Create a dataset respecting the HDF5 image specification

h5py_create_image_dataset.py

# images to hdf5
# https://groups.google.com/forum/#!topic/h5py/9sA18XbC_ao
# https://github.com/h5py/h5py/issues/268
import h5py
import numpy

def create_image_dataset(group, dataset_name, image, **kwargs):
    """

    Create a dataset respecting the HDF5 image specification
    http://www.hdfgroup.org/HDF5/doc/ADGuide/ImageSpec.html

    group (HDF group): the group that will contain the dataset
    dataset_name (string): name of the dataset
    image (numpy.ndimage): the image to create. It should have at least 2 dimensions
    returns the new dataset
    """
    assert(len(image.shape) >= 2)
    image_dataset = group.create_dataset(dataset_name, data=image, **kwargs)

    # numpy.string_ is to force fixed-length string (necessary for compatibility)
    image_dataset.attrs["CLASS"] = numpy.string_("IMAGE")
    # Colour image?
    if len(image.shape) == 3 and (image.shape[0] == 3 or image.shape[2] == 3):
        # TODO: check dtype is int?
        image_dataset.attrs["IMAGE_SUBCLASS"] = numpy.string_("IMAGE_TRUECOLOR")
        image_dataset.attrs["IMAGE_COLORMODEL"] = numpy.string_("RGB")
        if image.shape[0] == 3:
            # Stored as [pixel components][height][width]
            image_dataset.attrs["INTERLACE_MODE"] = numpy.string_("INTERLACE_PLANE")
        else: # This is the numpy standard
            # Stored as [height][width][pixel components]
            image_dataset.attrs["INTERLACE_MODE"] = numpy.string_("INTERLACE_PIXEL")
    else:
        image_dataset.attrs["IMAGE_SUBCLASS"] = numpy.string_("IMAGE_GRAYSCALE")
        image_dataset.attrs["IMAGE_WHITE_IS_ZERO"] = numpy.array(0, dtype="uint8")
        image_dataset.attrs["IMAGE_MINMAXRANGE"] = [image.min(), image.max()]

    image_dataset.attrs["DISPLAY_ORIGIN"] = numpy.string_("UL") # not rotated
    image_dataset.attrs["IMAGE_VERSION"] = numpy.string_("1.2")

    return image_dataset