OpenCL双边滤波实现美颜功能

2018-06-17 23:17:26来源:未知 阅读 ()

新老客户大回馈,云服务器低至5折

    OpenCL是一个并行异构计算的框架,包括intel,AMD,英伟达等等许多厂家都有对它的支持,不过英伟达只到1.2版本,主要发展自己的CUDA去了。虽然没有用过CUDA,但个人感觉CUDA比OpenCL更好一点,但OpenCL支持面更管,CPU,GPU,DSP,FPGA等多种芯片都能支持OpenCL。OpenCL与D3D中的像素着色器非常相似。

1.双边滤波原理

    双边滤波器的原理参考女神Rachel-Zhang的博客 双边滤波器的原理及实现. 引自Rachel-Zhang的博客,原理如下:

双边滤波(Bilateral filter)是一种可以保边去噪的滤波器。之所以可以达到此去噪效果,是因为滤波器是由两个函数构成。一个函数是由几何空间距离决定滤波器系数。另一个由像素差值决定滤波器系数。可以与其相比较的两个filter:高斯低通滤波器(http://en.wikipedia.org/wiki/Gaussian_filter)和α-截尾均值滤波器(去掉百分率为α的最小值和最大之后剩下像素的均值作为滤波器)。

双边滤波器中,输出像素的值依赖于邻域像素的值的加权组合,

          权重系数w(i,j,k,l)取决于定义域核和值域核的乘积。同时考虑了空间域与值域的差别,而Gaussian Filter和α均值滤波分别只考虑了空间域和值域差别。

本文基于这个公式用OpenCL实现双边滤波来做美颜。

2.核函数

    磨皮算法原理参考自http://www.zealfilter.com/portal.php?mod=view&aid=138,其中的肤色检测算法不好,我给去掉了,本来还要做个锐化处理的,但发现不做锐化效果也蛮好,所以就先没做,学下一步的OpenCL时在做锐化。

const sampler_t sampler = CLK_ADDRESS_CLAMP_TO_EDGE | CLK_FILTER_NEAREST;

kernel void bilateralBlur(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;  

    int ksize = 11;
    float sigma_d = 3.0;
    float sigma_r = 0.1;

    float4 fij = read_imagef(src, sampler, (int2)(x, y));
    float alpha = 0.2;

    float4 fkl;
    float dkl;
    float4 rkl;
    float4 wkl;

    float4 numerator = (float4)(0.0f,0.0f,0.0f,0.0f);
    float4 denominator = (float4)(1.0f, 1.0f, 1.0f, 1.0f);
    for (int K = -ksize / 2; K <= ksize / 2; K++)
    {
        for (int L = -ksize / 2; L <= ksize / 2; L++)
        {
            fkl = read_imagef(src, sampler, (int2)(x + K, y + L));

            dkl = -(K*K + L*L) / (2 * sigma_d*sigma_d);
            rkl.x = -(fij.x - fkl.x)*(fij.x - fkl.x) / (2 * sigma_r*sigma_r);
            rkl.y = -(fij.y - fkl.y)*(fij.y - fkl.y) / (2 * sigma_r*sigma_r);
            rkl.z = -(fij.z - fkl.z)*(fij.z - fkl.z) / (2 * sigma_r*sigma_r);

            wkl.x = exp(dkl + rkl.x);
            wkl.y = exp(dkl + rkl.y);
            wkl.z = exp(dkl + rkl.z);

            numerator.x += fkl.x * wkl.x;
            numerator.y += fkl.y * wkl.y;
            numerator.z += fkl.z * wkl.z;

            denominator.x += wkl.x;
            denominator.y += wkl.y;
            denominator.z += wkl.z;
        }
    }
    
    float4 gij = (float4)(0.0f, 0.0f, 0.0f, 1.0f);
    if (denominator.x > 0 && denominator.y > 0 && denominator.z)
    {
        gij.x = numerator.x / denominator.x;
        gij.y = numerator.y / denominator.y;
        gij.z = numerator.z / denominator.z;

        //双边滤波后再做一个融合
         gij.x = fij.x*alpha + gij.x*(1.0 - alpha);
        gij.y = fij.y*alpha + gij.y*(1.0 - alpha);
        gij.z = fij.z*alpha + gij.z*(1.0 - alpha);
    }

    write_imagef(dst, (int2)(x, y), gij);
}

kernel函数里面基本就是把数学公式写出来,可以说是非常简单的。

3.host端代码

    OpenCL代码分为host端的代码和device端的代码,kernel是跑在并行设备device上的,host一般适合跑串行的逻辑性强的代码,device则比较适合用来做计算,如卷积运算。计算机中,通常把CPU当host,把GPU当device。不过实际上CPU也可以作为device,因为intel也是支持OpenCL的。本文以CPU为host,GPU为device。

#include "stdafx.h"

#include <iostream>  
#include <fstream>  
#include <sstream>  
#include <malloc.h> 
#include <string.h>  
#include <opencv2/opencv.hpp>  

#include <CL/cl.h>  
 
 
 //----------获取OpenCL平台设备信息---------

void DisplayPlatformInfo(
    cl_platform_id id,
    cl_platform_info name,
    std::string str)
{
    cl_int errNum;
    std::size_t paramValueSize;

    errNum = clGetPlatformInfo(
        id,
        name,
        0,
        NULL,
        &paramValueSize);
    if (errNum != CL_SUCCESS)
    {
        std::cerr << "Failed to find OpenCL platform " << str << "." << std::endl;
        return;
    }

    char * info = (char *)alloca(sizeof(char) * paramValueSize);
    errNum = clGetPlatformInfo(
        id,
        name,
        paramValueSize,
        info,
        NULL);
    if (errNum != CL_SUCCESS)
    {
        std::cerr << "Failed to find OpenCL platform " << str << "." << std::endl;
        return;
    }

    std::cout << "\t" << str << ":\t" << info << std::endl;
}

template<typename T>
void appendBitfield(T info, T value, std::string name, std::string & str)
{
    if (info & value)
    {
        if (str.length() > 0)
        {
            str.append(" | ");
        }
        str.append(name);
    }
}

///
// Display information for a particular device.
// As different calls to clGetDeviceInfo may return
// values of different types a template is used. 
// As some values returned are arrays of values, a templated class is
// used so it can be specialized for this case, see below.
//
template <typename T>
class InfoDevice
{
public:
    static void display(
        cl_device_id id,
        cl_device_info name,
        std::string str)
    {
        cl_int errNum;
        std::size_t paramValueSize;

        errNum = clGetDeviceInfo(
            id,
            name,
            0,
            NULL,
            &paramValueSize);
        if (errNum != CL_SUCCESS)
        {
            std::cerr << "Failed to find OpenCL device info " << str << "." << std::endl;
            return;
        }

