這幾天在看opencl編程指南。照著書中的樣例實現了sobel算法：

1.結合opencv讀取圖像，保存到緩沖區中。

2.編寫和編譯內核。並保存顯示處理後的結果。

內核：

const sampler_t sampler = CLK_ADDRESS_CLAMP_TO_EDGE | CLK_FILTER_NEAREST;
kernel void sobel_rgb(read_only image2d_t src,write_only image2d_t dst)
{
	int x = (int)get_global_id(0);
	int y = (int)get_global_id(1);
	if (x >= get_image_width(src) || y >= get_image_height(src))
		return;
	float4 p00 = read_imagef(src, sampler, (int2)(x - 1, y - 1));
	float4 p10 = read_imagef(src, sampler, (int2)(x, y - 1));
	float4 p20 = read_imagef(src, sampler, (int2)(x + 1, y - 1));
	float4 p01 = read_imagef(src, sampler, (int2)(x - 1, y));
	float4 p21 = read_imagef(src, sampler, (int2)(x + 1, y));
	float4 p02 = read_imagef(src, sampler, (int2)(x - 1, y + 1));
	float4 p12 = read_imagef(src, sampler, (int2)(x, y + 1));
	float4 p22 = read_imagef(src, sampler, (int2)(x + 1, y + 1));
	float3 gx = -p00.xyz + p20.xyz + 2.0*(p21.xyz - p01.xyz) - p02.xyz + p22.xyz;
	float3 gy = -p00.xyz + p02.xyz + 2.0*(p21.xyz - p10.xyz) - p20.xyz + p22.xyz;
	float3 g = native_sqrt(gx*gx + gy*gy);
	write_imagef(dst,(int2)(x,y),(float4)(g.x,g.y,g.z,1.0f));
}
// TODO: Add OpenCL kernel code here.

//
// Book:      OpenCL(R) Programming Guide
// Authors:   Aaftab Munshi, Benedict Gaster, Timothy Mattson, James Fung, Dan Ginsburg
// ISBN-10:   0-321-74964-2
// ISBN-13:   978-0-321-74964-2
// Publisher: Addison-Wesley Professional
// URLs:      http://safari.informit.com/9780132488006/
//            http://www.openclprogrammingguide.com
//

// ImageFilter2D.cpp
//
//    This example demonstrates performing gaussian filtering on a 2D image using
//    OpenCL
//
//    Requires FreeImage library for image I/O:
//      http://freeimage.sourceforge.net/

#include <iostream>
#include <fstream>
#include <sstream>
#include <string.h>
#include <opencv.hpp>

#ifdef __APPLE__
#include <OpenCL/cl.h>
#else
#include <CL/cl.h>
#endif

#include "FreeImage.h"

///
//  Create an OpenCL context on the first available platform using
//  either a GPU or CPU depending on what is available.
//
cl_context CreateContext()
{
	cl_int errNum;
	cl_uint numPlatforms;
	cl_platform_id firstPlatformId;
	cl_context context = NULL;

	// First, select an OpenCL platform to run on.  For this example, we
	// simply choose the first available platform.  Normally, you would
	// query for all available platforms and select the most appropriate one.
	errNum = clGetPlatformIDs(1, &firstPlatformId, &numPlatforms);
	if (errNum != CL_SUCCESS || numPlatforms <= 0)
	{
		std::cerr << "Failed to find any OpenCL platforms." << std::endl;
		return NULL;
	}

	// Next, create an OpenCL context on the platform.  Attempt to
	// create a GPU-based context, and if that fails, try to create
	// a CPU-based context.
	cl_context_properties contextProperties[] =
	{
		CL_CONTEXT_PLATFORM,
		(cl_context_properties)firstPlatformId,
		0
	};
	context = clCreateContextFromType(contextProperties, CL_DEVICE_TYPE_GPU,
		NULL, NULL, &errNum);
	if (errNum != CL_SUCCESS)
	{
		std::cout << "Could not create GPU context, trying CPU..." << std::endl;
		context = clCreateContextFromType(contextProperties, CL_DEVICE_TYPE_CPU,
			NULL, NULL, &errNum);
		if (errNum != CL_SUCCESS)
		{
			std::cerr << "Failed to create an OpenCL GPU or CPU context." << std::endl;
			return NULL;
		}
	}

	return context;
}

///
//  Create a command queue on the first device available on the
//  context
//
cl_command_queue CreateCommandQueue(cl_context context, cl_device_id *device)
{
	cl_int errNum;
	cl_device_id *devices;
	cl_command_queue commandQueue = NULL;
	size_t deviceBufferSize = -1;

