Using algorithms
Using the library is straighforward. Many ready-to-use algorithm just takes images as input and returns an
image. Consider the algorithm mln::morpho::dilation(). In its simplest form, this algorithm
takes an image, a structuring element and returns an image, dilation(in, se) -> out:
#include <mln/morpho/dilation.hpp>
#include <mln/core/se/disc.hpp>
#include <mln/io/imread.hpp>
#include <mln/io/imsave.hpp>
mln::image2d<uint8_t> input;
mln::io::imread("input.tiff", input);
auto output = mln::morpho::dilation(input, mln::se::disc(5));
mln::io::imsave(output, "out.tiff");
Output image convention
Most algorithms have two versions:
out = algo(in)where the output image is allocated by the algorithm and returnedalgo(in, out)where the user has to provide the output image
Usually, the first version allocates and forward to the second version. The previous snippet of code is equivalent to:
mln::image2d<uint8_t> input;
mln::io::imread("input.tiff", input);
mln::image2d<uint8_t> output(input.width(), input.height);
mln::morpho::dilation(input, mln::se::disc(5), output);
mln::io::imsave(output, "out.tiff");
Parallel algorithms
Pylene supports multithreaded parallelism in some of its algorithms namely for the following pointwise algorithms.
The parallel versions of the algorithms are available in the namespace parallel::.
Using the previous code snippet as an example we would get:
#include <mln/morpho/dilation.hpp>
#include <mln/core/se/disc.hpp>
#include <mln/io/imread.hpp>
#include <mln/io/imsave.hpp>
mln::image2d<uint8_t> input;
mln::io::imread("input.tiff", input);
auto output = mln::morpho::parallel::dilation(input, mln::se::disc(5));
mln::io::imsave(output, "out.tiff");
You can also get better performances by specifying appropriate tile sizes depending on the size of the input image (see Tiling and parallelism)
by adding a height and width parameter to the function call (N.B. those parameters do not need to be equal).
auto output = mln::morpho::parallel::dilation(input, mln::se::disc(5), 128, 128);