Create 3D Image

This example illustrates how to create a data buffer corresponding to a 3D image, and copy it in an object connectable to an ImageDev algorithm.

To invoke an ImageDev algorithm, the data to process needs to be previously imported into an ImageView object of the IOLink library.

The first part of this example simply creates a buffer representing a 220x192x128 pixel image with a filled cube drawn inside. This step is for demonstration purposes only. In practice, you should already have the content of the image to process in a buffer stored in the data model used by your application.

Then some IOLink instructions create a new ImageView object. The buffer previously created is copied in this image with the WriteRegion method.

An ImageDev algorithm is applied afterward to show that it is now possible to process this image with ImageDev. This is the GaussianFilter3d algorithm which introduce a blur effect between the cube surface and the image background.

<b>Figure 1.</b> The 3D volume generated by this example visualized with Open Inventor

Figure 1. The 3D volume generated by this example visualized with Open Inventor

#include <ImageDev/Data/ImageViewHelper.h>
#include <ImageDev/ImageDev.h>
#include <ioformat/IOFormat.h>
#include <iolink/view/ImageViewFactory.h>
#include <iolink/view/ImageViewProvider.h>
#include <string.h>

using namespace imagedev;
using namespace ioformat;
using namespace iolink;

int
main( int argc, char* argv[] )
{
    int status = 0;

    try
    {
        // ImageDev library initialization
        if ( imagedev::isInitialized() == false )
            imagedev::init();

        // Initialize an unsigned 8-bit array storing data of a 3D image
        const uint64_t rowCount = 220;
        const uint64_t colCount = 192;
        const uint64_t sliCount = 128;
        std::vector< uint8_t > imageData( rowCount * colCount * sliCount );

        // Define a synthetic cube in this array
        const uint64_t side = colCount / 2; // side in pixels of the cube to draw

        // Loop on image slices
        for ( uint64_t k = 0; k < sliCount; ++k )
        {
            // Loop on image rows
            for ( uint64_t i = 0; i < rowCount; ++i )
            {
                // Loop on image columns
                for ( uint64_t j = 0; j < colCount; ++j )
                {
                    if ( ( i >= ( rowCount - side ) / 2 ) && ( i <= ( rowCount + side ) / 2 ) &&
                         ( j >= ( colCount - side ) / 2 ) && ( j <= ( colCount + side ) / 2 ) &&
                         ( k >= ( sliCount - side ) / 2 ) && ( k <= ( sliCount + side ) / 2 ) )
                        imageData[k * rowCount * colCount + i * colCount + j] = 228; // Value inside the cube
                    else
                        imageData[k * rowCount * colCount + i * colCount + j] = 0; // Background value
                }
            }
        }

        // Create an image view of same dimensions
        VectorXu64 imageShape{ colCount, rowCount, sliCount };
        auto image = ImageViewFactory::allocate( imageShape, DataTypeId::UINT8 );
        setDimensionalInterpretation( image, ImageTypeId::VOLUME );

        // Define the region where to write the data
        VectorXu64 imageOrig{ 0, 0, 0 };
        RegionXu64 imageRegion{ imageOrig, imageShape };

        // Copy the data in the image view
        image->writeRegion( imageRegion, imageData.data() );

        // This image can now be processed by any ImageDev algorithm, for instance for building a color image
        auto imageGauss = gaussianFilter3d( image,
                                            GaussianFilter3d::FilterMode::SEPARABLE,
                                            { 10.0f, 10.0f, 10.0f },
                                            2.0f,
                                            GaussianFilter3d::OutputType::SAME_AS_INPUT,
                                            false );

        // Save the created image with IOFormat
        writeView( imageGauss, "T02_02_output.tif" );

        std::cout << "This example ran successfully." << std::endl;
    }
    catch ( const imagedev::Exception& error )
    {
        // Print potential exception in the standard output
        std::cerr << "ImageDev exception: " << error.what() << std::endl;
        status = -1;
    }

    // ImageDev library finalization
    imagedev::finish();

    // Check if we must ask for an enter key to close the program
    if ( !( ( argc == 2 ) && strcmp( argv[1], "--no-stop-at-end" ) == 0 ) )
        std::cout << "Press Enter key to close this window." << std::endl, getchar();

    return status;
}

using System;
using ImageDev;
using IOLink;
using IOFormat;

namespace T02_02_CreateImage3d
{
    class Program
    {
        static void Main(string[] args)
        {
            int status = 0;

            try
            {
                // Initialize the ImageDev library if not done
                if (Initialization.IsInitialized() == false)
                    Initialization.Init();