	// First get the size of the devices buffer
	errNum = clGetContextInfo(context, CL_CONTEXT_DEVICES, 0, NULL, &deviceBufferSize);
	if (errNum != CL_SUCCESS)
	{
		std::cerr << "Failed call to clGetContextInfo(...,GL_CONTEXT_DEVICES,...)";
		return NULL;
	}

	if (deviceBufferSize <= 0)
	{
		std::cerr << "No devices available.";
		return NULL;
	}

	// Allocate memory for the devices buffer
	devices = new cl_device_id[deviceBufferSize / sizeof(cl_device_id)];
	errNum = clGetContextInfo(context, CL_CONTEXT_DEVICES, deviceBufferSize, devices, NULL);
	if (errNum != CL_SUCCESS)
	{
		std::cerr << "Failed to get device IDs";
		return NULL;
	}

	// In this example, we just choose the first available device.  In a
	// real program, you would likely use all available devices or choose
	// the highest performance device based on OpenCL device queries
	commandQueue = clCreateCommandQueue(context, devices[0], 0, NULL);
	if (commandQueue == NULL)
	{
		std::cerr << "Failed to create commandQueue for device 0";
		return NULL;
	}

	*device = devices[0];
	delete[] devices;
	return commandQueue;
}

///
//  Create an OpenCL program from the kernel source file
//
cl_program CreateProgram(cl_context context, cl_device_id device, const char* fileName)
{
	cl_int errNum;
	cl_program program;

	std::ifstream kernelFile(fileName, std::ios::in);
	if (!kernelFile.is_open())
	{
		std::cerr << "Failed to open file for reading: " << fileName << std::endl;
		return NULL;
	}

	std::ostringstream oss;
	oss << kernelFile.rdbuf();

	std::string srcStdStr = oss.str();
	const char *srcStr = srcStdStr.c_str();
	program = clCreateProgramWithSource(context, 1,
		(const char**)&srcStr,
		NULL, NULL);
	if (program == NULL)
	{
		std::cerr << "Failed to create CL program from source." << std::endl;
		return NULL;
	}

	errNum = clBuildProgram(program, 0, NULL, NULL, NULL, NULL);
	if (errNum != CL_SUCCESS)
	{
		// Determine the reason for the error
		char buildLog[16384];
		clGetProgramBuildInfo(program, device, CL_PROGRAM_BUILD_LOG,
			sizeof(buildLog), buildLog, NULL);

		std::cerr << "Error in kernel: " << std::endl;
		std::cerr << buildLog;
		clReleaseProgram(program);
		return NULL;
	}

	return program;
}


///
//  Cleanup any created OpenCL resources
//
void Cleanup(cl_context context, cl_command_queue commandQueue,
	cl_program program, cl_kernel kernel, cl_mem imageObjects[2],
	cl_sampler sampler)
{
	for (int i = 0; i < 2; i++)
	{
		if (imageObjects[i] != 0)
			clReleaseMemObject(imageObjects[i]);
	}
	if (commandQueue != 0)
		clReleaseCommandQueue(commandQueue);

	if (kernel != 0)
		clReleaseKernel(kernel);

	if (program != 0)
		clReleaseProgram(program);

	if (sampler != 0)
		clReleaseSampler(sampler);

	if (context != 0)
		clReleaseContext(context);

}

///
//  Load an image using the FreeImage library and create an OpenCL
//  image out of it
//
cl_mem LoadImage(cl_context context, char *fileName, int &width, int &height)
{
	//FREE_IMAGE_FORMAT format = FreeImage_GetFileType(fileName, 0);
	//FIBITMAP* image = FreeImage_Load(format, fileName);

	//// Convert to 32-bit image
	//FIBITMAP* temp = image;
	//image = FreeImage_ConvertTo32Bits(image);
	//FreeImage_Unload(temp);

	//width = FreeImage_GetWidth(image);
	//height = FreeImage_GetHeight(image);
	/*char *buffer = new char[width * height * 4];
	memcpy(buffer, FreeImage_GetBits(image), width * height * 4);