        T * info = (T *)alloca(sizeof(T) * paramValueSize);
        errNum = clGetDeviceInfo(
            id,
            name,
            paramValueSize,
            info,
            NULL);
        if (errNum != CL_SUCCESS)
        {
            std::cerr << "Failed to find OpenCL device info " << str << "." << std::endl;
            return;
        }

        // Handle a few special cases
        switch (name)
        {
        case CL_DEVICE_TYPE:
        {
            std::string deviceType;

            appendBitfield<cl_device_type>(
                *(reinterpret_cast<cl_device_type*>(info)),
                CL_DEVICE_TYPE_CPU,
                "CL_DEVICE_TYPE_CPU",
                deviceType);

            appendBitfield<cl_device_type>(
                *(reinterpret_cast<cl_device_type*>(info)),
                CL_DEVICE_TYPE_GPU,
                "CL_DEVICE_TYPE_GPU",
                deviceType);

            appendBitfield<cl_device_type>(
                *(reinterpret_cast<cl_device_type*>(info)),
                CL_DEVICE_TYPE_ACCELERATOR,
                "CL_DEVICE_TYPE_ACCELERATOR",
                deviceType);

            appendBitfield<cl_device_type>(
                *(reinterpret_cast<cl_device_type*>(info)),
                CL_DEVICE_TYPE_DEFAULT,
                "CL_DEVICE_TYPE_DEFAULT",
                deviceType);

            std::cout << "\t\t" << str << ":\t" << deviceType << std::endl;
        }
            break;
        case CL_DEVICE_SINGLE_FP_CONFIG:
        {
            std::string fpType;

            appendBitfield<cl_device_fp_config>(
                *(reinterpret_cast<cl_device_fp_config*>(info)),
                CL_FP_DENORM,
                "CL_FP_DENORM",
                fpType);

            appendBitfield<cl_device_fp_config>(
                *(reinterpret_cast<cl_device_fp_config*>(info)),
                CL_FP_INF_NAN,
                "CL_FP_INF_NAN",
                fpType);

            appendBitfield<cl_device_fp_config>(
                *(reinterpret_cast<cl_device_fp_config*>(info)),
                CL_FP_ROUND_TO_NEAREST,
                "CL_FP_ROUND_TO_NEAREST",
                fpType);

            appendBitfield<cl_device_fp_config>(
                *(reinterpret_cast<cl_device_fp_config*>(info)),
                CL_FP_ROUND_TO_ZERO,
                "CL_FP_ROUND_TO_ZERO",
                fpType);

            appendBitfield<cl_device_fp_config>(
                *(reinterpret_cast<cl_device_fp_config*>(info)),
                CL_FP_ROUND_TO_INF,
                "CL_FP_ROUND_TO_INF",
                fpType);

            appendBitfield<cl_device_fp_config>(
                *(reinterpret_cast<cl_device_fp_config*>(info)),
                CL_FP_FMA,
                "CL_FP_FMA",
                fpType);

#ifdef CL_FP_SOFT_FLOAT
            appendBitfield<cl_device_fp_config>(
                *(reinterpret_cast<cl_device_fp_config*>(info)),
                CL_FP_SOFT_FLOAT,
                "CL_FP_SOFT_FLOAT",
                fpType);
#endif

            std::cout << "\t\t" << str << ":\t" << fpType << std::endl;
        }
        case CL_DEVICE_GLOBAL_MEM_CACHE_TYPE:
        {
            std::string memType;

            appendBitfield<cl_device_mem_cache_type>(
                *(reinterpret_cast<cl_device_mem_cache_type*>(info)),
                CL_NONE,
                "CL_NONE",
                memType);
            appendBitfield<cl_device_mem_cache_type>(
                *(reinterpret_cast<cl_device_mem_cache_type*>(info)),
                CL_READ_ONLY_CACHE,
                "CL_READ_ONLY_CACHE",
                memType);

            appendBitfield<cl_device_mem_cache_type>(
                *(reinterpret_cast<cl_device_mem_cache_type*>(info)),
                CL_READ_WRITE_CACHE,
                "CL_READ_WRITE_CACHE",
                memType);

            std::cout << "\t\t" << str << ":\t" << memType << std::endl;
        }
            break;
        case CL_DEVICE_LOCAL_MEM_TYPE:
        {
            std::string memType;

            appendBitfield<cl_device_local_mem_type>(
                *(reinterpret_cast<cl_device_local_mem_type*>(info)),
                CL_GLOBAL,
                "CL_LOCAL",
                memType);

            appendBitfield<cl_device_local_mem_type>(
                *(reinterpret_cast<cl_device_local_mem_type*>(info)),
                CL_GLOBAL,
                "CL_GLOBAL",
                memType);

            std::cout << "\t\t" << str << ":\t" << memType << std::endl;
        }
            break;
        case CL_DEVICE_EXECUTION_CAPABILITIES:
        {
            std::string memType;

            appendBitfield<cl_device_exec_capabilities>(
                *(reinterpret_cast<cl_device_exec_capabilities*>(info)),
                CL_EXEC_KERNEL,
                "CL_EXEC_KERNEL",
                memType);

            appendBitfield<cl_device_exec_capabilities>(
                *(reinterpret_cast<cl_device_exec_capabilities*>(info)),
                CL_EXEC_NATIVE_KERNEL,
                "CL_EXEC_NATIVE_KERNEL",
                memType);

            std::cout << "\t\t" << str << ":\t" << memType << std::endl;
        }
            break;
        case CL_DEVICE_QUEUE_PROPERTIES:
        {
            std::string memType;

            appendBitfield<cl_device_exec_capabilities>(
                *(reinterpret_cast<cl_device_exec_capabilities*>(info)),
                CL_QUEUE_OUT_OF_ORDER_EXEC_MODE_ENABLE,
                "CL_QUEUE_OUT_OF_ORDER_EXEC_MODE_ENABLE",
                memType);

            appendBitfield<cl_device_exec_capabilities>(
                *(reinterpret_cast<cl_device_exec_capabilities*>(info)),
                CL_QUEUE_PROFILING_ENABLE,
                "CL_QUEUE_PROFILING_ENABLE",
                memType);

            std::cout << "\t\t" << str << ":\t" << memType << std::endl;
        }
            break;
        default:
            std::cout << "\t\t" << str << ":\t" << *info << std::endl;
            break;
        }
    }
};

///
// Simple trait class used to wrap base types.
//
template <typename T>
class ArrayType
{
public:
    static bool isChar() { return false; }
};

///
// Specialized for the char (i.e. null terminated string case).
//
template<>
class ArrayType<char>
{
public:
    static bool isChar() { return true; }
};

///
// Specialized instance of class InfoDevice for array types.
//
template <typename T>
class InfoDevice<ArrayType<T> >
{
public:
    static void display(
        cl_device_id id,
        cl_device_info name,
        std::string str)
    {
        cl_int errNum;
        std::size_t paramValueSize;

        errNum = clGetDeviceInfo(
            id,
            name,
            0,
            NULL,
            &paramValueSize);
        if (errNum != CL_SUCCESS)
        {
            std::cerr
                << "Failed to find OpenCL device info "
                << str
                << "."
                << std::endl;
            return;
        }

