_1_0.txt or copy at
// http://www.boost.org/LICENSE_1_0.txt
//
// See http://boostorg.github.com/compute for more information.
//---------------------------------------------------------------------------//
//Code sample for calculating histogram using OpenCL and
//displaying image histogram in OpenCV.
#include <iostream>
#include <string>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <boost/compute/source.hpp>
#include <boost/compute/system.hpp>
#include <boost/compute/container/vector.hpp>
#include <boost/compute/interop/opencv/core.hpp>
#include <boost/compute/interop/opencv/highgui.hpp>
#include <boost/program_options.hpp>
namespace compute = boost::compute;
namespace po = boost::program_options;
// number of bins
int histSize = 256;
// Set the ranges ( for B,G,R) )
// TryOut: consider the range in kernel calculation
float range[] = { 0, 256 } ;
const float* histRange = { range };
// Create naive histogram program
// Needs "cl_khr_local_int32_base_atomics" extension
const char source[] = BOOST_COMPUTE_STRINGIZE_SOURCE (
__kernel void histogram(read_only image2d_t src_image,
__global int* b_hist,
__global int* g_hist,
__global int* r_hist)
{
sampler_t sampler =( CLK_NORMALIZED_COORDS_FALSE |
CLK_FILTER_NEAREST |
CLK_ADDRESS_CLAMP_TO_EDGE);
int image_width = get_image_width(src_image);
int image_height = get_image_height(src_image);
int2 coords = (int2)(get_global_id(0), get_global_id(1));
float4 pixel = read_imagef(src_image,sampler, coords);
//boundary condition
if ((coords.x < image_width) && (coords.y < image_height))
{
uchar indx_x, indx_y, indx_z;
indx_x = convert_uchar_sat(pixel.x * 255.0f);
indx_y = convert_uchar_sat(pixel.y * 255.0f);
indx_z = convert_uchar_sat(pixel.z * 255.0f);
atomic_inc(&b_hist[(uint)indx_z]);
atomic_inc(&g_hist[(uint)indx_y]);
atomic_inc(&r_hist[(uint)indx_x]);
}
}
);
inline void showHistogramWindow(cv::Mat &b_hist, cv::Mat &g_hist, cv::Mat &r_hist,
std::string window_name)
{
// Draw the histograms for B, G and R
int hist_w = 1024;
int hist_h = 768;
int bin_w = cvRound((double)hist_w/histSize);
cv::Mat histImage(hist_h, hist_w, CV_8UC3, cv::Scalar(0,0,0));
// Normalize the result to [ 0, histImage.rows ]
cv::normalize(b_hist, b_hist, 0, histImage.rows, cv::NORM_MINMAX, -1, cv::Mat());
cv::normalize(g_hist, g_hist, 0, histImage.rows, cv::NORM_MINMAX, -1, cv::Mat());
cv::normalize(r_hist, r_hist, 0, histImage.rows, cv::NORM_MINMAX, -1, cv::Mat());
// Draw for each channel
for (int i = 1; i < histSize; i++ )
{
cv::line(histImage,
cv::Point(bin_w*(i-1), hist_h - cvRound(b_hist.at<float>(i-1))),
cv::Point(bin_w*(i), hist_h - cvRound(b_hist.at<float>(i))),
cv::Scalar(255, 0, 0),
2,
8,
0);
cv::line(histImage,
cv::Point(bin_w*(i-1), hist_h - cvRound(g_hist.at<float>(i-1))),
cv::Point(bin_w*(i), hist_h - cvRound(g_hist.at<float>(i))),
cv::Scalar(0, 255, 0),
2,
8,
0);
cv::line(histImage,
cv::Point( bin_w*(i-1), hist_h - cvRound(r_hist.at<float>(i-1))),
cv::Point( bin_w*(i), hist_h - cvRound(r_hist.at<float>(i)) ),
cv::Scalar( 0, 0, 255),
2,
8,
0);
}
// Display
cv::namedWindow(window_name, CV_WINDOW_AUTOSIZE );
cv::imshow(window_name, histImage );
}
//Get the device context
//Create GPU array/vector
//Copy the image & set up the kernel
//Execute the kernel
//Copy GPU data back to CPU cv::Mat data pointer
//OpenCV conversion for convienient display
void calculateHistogramUsingCL(cv::Mat src, compute::command_queue &queue)
{
compute::context context = queue.get_context();
// Convert image to BGRA (OpenCL requires 16-byte aligned data)
cv::cvtColor(src, src, CV_BGR2BGRA);
//3 channels & 256 bins : alpha channel is ignored
compute::vector<int> gpu_b_hist(histSize, context);
compute::vector<int> gpu_g_hist(histSize, context);
compute::vector<int> gpu_r_hist(histSize, context);
// Transfer image to gpu
compute::image2d gpu_src =
compute::opencv_create_image2d_with_mat(
src, compute::image2d::read_only,
queue
);
compute::program histogram_program =
compute::program::create_with_source(source, context);
histogram_program.build();
// create histogram kernel and set arguments
compute::kernel histogram_kernel(histogram_program, "histogram");
histogram_kernel.set_arg(0, gpu_src);
histogram_kernel.set_arg(1, gpu_b_hist.get_buffer());
histogram_kernel.set_arg(2, gpu_g_hist.get_buffer());
histogram_kernel.set_arg(3, gpu_r_hist.get_buffer());
// run histogram kernel
// each kernel thread updating red, green & blue bins
size_t origin[2] = { 0, 0 };
size_t region[2] = { gpu_src.width(),
gpu_src.height() };
queue.enqueue_nd_range_kernel(histogram_kernel, 2, origin, region, 0);
//Make sure kernel get executed and data copied back
queue.finish();
//create Mat and copy GPU bins to CPU memory
cv::Mat b_hist(256, 1, CV_32SC1);
compute::copy(gpu_b_hist.begin(), gpu_b_hist.end(), b_hist.data, queue);
cv::Mat g_hist(256, 1, CV_32SC1);
compute::copy(gpu_g_hist.begin(), gpu_g_hist.end(), g_hist.data, queue);
cv::Mat r_hist(256, 1, CV_32SC1);
compute::copy(gpu_r_hist.begin(), gpu_r_hist.end(), r_hist.data, queue);
b_hist.convertTo(b_hist, CV_32FC1); //converted for displaying
g_hist.convertTo(g_hist, CV_32FC1);
r_hist.convertTo(r_hist, CV_32FC1);
showHistogramWindow(b_hist, g_hist, r_hist, "Histogram");
}
int main( int argc, char** argv )
{
// Get default device and setup context
compute::device gpu = compute::system::default_device();
compute::context context(gpu);
compute::command_queue queue(context, gpu);
cv::Mat src;
// setup the command line arguments
po::options_description desc;
desc.add_options()
("help", "show available options")
("image", po::value<std::string>(), "path to image file");
// Parse the command lines
po::variables_map vm;
po::store(po::parse_command_line(argc, argv, desc), vm);
po::notify(vm);
//check the command line arguments
if(vm.count("help"))
{
std::cout << desc << std::endl;
return 0;
}
//check for image paths
if(vm.count("image"))
{
// Read image with OpenCV
src = cv::imread(vm["image"].as<std::string>(),
CV_LOAD_IMAGE_COLOR);
if(!src.data){
std::cerr << "Failed to load image" << std::endl;
return -1;
}
calculateHistogramUsingCL(src, queue);
cv::imshow("Image", src);
cv::waitKey(0);
}
else
{
std::cout << desc << std::endl;
return 0;
}
return 0;
}
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