C++ pointer::getProgram方法代码示例

void SeededRegionGrowing::recompileOpenCLCode(Image::pointer input) {
    // Check if there is a need to recompile OpenCL code
    if(input->getDimensions() == mDimensionCLCodeCompiledFor &&
            input->getDataType() == mTypeCLCodeCompiledFor)
        return;

    OpenCLDevice::pointer device = getMainDevice();
    std::string buildOptions = "";
    if(input->getDataType() == TYPE_FLOAT) {
        buildOptions = "-DTYPE_FLOAT";
    } else if(input->getDataType() == TYPE_INT8 || input->getDataType() == TYPE_INT16) {
        buildOptions = "-DTYPE_INT";
    } else {
        buildOptions = "-DTYPE_UINT";
    }
    std::string filename;
    if(input->getDimensions() == 2) {
        filename = "Algorithms/SeededRegionGrowing/SeededRegionGrowing2D.cl";
    } else {
        filename = "Algorithms/SeededRegionGrowing/SeededRegionGrowing3D.cl";
    }
    int programNr = device->createProgramFromSource(std::string(FAST_SOURCE_DIR) + filename, buildOptions);
    mKernel = cl::Kernel(device->getProgram(programNr), "seededRegionGrowing");
    mDimensionCLCodeCompiledFor = input->getDimensions();
    mTypeCLCodeCompiledFor = input->getDataType();
}

void DoubleFilter::execute() {
    if(!mInput.isValid()) {
        throw Exception("No input supplied to GaussianSmoothingFilter");
    }

    Image::pointer input = mInput;
    Image::pointer output = mOutput;

    // Initialize output image
    output->createFromImage(input, mDevice);

    if(mDevice->isHost()) {
        // Execution device is Host, use the executeAlgorithmOnHost function with the given data type
        switch(input->getDataType()) {
            // This macro creates a case statement for each data type and sets FAST_TYPE to the correct C++ data type
            fastSwitchTypeMacro(executeAlgorithmOnHost<FAST_TYPE>(input, output));
        }
    } else {
        // Execution device is an OpenCL device
        OpenCLDevice::pointer device = boost::static_pointer_cast<OpenCLDevice>(mDevice);

        // Set build options based on the data type of the data
        std::string buildOptions = "";
        switch(input->getDataType()) {
        case TYPE_FLOAT:
            buildOptions = "-DTYPE=float";
            break;
        case TYPE_INT8:
            buildOptions = "-DTYPE=char";
            break;
        case TYPE_UINT8:
            buildOptions = "-DTYPE=uchar";
            break;
        case TYPE_INT16:
            buildOptions = "-DTYPE=short";
            break;
        case TYPE_UINT16:
            buildOptions = "-DTYPE=ushort";
            break;
        }

        // Compile the code
        int programNr = device->createProgramFromSource(std::string(FAST_SOURCE_DIR) + "Tests/Algorithms/DoubleFilter.cl", buildOptions);
        cl::Kernel kernel = cl::Kernel(device->getProgram(programNr), "doubleFilter");

        // Get global size for the kernel
        cl::NDRange globalSize(input->getWidth()*input->getHeight()*input->getDepth()*input->getNrOfComponents());

        // Set the arguments for the kernel
        OpenCLBufferAccess inputAccess = input->getOpenCLBufferAccess(ACCESS_READ, device);
        OpenCLBufferAccess outputAccess = output->getOpenCLBufferAccess(ACCESS_READ_WRITE, device);
        kernel.setArg(0, *inputAccess.get());
        kernel.setArg(1, *outputAccess.get());

        // Execute the kernel
        device->getCommandQueue().enqueueNDRangeKernel(
                kernel,
                cl::NullRange,
                globalSize,
                cl::NullRange
        );
    }

    // Update timestamp of the output data
    output->updateModifiedTimestamp();
}

void getIntensitySumFromOpenCLImage(OpenCLDevice::pointer device, cl::Image2D image, DataType type, float* sum) {
    // Get power of two size
    unsigned int powerOfTwoSize = getPowerOfTwoSize(std::max(image.getImageInfo<CL_IMAGE_WIDTH>(), image.getImageInfo<CL_IMAGE_HEIGHT>()));

    // Create image levels
    unsigned int size = powerOfTwoSize;
    size /= 2;
    std::vector<cl::Image2D> levels;
    while(size >= 4) {
        cl::Image2D level = cl::Image2D(device->getContext(), CL_MEM_READ_WRITE, getOpenCLImageFormat(device, CL_MEM_OBJECT_IMAGE2D, TYPE_FLOAT, 1), size, size);
        levels.push_back(level);
        size /= 2;
    }

    // Compile OpenCL code
    std::string buildOptions = "";
    switch(type) {
    case TYPE_FLOAT:
        buildOptions = "-DTYPE_FLOAT";
        break;
    case TYPE_UINT8:
        buildOptions = "-DTYPE_UINT8";
        break;
    case TYPE_INT8:
        buildOptions = "-DTYPE_INT8";
        break;
    case TYPE_UINT16:
        buildOptions = "-DTYPE_UINT16";
        break;
    case TYPE_INT16:
        buildOptions = "-DTYPE_INT16";
        break;
    }
    std::string sourceFilename = std::string(FAST_SOURCE_DIR) + "/ImageSum.cl";
    std::string programName = sourceFilename + buildOptions;
    // Only create program if it doesn't exist for this device from before
    if(!device->hasProgram(programName))
        device->createProgramFromSourceWithName(programName, sourceFilename, buildOptions);
    cl::Program program = device->getProgram(programName);
    cl::CommandQueue queue = device->getCommandQueue();