        T * info = (T *)alloca(sizeof(T) * paramValueSize);
        errNum = clGetDeviceInfo(
            id,
            name,
            paramValueSize,
            info,
            NULL);
        if (errNum != CL_SUCCESS)
        {
            std::cerr
                << "Failed to find OpenCL device info "
                << str
                << "."
                << std::endl;
            return;
        }

        if (ArrayType<T>::isChar())
        {
            std::cout << "\t" << str << ":\t" << info << std::endl;
        }
        else if (name == CL_DEVICE_MAX_WORK_ITEM_SIZES)
        {
            cl_uint maxWorkItemDimensions;

            errNum = clGetDeviceInfo(
                id,
                CL_DEVICE_MAX_WORK_ITEM_DIMENSIONS,
                sizeof(cl_uint),
                &maxWorkItemDimensions,
                NULL);
            if (errNum != CL_SUCCESS)
            {
                std::cerr
                    << "Failed to find OpenCL device info "
                    << "CL_DEVICE_MAX_WORK_ITEM_DIMENSIONS."
                    << std::endl;
                return;
            }

            std::cout << "\t" << str << ":\t";
            for (cl_uint i = 0; i < maxWorkItemDimensions; i++)
            {
                std::cout << info[i] << " ";
            }
            std::cout << std::endl;
        }
    }
};

///
//  Enumerate platforms and display information about them 
//  and their associated devices.
//
void displayInfo(void)
{
    cl_int errNum;
    cl_uint numPlatforms;
    cl_platform_id * platformIds;
    cl_context context = NULL;

    // First, query the total number of platforms
    errNum = clGetPlatformIDs(0, NULL, &numPlatforms);
    if (errNum != CL_SUCCESS || numPlatforms <= 0)
    {
        std::cerr << "Failed to find any OpenCL platform." << std::endl;
        return;
    }

    // Next, allocate memory for the installed plaforms, and qeury 
    // to get the list.
    platformIds = (cl_platform_id *)alloca(sizeof(cl_platform_id) * numPlatforms);
    // First, query the total number of platforms
    errNum = clGetPlatformIDs(numPlatforms, platformIds, NULL);
    if (errNum != CL_SUCCESS)
    {
        std::cerr << "Failed to find any OpenCL platforms." << std::endl;
        return;
    }

    std::cout << "Number of platforms: \t" << numPlatforms << std::endl;
    // Iterate through the list of platforms displaying associated information
    for (cl_uint i = 0; i < numPlatforms; i++) {
        // First we display information associated with the platform
        DisplayPlatformInfo(
            platformIds[i],
            CL_PLATFORM_PROFILE,
            "CL_PLATFORM_PROFILE");
        DisplayPlatformInfo(
            platformIds[i],
            CL_PLATFORM_VERSION,
            "CL_PLATFORM_VERSION");
        DisplayPlatformInfo(
            platformIds[i],
            CL_PLATFORM_VENDOR,
            "CL_PLATFORM_VENDOR");
        DisplayPlatformInfo(
            platformIds[i],
            CL_PLATFORM_EXTENSIONS,
            "CL_PLATFORM_EXTENSIONS");

        // Now query the set of devices associated with the platform
        cl_uint numDevices;
        errNum = clGetDeviceIDs(
            platformIds[i],
            CL_DEVICE_TYPE_ALL,
            0,
            NULL,
            &numDevices);
        if (errNum != CL_SUCCESS)
        {
            std::cerr << "Failed to find OpenCL devices." << std::endl;
            return;
        }

        cl_device_id * devices = (cl_device_id *)alloca(sizeof(cl_device_id) * numDevices);
        errNum = clGetDeviceIDs(
            platformIds[i],
            CL_DEVICE_TYPE_ALL,
            numDevices,
            devices,
            NULL);
        if (errNum != CL_SUCCESS)
        {
            std::cerr << "Failed to find OpenCL devices." << std::endl;
            return;
        }

        std::cout << "\tNumber of devices: \t" << numDevices << std::endl;
        // Iterate through each device, displaying associated information
        for (cl_uint j = 0; j < numDevices; j++)
        {
            InfoDevice<cl_device_type>::display(
                devices[j],
                CL_DEVICE_TYPE,
                "CL_DEVICE_TYPE");

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_VENDOR_ID,
                "CL_DEVICE_VENDOR_ID");

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_MAX_COMPUTE_UNITS,
                "CL_DEVICE_MAX_COMPUTE_UNITS");

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_MAX_WORK_ITEM_DIMENSIONS,
                "CL_DEVICE_MAX_WORK_ITEM_DIMENSIONS");

            InfoDevice<ArrayType<size_t> >::display(
                devices[j],
                CL_DEVICE_MAX_WORK_ITEM_SIZES,
                "CL_DEVICE_MAX_WORK_ITEM_SIZES");

            InfoDevice<std::size_t>::display(
                devices[j],
                CL_DEVICE_MAX_WORK_GROUP_SIZE,
                "CL_DEVICE_MAX_WORK_GROUP_SIZE");

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_CHAR,
                "CL_DEVICE_PREFERRED_VECTOR_WIDTH_CHAR");

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_SHORT,
                "CL_DEVICE_PREFERRED_VECTOR_WIDTH_SHORT");

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_INT,
                "CL_DEVICE_PREFERRED_VECTOR_WIDTH_INT");

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_LONG,
                "CL_DEVICE_PREFERRED_VECTOR_WIDTH_LONG");

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_FLOAT,
                "CL_DEVICE_PREFERRED_VECTOR_WIDTH_FLOAT");

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_DOUBLE,
                "CL_DEVICE_PREFERRED_VECTOR_WIDTH_DOUBLE");

#ifdef CL_DEVICE_PREFERRED_VECTOR_WIDTH_HALF

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_HALF,
                "CL_DEVICE_PREFERRED_VECTOR_WIDTH_HALF");

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_NATIVE_VECTOR_WIDTH_CHAR,
                "CL_DEVICE_NATIVE_VECTOR_WIDTH_CHAR");

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_NATIVE_VECTOR_WIDTH_SHORT,
                "CL_DEVICE_NATIVE_VECTOR_WIDTH_SHORT");

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_NATIVE_VECTOR_WIDTH_INT,
                "CL_DEVICE_NATIVE_VECTOR_WIDTH_INT");

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_NATIVE_VECTOR_WIDTH_LONG,
                "CL_DEVICE_NATIVE_VECTOR_WIDTH_LONG");

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_NATIVE_VECTOR_WIDTH_FLOAT,
                "CL_DEVICE_NATIVE_VECTOR_WIDTH_FLOAT");

