def blur_gaussian(img_paths, radius=3, size=None, write=True): """blur_gaussian(img_paths, radius=3, size=None, write=True) Takes images(s) and blurs them using a gaussian kernel based on a given radius. :type img_paths: pyifx.misc.PyifxImage, pyifx.misc.ImageVolume, list :param img_paths: The image(s) to be blurred. :type radius: int :param radius: The radius of the gaussian kernel. If nothing is entered for this parameter, it will default to 3. :type size: list, NoneType :param size: The dimensions of the gaussian kernel. Must be entered in :type write: bool :param write: Whether to write the blurred image(s). :return: PyifxImage instance, ImageVolume instance, or list with elements of type PyifxImage :rtype: pyifx.misc.PyifxImage, pyifx.misc.ImageVolume, list """ INTERNAL._type_checker(radius, [int, float]) INTERNAL._type_checker(img_paths, [misc.PyifxImage, misc.ImageVolume, list]) INTERNAL._type_checker(write, [bool]) INTERNAL._type_checker(size, [int, list, np.ndarray, None]) return INTERNAL._convolution_handler(img_paths, radius=radius, type_kernel="gaussian", size=size, custom=None, write=write)
def convolute_custom(img_paths, kernel, write=True): """ convolute_custom(img_paths, kernel, write=True) Takes image(s) and creates new images that are convoluted over using a given kernel. :type img_paths: pyifx.misc.PyifxImage, pyifx.misc.ImageVolume, list :param img_paths: The image(s) to be convoluted over. :type kernel: numpy.ndarray, list :param kernel: The kernel to be used for convolution. This can be provided in either a 2-dimensional list or a numpy 2-dimensional array. :type write: bool :param write: Whether to write the convoluted image(s). :return: PyifxImage instance, ImageVolume instance, or list with elements of type PyifxImage :rtype: pyifx.misc.PyifxImage, pyifx.misc.ImageVolume, list """ INTERNAL._type_checker(kernel, [np.ndarray, list]) INTERNAL._type_checker(img_paths, [misc.PyifxImage, misc.ImageVolume, list]) INTERNAL._type_checker(write, [bool]) return INTERNAL._convolution_handler(img_paths, radius=None, type_kernel=None, size=None, custom=kernel, write=write)