    // Fill first level
    size = powerOfTwoSize/2;
    cl::Kernel firstLevel(program, "createFirstSumImage2DLevel");
    firstLevel.setArg(0, image);
    firstLevel.setArg(1, levels[0]);

    queue.enqueueNDRangeKernel(
            firstLevel,
            cl::NullRange,
            cl::NDRange(size,size),
            cl::NullRange
    );

    // Fill all other levels
    cl::Kernel createLevel(program, "createSumImage2DLevel");
    int i = 0;
    size /= 2;
    while(size >= 4) {
        createLevel.setArg(0, levels[i]);
        createLevel.setArg(1, levels[i+1]);
        queue.enqueueNDRangeKernel(
                createLevel,
                cl::NullRange,
                cl::NDRange(size,size),
                cl::NullRange
        );
        i++;
        size /= 2;
    }

    // Get result from the last level
    unsigned int nrOfElements = 4*4;
    unsigned int nrOfComponents = getOpenCLImageFormat(device, CL_MEM_OBJECT_IMAGE2D, TYPE_FLOAT, 1).image_channel_order == CL_RGBA ? 4 : 1;
    float* result = (float*)allocateDataArray(nrOfElements,TYPE_FLOAT,nrOfComponents);
    queue.enqueueReadImage(levels[levels.size()-1],CL_TRUE,createOrigoRegion(),createRegion(4,4,1),0,0,result);
    *sum = getSumFromOpenCLImageResult<float>(result, nrOfElements, nrOfComponents);
    delete[] result;
}

void getMaxAndMinFromOpenCLBuffer(OpenCLDevice::pointer device, cl::Buffer buffer, unsigned int size, DataType type, float* min, float* max) {
    // Compile OpenCL code
    std::string buildOptions = "";
    switch(type) {
    case TYPE_FLOAT:
        buildOptions = "-DTYPE_FLOAT";
        break;
    case TYPE_UINT8:
        buildOptions = "-DTYPE_UINT8";
        break;
    case TYPE_INT8:
        buildOptions = "-DTYPE_INT8";
        break;
    case TYPE_UINT16:
        buildOptions = "-DTYPE_UINT16";
        break;
    case TYPE_INT16:
        buildOptions = "-DTYPE_INT16";
        break;
    }
    std::string sourceFilename = std::string(FAST_SOURCE_DIR) + "/ImageMinMax.cl";
    std::string programName = sourceFilename + buildOptions;
    // Only create program if it doesn't exist for this device from before
    if(!device->hasProgram(programName))
        device->createProgramFromSourceWithName(programName, sourceFilename, buildOptions);
    cl::Program program = device->getProgram(programName);
    cl::CommandQueue queue = device->getCommandQueue();

    // Nr of work groups must be set so that work-group size does not exceed max work-group size (256 on AMD)
    int length = size;
    cl::Kernel reduce(program, "reduce");

    cl::Buffer current = buffer;
    cl::Buffer clResult;
    int workGroupSize = 256;
    int workGroups = 256;
    int X = ceil((float)length / (workGroups*workGroupSize));

    clResult = cl::Buffer(device->getContext(), CL_MEM_READ_WRITE, getSizeOfDataType(type,1)*workGroups*2);
    reduce.setArg(0, current);
    reduce.setArg(1, workGroupSize * getSizeOfDataType(type,1), NULL);
    reduce.setArg(2, workGroupSize * getSizeOfDataType(type,1), NULL);
    reduce.setArg(3, size);
    reduce.setArg(4, X);
    reduce.setArg(5, clResult);

    queue.enqueueNDRangeKernel(
            reduce,
            cl::NullRange,
            cl::NDRange(workGroups*workGroupSize),
            cl::NDRange(workGroupSize)
    );

    length = workGroups;

    void* result = allocateDataArray(length, type, 2);
    unsigned int nrOfElements = length;
    queue.enqueueReadBuffer(clResult,CL_TRUE,0,getSizeOfDataType(type,1)*workGroups*2,result);
    switch(type) {
    case TYPE_FLOAT:
        getMaxAndMinFromOpenCLImageResult<float>(result, nrOfElements, 2, min, max);
        break;
    case TYPE_INT8:
        getMaxAndMinFromOpenCLImageResult<char>(result, nrOfElements, 2, min, max);
        break;
    case TYPE_UINT8:
        getMaxAndMinFromOpenCLImageResult<uchar>(result, nrOfElements, 2, min, max);
        break;
    case TYPE_INT16:
        getMaxAndMinFromOpenCLImageResult<short>(result, nrOfElements, 2, min, max);
        break;
    case TYPE_UINT16:
        getMaxAndMinFromOpenCLImageResult<ushort>(result, nrOfElements, 2, min, max);
        break;
    }
    deleteArray(result, type);
}