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_NATIVE_VECTOR_WIDTH_DOUBLE,
                "CL_DEVICE_NATIVE_VECTOR_WIDTH_DOUBLE");

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_NATIVE_VECTOR_WIDTH_HALF,
                "CL_DEVICE_NATIVE_VECTOR_WIDTH_HALF");
#endif

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_MAX_CLOCK_FREQUENCY,
                "CL_DEVICE_MAX_CLOCK_FREQUENCY");

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_ADDRESS_BITS,
                "CL_DEVICE_ADDRESS_BITS");

            InfoDevice<cl_ulong>::display(
                devices[j],
                CL_DEVICE_MAX_MEM_ALLOC_SIZE,
                "CL_DEVICE_MAX_MEM_ALLOC_SIZE");

            InfoDevice<cl_bool>::display(
                devices[j],
                CL_DEVICE_IMAGE_SUPPORT,
                "CL_DEVICE_IMAGE_SUPPORT");

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_MAX_READ_IMAGE_ARGS,
                "CL_DEVICE_MAX_READ_IMAGE_ARGS");

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_MAX_WRITE_IMAGE_ARGS,
                "CL_DEVICE_MAX_WRITE_IMAGE_ARGS");

            InfoDevice<std::size_t>::display(
                devices[j],
                CL_DEVICE_IMAGE2D_MAX_WIDTH,
                "CL_DEVICE_IMAGE2D_MAX_WIDTH");

            InfoDevice<std::size_t>::display(
                devices[j],
                CL_DEVICE_IMAGE2D_MAX_WIDTH,
                "CL_DEVICE_IMAGE2D_MAX_WIDTH");

            InfoDevice<std::size_t>::display(
                devices[j],
                CL_DEVICE_IMAGE2D_MAX_HEIGHT,
                "CL_DEVICE_IMAGE2D_MAX_HEIGHT");

            InfoDevice<std::size_t>::display(
                devices[j],
                CL_DEVICE_IMAGE3D_MAX_WIDTH,
                "CL_DEVICE_IMAGE3D_MAX_WIDTH");

            InfoDevice<std::size_t>::display(
                devices[j],
                CL_DEVICE_IMAGE3D_MAX_HEIGHT,
                "CL_DEVICE_IMAGE3D_MAX_HEIGHT");

            InfoDevice<std::size_t>::display(
                devices[j],
                CL_DEVICE_IMAGE3D_MAX_DEPTH,
                "CL_DEVICE_IMAGE3D_MAX_DEPTH");

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_MAX_SAMPLERS,
                "CL_DEVICE_MAX_SAMPLERS");

            InfoDevice<std::size_t>::display(
                devices[j],
                CL_DEVICE_MAX_PARAMETER_SIZE,
                "CL_DEVICE_MAX_PARAMETER_SIZE");

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_MEM_BASE_ADDR_ALIGN,
                "CL_DEVICE_MEM_BASE_ADDR_ALIGN");

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_MIN_DATA_TYPE_ALIGN_SIZE,
                "CL_DEVICE_MIN_DATA_TYPE_ALIGN_SIZE");

            InfoDevice<cl_device_fp_config>::display(
                devices[j],
                CL_DEVICE_SINGLE_FP_CONFIG,
                "CL_DEVICE_SINGLE_FP_CONFIG");

            InfoDevice<cl_device_mem_cache_type>::display(
                devices[j],
                CL_DEVICE_GLOBAL_MEM_CACHE_TYPE,
                "CL_DEVICE_GLOBAL_MEM_CACHE_TYPE");

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_GLOBAL_MEM_CACHELINE_SIZE,
                "CL_DEVICE_GLOBAL_MEM_CACHELINE_SIZE");

            InfoDevice<cl_ulong>::display(
                devices[j],
                CL_DEVICE_GLOBAL_MEM_CACHE_SIZE,
                "CL_DEVICE_GLOBAL_MEM_CACHE_SIZE");

            InfoDevice<cl_ulong>::display(
                devices[j],
                CL_DEVICE_GLOBAL_MEM_SIZE,
                "CL_DEVICE_GLOBAL_MEM_SIZE");

            InfoDevice<cl_ulong>::display(
                devices[j],
                CL_DEVICE_MAX_CONSTANT_BUFFER_SIZE,
                "CL_DEVICE_MAX_CONSTANT_BUFFER_SIZE");

            InfoDevice<cl_uint>::display(
                devices[j],
                CL_DEVICE_MAX_CONSTANT_ARGS,
                "CL_DEVICE_MAX_CONSTANT_ARGS");

            InfoDevice<cl_device_local_mem_type>::display(
                devices[j],
                CL_DEVICE_LOCAL_MEM_TYPE,
                "CL_DEVICE_LOCAL_MEM_TYPE");

            InfoDevice<cl_ulong>::display(
                devices[j],
                CL_DEVICE_LOCAL_MEM_SIZE,
                "CL_DEVICE_LOCAL_MEM_SIZE");

            InfoDevice<cl_bool>::display(
                devices[j],
                CL_DEVICE_ERROR_CORRECTION_SUPPORT,
                "CL_DEVICE_ERROR_CORRECTION_SUPPORT");

#ifdef CL_DEVICE_HOST_UNIFIED_MEMORY
            InfoDevice<cl_bool>::display(
                devices[j],
                CL_DEVICE_HOST_UNIFIED_MEMORY,
                "CL_DEVICE_HOST_UNIFIED_MEMORY");
#endif

            InfoDevice<std::size_t>::display(
                devices[j],
                CL_DEVICE_PROFILING_TIMER_RESOLUTION,
                "CL_DEVICE_PROFILING_TIMER_RESOLUTION");

            InfoDevice<cl_bool>::display(
                devices[j],
                CL_DEVICE_ENDIAN_LITTLE,
                "CL_DEVICE_ENDIAN_LITTLE");

            InfoDevice<cl_bool>::display(
                devices[j],
                CL_DEVICE_AVAILABLE,
                "CL_DEVICE_AVAILABLE");

            InfoDevice<cl_bool>::display(
                devices[j],
                CL_DEVICE_COMPILER_AVAILABLE,
                "CL_DEVICE_COMPILER_AVAILABLE");

            InfoDevice<cl_device_exec_capabilities>::display(
                devices[j],
                CL_DEVICE_EXECUTION_CAPABILITIES,
                "CL_DEVICE_EXECUTION_CAPABILITIES");

            InfoDevice<cl_command_queue_properties>::display(
                devices[j],
                CL_DEVICE_QUEUE_PROPERTIES,
                "CL_DEVICE_QUEUE_PROPERTIES");

            InfoDevice<cl_platform_id>::display(
                devices[j],
                CL_DEVICE_PLATFORM,
                "CL_DEVICE_PLATFORM");