	FreeImage_Unload(image);*/
	cv::Mat image1 = cv::imread(fileName);
	width = image1.cols;
	height = image1.rows;
	char *buffer = new char[width * height * 4];
	int w = 0;
	for (int v = height - 1; v >= 0; v--)
	{
		for (int u = 0; u <width; u++)
		{
			buffer[w++] = image1.at<cv::Vec3b>(v, u)[0];
			buffer[w++] = image1.at<cv::Vec3b>(v, u)[1];
			buffer[w++] = image1.at<cv::Vec3b>(v, u)[2];
			w++;
		}
	}
	

	// Create OpenCL image
	cl_image_format clImageFormat;
	clImageFormat.image_channel_order = CL_RGBA;
	clImageFormat.image_channel_data_type = CL_UNORM_INT8;

	cl_int errNum;
	cl_mem clImage;
	clImage = clCreateImage2D(context,
		CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR,
		&clImageFormat,
		width,
		height,
		0,
		buffer,
		&errNum);

	if (errNum != CL_SUCCESS)
	{
		std::cerr << "Error creating CL image object" << std::endl;
		return 0;
	}

	return clImage;
}

///
//  Save an image using the FreeImage library
//
bool SaveImage(char *fileName, char *buffer, int width, int height)
{
	FREE_IMAGE_FORMAT format = FreeImage_GetFIFFromFilename(fileName);
	FIBITMAP *image = FreeImage_ConvertFromRawBits((BYTE*)buffer, width,
		height, width * 4, 32,
		0xFF000000, 0x00FF0000, 0x0000FF00);
	return FreeImage_Save(format, image, fileName);
}

///
//  Round up to the nearest multiple of the group size
//
size_t RoundUp(int groupSize, int globalSize)
{
	int r = globalSize % groupSize;
	if (r == 0)
	{
		return globalSize;
	}
	else
	{
		return globalSize + groupSize - r;
	}
}

///
//	main() for HelloBinaryWorld example
//
int main(int argc, char** argv)
{
	cl_context context = 0;
	cl_command_queue commandQueue = 0;
	cl_program program = 0;
	cl_device_id device = 0;
	cl_kernel kernel = 0;
	cl_mem imageObjects[2] = { 0, 0 };
	cl_sampler sampler = 0;
	cl_int errNum;


	/*if (argc != 3)
	{
		std::cerr << "USAGE: " << argv[0] << " <inputImageFile> <outputImageFiles>" << std::endl;
		return 1;
	}*/

	// Create an OpenCL context on first available platform
	context = CreateContext();
	if (context == NULL)
	{
		std::cerr << "Failed to create OpenCL context." << std::endl;
		return 1;
	}

	// Create a command-queue on the first device available
	// on the created context
	commandQueue = CreateCommandQueue(context, &device);
	if (commandQueue == NULL)
	{
		Cleanup(context, commandQueue, program, kernel, imageObjects, sampler);
		return 1;
	}

	// Make sure the device supports images, otherwise exit
	cl_bool imageSupport = CL_FALSE;
	clGetDeviceInfo(device, CL_DEVICE_IMAGE_SUPPORT, sizeof(cl_bool),
		&imageSupport, NULL);
	if (imageSupport != CL_TRUE)
	{
		std::cerr << "OpenCL device does not support images." << std::endl;
		Cleanup(context, commandQueue, program, kernel, imageObjects, sampler);
		return 1;
	}

	// Load input image from file and load it into
	// an OpenCL image object
	int width, height;
	char *src0 = "C:/Users/jiang/Desktop/image/tu1.jpg";
	imageObjects[0] = LoadImage(context, src0, width, height);
	if (imageObjects[0] == 0)
	{
		std::cerr << "Error loading: " << std::string(src0) << std::endl;
		Cleanup(context, commandQueue, program, kernel, imageObjects, sampler);
		return 1;
	}

	// Create ouput image object
	cl_image_format clImageFormat;
	clImageFormat.image_channel_order = CL_RGBA;
	clImageFormat.image_channel_data_type = CL_UNORM_INT8;
	imageObjects[1] = clCreateImage2D(context,
		CL_MEM_WRITE_ONLY,
		&clImageFormat,
		width,
		height,
		0,
		NULL,
		&errNum);

	if (errNum != CL_SUCCESS)
	{
		std::cerr << "Error creating CL output image object." << std::endl;
		Cleanup(context, commandQueue, program, kernel, imageObjects, sampler);
		return 1;
	}