                // Initialize an unsigned 8-bit array storing data of a 3D image
                ulong rowCount = 220;
                ulong colCount = 192;
                ulong sliCount = 128;
                byte[] imageData = new byte[rowCount * colCount * sliCount];

                // Define a synthetic cube in this array
                ulong side = colCount / 2; // side in pixels of the cube to draw

                // Loop on image slices
                for (ulong k = 0; k < sliCount; ++k)
                {
                    // Loop on image rows
                    for (ulong i = 0; i < rowCount; ++i)
                    {
                        // Loop on image columns
                        for (ulong j = 0; j < colCount; ++j)
                        {
                            if ((i >= (rowCount - side) / 2) && (i <= (rowCount + side) / 2) &&
                                 (j >= (colCount - side) / 2) && (j <= (colCount + side) / 2) &&
                                 (k >= (sliCount - side) / 2) && (k <= (sliCount + side) / 2))
                                imageData[k * rowCount * colCount + i * colCount + j] = 228; // Value inside the cube
                            else
                                imageData[k * rowCount * colCount + i * colCount + j] = 0; // Background value
                        }
                    }
                }

                // Create an image view of same dimensions
                VectorXu64 imageShape = new VectorXu64(colCount, rowCount, sliCount);
                ImageView image = ImageViewFactory.Allocate(imageShape, DataTypeId.UINT8);
                Data.SetDimensionalInterpretation(image, ImageTypeId.VOLUME);

                // Define the region where to write the data
                VectorXu64 imageOrig = new VectorXu64(0, 0, 0);
                RegionXu64 imageRegion = new RegionXu64(imageOrig, imageShape);

                // Copy the data in the image view
                image.WriteRegion(imageRegion, imageData);

                // This image can now be processed by any ImageDev algorithm, for instance to generate a blur effect on its
                // edges
                ImageView imageGauss = Processing.GaussianFilter3d(image,
                                                                    GaussianFilter3d.FilterMode.SEPARABLE,
                                                                    new double[] { 10.0, 10.0, 10.0 });

                // Save the created image with IOFormat
                ViewIO.WriteView(imageGauss, "T02_02_output.tif");

            }
            catch (Exception error)
            {
                // Print potential exception in the standard output
                System.Console.WriteLine("HelloImageDev exception: " + error.ToString());
                status = -1;
            }

            // ImageDev library finalization
            Initialization.Finish();

            // Check if we must ask for an enter key to close the program
            if (!((args.Length >= 1) && (args[0] == "--no-stop-at-end")))
            {
                System.Console.WriteLine("Press Enter key to close this window.");
                System.Console.ReadKey();
            }

            System.Environment.Exit(status);
        }
    }
}

import imagedev
import iolink
import ioformat
import numpy

# Initialize the ImageDev library if not done
if (imagedev.is_initialized() == False): imagedev.init()

# Initialize an unsigned 8 - bit array storing data of a 3D image
row_count = 220
col_count = 192
sli_count = 128
image_data = numpy.zeros((row_count , col_count , sli_count), numpy.uint8)
# Define a synthetic cube in this array
side = int(col_count / 2) # side in pixels of the cube to draw

image_data[int((row_count - side) / 2):int((row_count + side) / 2),
           int((col_count - side) / 2):int((col_count + side) / 2),
           int((sli_count - side) / 2):int((sli_count + side) / 2)] = 228

# Create an image view of same dimensions VectorXu64
image_shape = iolink.VectorXu64(col_count, row_count, sli_count)
image = iolink.ImageViewFactory.allocate(image_shape, iolink.DataTypeId_UINT8)
imagedev.set_dimensional_interpretation(image, iolink.ImageTypeId.VOLUME)

# Define the region where to write the data
image_orig = iolink.VectorXu64(0, 0, 0)
image_region = iolink.RegionXu64(image_orig, image_shape)

# Copy the data in the image view
image.write_region(image_region, image_data)

# This image can now be processed by any ImageDev algorithm, for instance to generate a blur effect on its edges
image_gauss = imagedev.gaussian_filter_3d(image, imagedev.GaussianFilter3d.FilterMode.SEPARABLE, [10.0, 10.0, 10.0])

# Save the created image with IOFormat
ioformat.write_view(image_gauss, "T02_02_output.tif")

# ImageDev library finalization
imagedev.finish()

See also

GaussianFilter3d