            InfoDevice<ArrayType<char> >::display(
                devices[j],
                CL_DEVICE_NAME,
                "CL_DEVICE_NAME");

            InfoDevice<ArrayType<char> >::display(
                devices[j],
                CL_DEVICE_VENDOR,
                "CL_DEVICE_VENDOR");

            InfoDevice<ArrayType<char> >::display(
                devices[j],
                CL_DRIVER_VERSION,
                "CL_DRIVER_VERSION");

            InfoDevice<ArrayType<char> >::display(
                devices[j],
                CL_DEVICE_PROFILE,
                "CL_DEVICE_PROFILE");

            InfoDevice<ArrayType<char> >::display(
                devices[j],
                CL_DEVICE_VERSION,
                "CL_DEVICE_VERSION");

#ifdef CL_DEVICE_OPENCL_C_VERSION
            InfoDevice<ArrayType<char> >::display(
                devices[j],
                CL_DEVICE_OPENCL_C_VERSION,
                "CL_DEVICE_OPENCL_C_VERSION");
#endif

            InfoDevice<ArrayType<char> >::display(
                devices[j],
                CL_DEVICE_EXTENSIONS,
                "CL_DEVICE_EXTENSIONS");


            std::cout << std::endl << std::endl;
        }
    }
}

//-----------以上为获取并显示OpenCL设备信息的代码------------------

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;  
}  


void Cleanup(cl_context context, cl_command_queue commandQueue,  
             cl_program program, cl_kernel kernel, cl_mem imageObjects[2])  
{  
    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 (context != 0)  
        clReleaseContext(context);  

}  
  
cl_mem LoadImage(cl_context context, char *fileName, int &width, int &height)  
{  
    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;  
}  

size_t RoundUp(int groupSize, int globalSize)  
{  
    int r = globalSize % groupSize;  
    if (r == 0)  
    {  
        return globalSize;  
    }  
    else  
    {  
        return globalSize + groupSize - r;  
    }  
}  

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_int errNum;  

    //打印所有OpenCL平台设备信息
    displayInfo();

    cl_uint numplatforms;
    errNum = clGetPlatformIDs(0, NULL, &numplatforms);
    if (errNum != CL_SUCCESS || numplatforms <= 0){
        printf("没有找到OpenCL平台 \n");
        return 1;
    }

    cl_platform_id * platformIds;
    platformIds = (cl_platform_id*)alloca(sizeof(cl_platform_id)*numplatforms);
    errNum = clGetPlatformIDs(numplatforms, platformIds, NULL);
    if (errNum != CL_SUCCESS){
        printf("没有找到OpenCL平台 \n");
        return 1;
    }
    printf("平台数:%d \n", numplatforms);

    //选用CL_DEVICE_MAX_WORK_GROUP_SIZE最大的显卡
    cl_uint numDevices,index_platform = 0,index_device = 0;
    cl_device_id *devicesIds;
    std::size_t paramValueSize = 0;
    for (cl_uint i = 0; i < numplatforms; i++){
        errNum = clGetDeviceIDs(platformIds[i], CL_DEVICE_TYPE_GPU, 0, NULL, &numDevices);
        if (errNum != CL_SUCCESS || numDevices <= 0){
            printf("平台 %d 没有找到设备",i);
            continue;
        }
        devicesIds = (cl_device_id*)alloca(sizeof(cl_device_id)*numDevices);
        errNum = clGetDeviceIDs(platformIds[i], CL_DEVICE_TYPE_GPU, numDevices, devicesIds, NULL);
        if (errNum != CL_SUCCESS ){
            printf("平台 %d 获取设备ID失败", i);
            continue;
        }

        for (cl_uint j = 0; j < numDevices; j++){
            std::size_t tmpSize = 0;
            errNum = clGetDeviceInfo(devicesIds[j], CL_DEVICE_MAX_WORK_GROUP_SIZE, sizeof(size_t), &tmpSize, NULL);
            if (errNum != CL_SUCCESS){
                std::cerr << "Failed to find OpenCL device info " << std::endl;
                continue;
            }

            if (tmpSize >= paramValueSize){
                index_platform = i;
                index_device = j;
            }
        }
    }

    cl_context_properties contextProperties[] ={
        CL_CONTEXT_PLATFORM,
        (cl_context_properties)platformIds[index_platform],
        0
    };
    context = clCreateContext(contextProperties, numDevices, devicesIds, NULL, NULL, &errNum);
    if (errNum != CL_SUCCESS){
        std::cerr << "Failed to Create Context " << std::endl;
        return 1;
    }

    device = devicesIds[index_device];

    // Create a command-queue on the first device available  
    // on the created context  
    commandQueue = clCreateCommandQueue(context, device, CL_QUEUE_PROFILING_ENABLE, &errNum);
    if (commandQueue == NULL)  {  
        Cleanup(context, commandQueue, program, kernel, imageObjects);  
         system("pause") ; 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);  
         system("pause") ; return 1; 
    }  

    // Load input image from file and load it into  
    // an OpenCL image object  
    int width, height;  
    char *src0 = "test.png";
    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);  
         system("pause") ; 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);  
         system("pause") ; return 1; 
    }  

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

    // Set the kernel arguments  
    errNum = clSetKernelArg(kernel, 0, sizeof(cl_mem), &imageObjects[0]);  
    errNum |= clSetKernelArg(kernel, 1, sizeof(cl_mem), &imageObjects[1]);  
    if (errNum != CL_SUCCESS)  {  
        std::cerr << "Error setting kernel arguments." << std::endl;  
        Cleanup(context, commandQueue, program, kernel, imageObjects);  
        system("pause") ; return 1; 
    }  

    size_t localWorkSize[2] = { 32, 32 };  
    size_t globalWorkSize[2] = { RoundUp(localWorkSize[0], width),  
        RoundUp(localWorkSize[1], height) };  

    cl_event prof_event;

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

    clFinish(commandQueue);
    errNum = clWaitForEvents(1, &prof_event);
    if (errNum)
    {
        printf("clWaitForEvents() failed for histogram_rgba_unorm8 kernel. (%d)\n", errNum);
        return EXIT_FAILURE;
    }

    cl_ulong ev_start_time = (cl_ulong)0;
    cl_ulong ev_end_time = (cl_ulong)0;
    size_t return_bytes;

    errNum = clGetEventProfilingInfo(prof_event, CL_PROFILING_COMMAND_QUEUED,sizeof(cl_ulong), &ev_start_time, &return_bytes);
    errNum |= clGetEventProfilingInfo(prof_event, CL_PROFILING_COMMAND_END,sizeof(cl_ulong), &ev_end_time, &return_bytes);
    if (errNum)
    {
        printf("clGetEventProfilingInfo() failed for kernel. (%d)\n", errNum);
        return EXIT_FAILURE;
    }

    double run_time = (double)(ev_end_time - ev_start_time);

    printf("Image dimensions: %d x %d pixels, Image type = CL_RGBA, CL_UNORM_INT8\n", width, height);
    printf("Work Timer:%lfms\n", run_time / 1000000);

    clReleaseEvent(prof_event);