	// Create sampler for sampling image object
	sampler = clCreateSampler(context,
		CL_FALSE, // Non-normalized coordinates
		CL_ADDRESS_CLAMP_TO_EDGE,
		CL_FILTER_NEAREST,
		&errNum);

	if (errNum != CL_SUCCESS)
	{
		std::cerr << "Error creating CL sampler object." << std::endl;
		Cleanup(context, commandQueue, program, kernel, imageObjects, sampler);
		return 1;
	}

	// Create OpenCL program
	//program = CreateProgram(context, device, "ImageFilter2D.cl");
	program = CreateProgram(context, device, "Sobel.cl");
	if (program == NULL)
	{
		Cleanup(context, commandQueue, program, kernel, imageObjects, sampler);
		return 1;
	}
	// Create OpenCL kernel
	kernel = clCreateKernel(program, "sobel_rgb", NULL);
	if (kernel == NULL)
	{
		std::cerr << "Failed to create kernel" << std::endl;
		Cleanup(context, commandQueue, program, kernel, imageObjects, sampler);
		return 1;
	}

	// Set the kernel arguments
	errNum = clSetKernelArg(kernel, 0, sizeof(cl_mem), &imageObjects[0]);
	errNum |= clSetKernelArg(kernel, 1, sizeof(cl_mem), &imageObjects[1]);
	/*errNum |= clSetKernelArg(kernel, 2, sizeof(cl_sampler), &sampler);
	errNum |= clSetKernelArg(kernel, 3, sizeof(cl_int), &width);
	errNum |= clSetKernelArg(kernel, 4, sizeof(cl_int), &height);*/
	if (errNum != CL_SUCCESS)
	{
		std::cerr << "Error setting kernel arguments." << std::endl;
		Cleanup(context, commandQueue, program, kernel, imageObjects, sampler);
		return 1;
	}

	size_t localWorkSize[2] = { 16, 16 };
	size_t globalWorkSize[2] = { RoundUp(localWorkSize[0], width),
		RoundUp(localWorkSize[1], height) };

	// Queue the kernel up for execution
	errNum = clEnqueueNDRangeKernel(commandQueue, kernel, 2, NULL,
		globalWorkSize, localWorkSize,
		0, NULL, NULL);
	if (errNum != CL_SUCCESS)
	{
		std::cerr << "Error queuing kernel for execution." << std::endl;
		Cleanup(context, commandQueue, program, kernel, imageObjects, sampler);
		return 1;
	}

	// Read the output buffer back to the Host
	char *buffer = new char[width * height * 4];
	size_t origin[3] = { 0, 0, 0 };
	size_t region[3] = { width, height, 1 };
	errNum = clEnqueueReadImage(commandQueue, imageObjects[1], CL_TRUE,
		origin, region, 0, 0, buffer,
		0, NULL, NULL);
	if (errNum != CL_SUCCESS)
	{
		std::cerr << "Error reading result buffer." << std::endl;
		Cleanup(context, commandQueue, program, kernel, imageObjects, sampler);
		return 1;
	}

	std::cout << std::endl;
	std::cout << "Executed program succesfully." << std::endl;

	//memset(buffer, 0xff, width * height * 4);
	// Save the image out to disk
	char *saveImage = "C:/Users/jiang/Desktop/image/tu2.jpg";
	//std::cout << buffer << std::endl;
	cv::Mat imageColor = cv::imread(src0);
	cv::Mat imageColor2;
	imageColor2.create(imageColor.rows, imageColor.cols, imageColor.type());
	int w = 0;
	for (int v = imageColor2.rows-1; v >=0; v--)
	{
		for (int u =0 ; u <imageColor2.cols; u++)
		{
			imageColor2.at<cv::Vec3b>(v, u)[0] = buffer[w++];
			imageColor2.at<cv::Vec3b>(v, u)[1] = buffer[w++];
			imageColor2.at<cv::Vec3b>(v, u)[2] = buffer[w++];
			w++;
		}
	}
	cv::imshow("image", imageColor2);
	cv::imwrite(saveImage, imageColor2);
	cv::waitKey(0);
	/*if (!SaveImage(saveImage, buffer, width, height))
	{
		std::cerr << "Error writing output image: " << saveImage<< std::endl;
		Cleanup(context, commandQueue, program, kernel, imageObjects, sampler);
		delete[] buffer;
		return 1;
	}*/

	delete[] buffer;
	Cleanup(context, commandQueue, program, kernel, imageObjects, sampler);
	return 0;
}

opencl+opencv實現sobel算法