    // 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);  
         system("pause") ; return 1; 
    }  

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

    // Save the image out to disk  
    char *saveImage = "output.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("原始图像", imageColor);
    cv::imshow("磨皮后", imageColor2);  
    cv::imwrite(saveImage, imageColor2);  
    cv::waitKey(0);  

    delete[] buffer;  

    Cleanup(context, commandQueue, program, kernel, imageObjects);  

    return 0;  
}

    这个host端的程序包含了opencv的一点内容,主要是用opencv来读取图片,用其他方式读取图片当然也是可以的。实际上,opencv本身有一个ocl模块,貌似是由AMD给opencv做得OpenCL扩展,其中包括了许多用OpenCL实现的opencv的一些常用函数,其中就已经包括了双边滤波和自适应双边滤波。

    这段程序选用了CL_DEVICE_MAX_WORK_GROUP_SIZE最大的显卡,最佳的OpenCL设备的选择应当综合考虑,在我的电脑上CL_DEVICE_MAX_WORK_GROUP_SIZE的CPU似乎就是最佳的OpenCL设备,虽然在实际获取的设备信息中CPU的许多参数比GPU强,但是实际运行的时长却是GPU的几倍,所以对于用哪些参数来判断一个OpenCL设备是最佳的我也不是很清楚,希望懂得朋友可以指导一二。

    另外,这段程序其实是很简单的,实际有效的代码只有300多行,获取设备信息的代码只是为了看看自己的电脑上有哪些OpenCL设备以及相关的信息,main中的displayInfo();完全可以注释掉。

    另外关于OpenCL库文件的获取,可以从intel,英伟达,AMD等获取到,我所使用的OpenCL的头文件和lib文件就是从英伟达的CUDA里面copy出来的,你也可以直接就是用我的。

4.运行结果

(1)硬件信息

imageimage

(2)控制台输出OpenCL设备的信息

Number of platforms:    2
        CL_PLATFORM_PROFILE:    FULL_PROFILE
        CL_PLATFORM_VERSION:    OpenCL 2.0
        CL_PLATFORM_VENDOR:     Intel(R) Corporation
        CL_PLATFORM_EXTENSIONS: cl_intel_dx9_media_sharing cl_khr_3d_image_writes cl_khr_byte_addressable_store cl_khr_d3d11_sharing cl_khr_depth_images cl_khr_dx9_media_sharing cl_khr_gl_sharing cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_icd cl_khr_image2d_from_buffer cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_spir
        Number of devices:      2
                CL_DEVICE_TYPE: CL_DEVICE_TYPE_GPU
                CL_DEVICE_VENDOR_ID:    32902
                CL_DEVICE_MAX_COMPUTE_UNITS:    24
                CL_DEVICE_MAX_WORK_ITEM_DIMENSIONS:     3
        CL_DEVICE_MAX_WORK_ITEM_SIZES:  256 256 256
                CL_DEVICE_MAX_WORK_GROUP_SIZE:  256
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_CHAR:  1
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_SHORT: 1
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_INT:   1
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_LONG:  1
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_FLOAT: 1
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_DOUBLE:        0
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_HALF:  1
                CL_DEVICE_NATIVE_VECTOR_WIDTH_CHAR:     1
                CL_DEVICE_NATIVE_VECTOR_WIDTH_SHORT:    1
                CL_DEVICE_NATIVE_VECTOR_WIDTH_INT:      1
                CL_DEVICE_NATIVE_VECTOR_WIDTH_LONG:     1
                CL_DEVICE_NATIVE_VECTOR_WIDTH_FLOAT:    1
                CL_DEVICE_NATIVE_VECTOR_WIDTH_DOUBLE:   0
                CL_DEVICE_NATIVE_VECTOR_WIDTH_HALF:     1
                CL_DEVICE_MAX_CLOCK_FREQUENCY:  1050
                CL_DEVICE_ADDRESS_BITS: 32
                CL_DEVICE_MAX_MEM_ALLOC_SIZE:   390280806
                CL_DEVICE_IMAGE_SUPPORT:        1
                CL_DEVICE_MAX_READ_IMAGE_ARGS:  128
                CL_DEVICE_MAX_WRITE_IMAGE_ARGS: 128
                CL_DEVICE_IMAGE2D_MAX_WIDTH:    16384
                CL_DEVICE_IMAGE2D_MAX_WIDTH:    16384
                CL_DEVICE_IMAGE2D_MAX_HEIGHT:   16384
                CL_DEVICE_IMAGE3D_MAX_WIDTH:    16384
                CL_DEVICE_IMAGE3D_MAX_HEIGHT:   16384
                CL_DEVICE_IMAGE3D_MAX_DEPTH:    2048
                CL_DEVICE_MAX_SAMPLERS: 16
                CL_DEVICE_MAX_PARAMETER_SIZE:   1024
                CL_DEVICE_MEM_BASE_ADDR_ALIGN:  1024
                CL_DEVICE_MIN_DATA_TYPE_ALIGN_SIZE:     128
                CL_DEVICE_SINGLE_FP_CONFIG:     CL_FP_DENORM | CL_FP_INF_NAN | CL_FP_ROUND_TO_NEAREST | CL_FP_ROUND_TO_ZERO | CL_FP_ROUND_TO_INF
                CL_DEVICE_SINGLE_FP_CONFIG:     CL_READ_ONLY_CACHE | CL_READ_WRITE_CACHE
                CL_DEVICE_GLOBAL_MEM_CACHE_TYPE:        CL_READ_WRITE_CACHE
                CL_DEVICE_GLOBAL_MEM_CACHELINE_SIZE:    64
                CL_DEVICE_GLOBAL_MEM_CACHE_SIZE:        524288
                CL_DEVICE_GLOBAL_MEM_SIZE:      1561123226
                CL_DEVICE_MAX_CONSTANT_BUFFER_SIZE:     65536
                CL_DEVICE_MAX_CONSTANT_ARGS:    8
                CL_DEVICE_LOCAL_MEM_TYPE:
                CL_DEVICE_LOCAL_MEM_SIZE:       65536
                CL_DEVICE_ERROR_CORRECTION_SUPPORT:     0
                CL_DEVICE_HOST_UNIFIED_MEMORY:  1
                CL_DEVICE_PROFILING_TIMER_RESOLUTION:   83
                CL_DEVICE_ENDIAN_LITTLE:        1
                CL_DEVICE_AVAILABLE:    1
                CL_DEVICE_COMPILER_AVAILABLE:   1
                CL_DEVICE_EXECUTION_CAPABILITIES:       CL_EXEC_KERNEL
                CL_DEVICE_QUEUE_PROPERTIES:     CL_QUEUE_PROFILING_ENABLE
                CL_DEVICE_PLATFORM:     00DEC488
        CL_DEVICE_NAME: Intel(R) HD Graphics 520
        CL_DEVICE_VENDOR:       Intel(R) Corporation
        CL_DRIVER_VERSION:      20.19.15.4364
        CL_DEVICE_PROFILE:      FULL_PROFILE
        CL_DEVICE_VERSION:      OpenCL 2.0
        CL_DEVICE_OPENCL_C_VERSION:     OpenCL C 2.0
        CL_DEVICE_EXTENSIONS:   cl_intel_accelerator cl_intel_advanced_motion_estimation cl_intel_ctz cl_intel_d3d11_nv12_media_sharing cl_intel_dx9_media_sharing cl_intel_motion_estimation cl_intel_simultaneous_sharing cl_intel_subgroups cl_khr_3d_image_writes cl_khr_byte_addressable_store cl_khr_d3d10_sharing cl_khr_d3d11_sharing cl_khr_depth_images cl_khr_dx9_media_sharing cl_khr_fp16 cl_khr_gl_depth_images cl_khr_gl_event cl_khr_gl_msaa_sharing cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_gl_sharing cl_khr_icd cl_khr_image2d_from_buffer cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_mipmap_image cl_khr_mipmap_image_writes cl_khr_spir


                CL_DEVICE_TYPE: CL_DEVICE_TYPE_CPU
                CL_DEVICE_VENDOR_ID:    32902
                CL_DEVICE_MAX_COMPUTE_UNITS:    4
                CL_DEVICE_MAX_WORK_ITEM_DIMENSIONS:     3
        CL_DEVICE_MAX_WORK_ITEM_SIZES:  8192 8192 8192
                CL_DEVICE_MAX_WORK_GROUP_SIZE:  8192
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_CHAR:  1
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_SHORT: 1
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_INT:   1
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_LONG:  1
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_FLOAT: 1
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_DOUBLE:        1
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_HALF:  0
                CL_DEVICE_NATIVE_VECTOR_WIDTH_CHAR:     32
                CL_DEVICE_NATIVE_VECTOR_WIDTH_SHORT:    16
                CL_DEVICE_NATIVE_VECTOR_WIDTH_INT:      8
                CL_DEVICE_NATIVE_VECTOR_WIDTH_LONG:     4
                CL_DEVICE_NATIVE_VECTOR_WIDTH_FLOAT:    8
                CL_DEVICE_NATIVE_VECTOR_WIDTH_DOUBLE:   4
                CL_DEVICE_NATIVE_VECTOR_WIDTH_HALF:     0
                CL_DEVICE_MAX_CLOCK_FREQUENCY:  2500
                CL_DEVICE_ADDRESS_BITS: 32
                CL_DEVICE_MAX_MEM_ALLOC_SIZE:   536838144
                CL_DEVICE_IMAGE_SUPPORT:        1
                CL_DEVICE_MAX_READ_IMAGE_ARGS:  480
                CL_DEVICE_MAX_WRITE_IMAGE_ARGS: 480
                CL_DEVICE_IMAGE2D_MAX_WIDTH:    16384
                CL_DEVICE_IMAGE2D_MAX_WIDTH:    16384
                CL_DEVICE_IMAGE2D_MAX_HEIGHT:   16384
                CL_DEVICE_IMAGE3D_MAX_WIDTH:    2048
                CL_DEVICE_IMAGE3D_MAX_HEIGHT:   2048
                CL_DEVICE_IMAGE3D_MAX_DEPTH:    2048
                CL_DEVICE_MAX_SAMPLERS: 480
                CL_DEVICE_MAX_PARAMETER_SIZE:   3840
                CL_DEVICE_MEM_BASE_ADDR_ALIGN:  1024
                CL_DEVICE_MIN_DATA_TYPE_ALIGN_SIZE:     128
                CL_DEVICE_SINGLE_FP_CONFIG:     CL_FP_DENORM | CL_FP_INF_NAN | CL_FP_ROUND_TO_NEAREST
                CL_DEVICE_SINGLE_FP_CONFIG:     CL_READ_ONLY_CACHE | CL_READ_WRITE_CACHE
                CL_DEVICE_GLOBAL_MEM_CACHE_TYPE:        CL_READ_WRITE_CACHE
                CL_DEVICE_GLOBAL_MEM_CACHELINE_SIZE:    64
                CL_DEVICE_GLOBAL_MEM_CACHE_SIZE:        262144
                CL_DEVICE_GLOBAL_MEM_SIZE:      2147352576
                CL_DEVICE_MAX_CONSTANT_BUFFER_SIZE:     131072
                CL_DEVICE_MAX_CONSTANT_ARGS:    480
                CL_DEVICE_LOCAL_MEM_TYPE:       CL_LOCAL | CL_GLOBAL
                CL_DEVICE_LOCAL_MEM_SIZE:       32768
                CL_DEVICE_ERROR_CORRECTION_SUPPORT:     0
                CL_DEVICE_HOST_UNIFIED_MEMORY:  1
                CL_DEVICE_PROFILING_TIMER_RESOLUTION:   395
                CL_DEVICE_ENDIAN_LITTLE:        1
                CL_DEVICE_AVAILABLE:    1
                CL_DEVICE_COMPILER_AVAILABLE:   1
                CL_DEVICE_EXECUTION_CAPABILITIES:       CL_EXEC_KERNEL | CL_EXEC_NATIVE_KERNEL
                CL_DEVICE_QUEUE_PROPERTIES:     CL_QUEUE_OUT_OF_ORDER_EXEC_MODE_ENABLE | CL_QUEUE_PROFILING_ENABLE
                CL_DEVICE_PLATFORM:     00DEC488
        CL_DEVICE_NAME: Intel(R) Core(TM) i7-6500U CPU @ 2.50GHz
        CL_DEVICE_VENDOR:       Intel(R) Corporation
        CL_DRIVER_VERSION:      5.2.0.10094
        CL_DEVICE_PROFILE:      FULL_PROFILE
        CL_DEVICE_VERSION:      OpenCL 2.0 (Build 10094)
        CL_DEVICE_OPENCL_C_VERSION:     OpenCL C 2.0
        CL_DEVICE_EXTENSIONS:   cl_khr_icd cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_byte_addressable_store cl_khr_depth_images cl_khr_3d_image_writes cl_intel_exec_by_local_thread cl_khr_spir cl_khr_dx9_media_sharing cl_intel_dx9_media_sharing cl_khr_d3d11_sharing cl_khr_gl_sharing cl_khr_fp64 cl_khr_image2d_from_buffer


        CL_PLATFORM_PROFILE:    FULL_PROFILE
        CL_PLATFORM_VERSION:    OpenCL 1.2 CUDA 8.0.44
        CL_PLATFORM_VENDOR:     NVIDIA Corporation
        CL_PLATFORM_EXTENSIONS: cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_fp64 cl_khr_byte_addressable_store cl_khr_icd cl_khr_gl_sharing cl_nv_compiler_options cl_nv_device_attribute_query cl_nv_pragma_unroll cl_nv_d3d10_sharing cl_khr_d3d10_sharing cl_nv_d3d11_sharing cl_nv_copy_opts
        Number of devices:      1
                CL_DEVICE_TYPE: CL_DEVICE_TYPE_GPU
                CL_DEVICE_VENDOR_ID:    4318
                CL_DEVICE_MAX_COMPUTE_UNITS:    3
                CL_DEVICE_MAX_WORK_ITEM_DIMENSIONS:     3
        CL_DEVICE_MAX_WORK_ITEM_SIZES:  1024 1024 64
                CL_DEVICE_MAX_WORK_GROUP_SIZE:  1024
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_CHAR:  1
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_SHORT: 1
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_INT:   1
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_LONG:  1
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_FLOAT: 1
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_DOUBLE:        1
                CL_DEVICE_PREFERRED_VECTOR_WIDTH_HALF:  0
                CL_DEVICE_NATIVE_VECTOR_WIDTH_CHAR:     1
                CL_DEVICE_NATIVE_VECTOR_WIDTH_SHORT:    1
                CL_DEVICE_NATIVE_VECTOR_WIDTH_INT:      1
                CL_DEVICE_NATIVE_VECTOR_WIDTH_LONG:     1
                CL_DEVICE_NATIVE_VECTOR_WIDTH_FLOAT:    1
                CL_DEVICE_NATIVE_VECTOR_WIDTH_DOUBLE:   1
                CL_DEVICE_NATIVE_VECTOR_WIDTH_HALF:     0
                CL_DEVICE_MAX_CLOCK_FREQUENCY:  1241
                CL_DEVICE_ADDRESS_BITS: 32
                CL_DEVICE_MAX_MEM_ALLOC_SIZE:   536870912
                CL_DEVICE_IMAGE_SUPPORT:        1
                CL_DEVICE_MAX_READ_IMAGE_ARGS:  256
                CL_DEVICE_MAX_WRITE_IMAGE_ARGS: 16
                CL_DEVICE_IMAGE2D_MAX_WIDTH:    16384
                CL_DEVICE_IMAGE2D_MAX_WIDTH:    16384
                CL_DEVICE_IMAGE2D_MAX_HEIGHT:   16384
                CL_DEVICE_IMAGE3D_MAX_WIDTH:    4096
                CL_DEVICE_IMAGE3D_MAX_HEIGHT:   4096
                CL_DEVICE_IMAGE3D_MAX_DEPTH:    4096
                CL_DEVICE_MAX_SAMPLERS: 32
                CL_DEVICE_MAX_PARAMETER_SIZE:   4352
                CL_DEVICE_MEM_BASE_ADDR_ALIGN:  4096
                CL_DEVICE_MIN_DATA_TYPE_ALIGN_SIZE:     128
                CL_DEVICE_SINGLE_FP_CONFIG:     CL_FP_DENORM | CL_FP_INF_NAN | CL_FP_ROUND_TO_NEAREST | CL_FP_ROUND_TO_ZERO | CL_FP_ROUND_TO_INF | CL_FP_FMA
                CL_DEVICE_SINGLE_FP_CONFIG:     CL_READ_ONLY_CACHE | CL_READ_WRITE_CACHE
                CL_DEVICE_GLOBAL_MEM_CACHE_TYPE:        CL_READ_WRITE_CACHE
                CL_DEVICE_GLOBAL_MEM_CACHELINE_SIZE:    128
                CL_DEVICE_GLOBAL_MEM_CACHE_SIZE:        49152
                CL_DEVICE_GLOBAL_MEM_SIZE:      2147483648
                CL_DEVICE_MAX_CONSTANT_BUFFER_SIZE:     65536
                CL_DEVICE_MAX_CONSTANT_ARGS:    9
                CL_DEVICE_LOCAL_MEM_TYPE:
                CL_DEVICE_LOCAL_MEM_SIZE:       49152
                CL_DEVICE_ERROR_CORRECTION_SUPPORT:     0
                CL_DEVICE_HOST_UNIFIED_MEMORY:  0
                CL_DEVICE_PROFILING_TIMER_RESOLUTION:   1000
                CL_DEVICE_ENDIAN_LITTLE:        1
                CL_DEVICE_AVAILABLE:    1
                CL_DEVICE_COMPILER_AVAILABLE:   1
                CL_DEVICE_EXECUTION_CAPABILITIES:       CL_EXEC_KERNEL
                CL_DEVICE_QUEUE_PROPERTIES:     CL_QUEUE_OUT_OF_ORDER_EXEC_MODE_ENABLE | CL_QUEUE_PROFILING_ENABLE
                CL_DEVICE_PLATFORM:     00E30580
        CL_DEVICE_NAME: GeForce 940MX
        CL_DEVICE_VENDOR:       NVIDIA Corporation
        CL_DRIVER_VERSION:      369.30
        CL_DEVICE_PROFILE:      FULL_PROFILE
        CL_DEVICE_VERSION:      OpenCL 1.2 CUDA
        CL_DEVICE_OPENCL_C_VERSION:     OpenCL C 1.2
        CL_DEVICE_EXTENSIONS:   cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_fp64 cl_khr_byte_addressable_store cl_khr_icd cl_khr_gl_sharing cl_nv_compiler_options cl_nv_device_attribute_query cl_nv_pragma_unroll cl_nv_d3d10_sharing cl_khr_d3d10_sharing cl_nv_d3d11_sharing cl_nv_copy_opts


平台数:2
Image dimensions: 273 x 415 pixels, Image type = CL_RGBA, CL_UNORM_INT8
Work Timer:3.422816ms

Executed program succesfully.

273X415大小的图片用时不到4ms。

(3)双边滤波的效果

image

    效果应该来说是很明显的。不过由于没有肤色检测和最后一步锐化,以及参数的设置等问题,连我朋友都说这个磨皮效果太嫩了,看着很假。所以在算法上我这个是有待完善的。

    另外,在速度上,这个算法应该依然有优化的空间。

 

 

源码:http://download.csdn.net/download/qq_33892166/9761287

    源码如果报错“Error queuing kernel for execution.”,尝试修改 size_t localWorkSize[2] = { 32, 32 }; 为 size_t localWorkSize[2] = { 16, 16 };

 

  

标签:

版权申明:本站文章部分自网络,如有侵权,请联系:west999com@outlook.com
特别注意:本站所有转载文章言论不代表本站观点,本站所提供的摄影照片,插画,设计作品,如需使用,请与原作者联系,版权归原作者所有

上一篇:读书笔记 effective c++ Item 21 当你必须返回一个对象的时候,

下一篇:C++ 基本概念