# Copyright (c) 2017, System Engineering Software Society
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from __future__ import (print_function, division, unicode_literals,
absolute_import)
from sympathy.api import node
from sympathy.api.nodeconfig import Ports, Tag, Tags
import numpy as np
from skimage import morphology
from sylib.imageprocessing.image import Image
from sylib.imageprocessing.algorithm_selector import ImageFiltering_abstract
[docs]class ImageGenerate(ImageFiltering_abstract, node.Node):
name = 'Generate Image'
author = 'Mathias Broxvall'
copyright = '(C) 2017 System Engineering Software Society'
version = '0.1'
icon = 'image_generate.svg'
description = 'Generates an image or structuring element of a given size'
nodeid = 'syip.imagegenerate'
tags = Tags(Tag.ImageProcessing.IO)
algorithms = {
'empty': {
'description': 'Generates an empty image of a given size',
'width': 'Width of generated image',
'height': 'Height of generated image',
'channels': 'Number of channels in generated image',
'algorithm': lambda par: np.zeros((par['height'].value,
par['width'].value,
par['channels'].value))
},
'disk': {
'description': 'Generates an circular binary structuring element',
'size': 'Radius of the disk',
'algorithm': lambda par: morphology.disk(par['size'].value)
},
'diamond': {
'description': (
'Generates a diamond-shaped binary structuring element.\n\n'
'A pixel is part of the neighborhood if the city '
'block/Manhattan distance between it and the center of the'
'neighborhood is no greater than radius.'),
'size': 'Radius of the disk',
'algorithm': lambda par: morphology.diamond(par['size'].value)
},
'square': {
'description': (
'Generates a square-shaped binary structuring element.'),
'size': 'Size of the square',
'algorithm': lambda par: morphology.square(par['size'].value)
},
'star': {
'description': (
'Generates a star-shaped binary structuring element.\n'
'The star has 8 vertices and is an overlap of a square of '
'size 2n + 1 with its 45 degree rotated version. The slanted '
'sides are 45 or 135 degrees to the horizontal axis.'),
'size': 'Size "N" of the square',
'algorithm': lambda par: morphology.star(par['size'].value)
},
'octagon': {
'description': (
'Generates an octagon-shaped binary structuring element.'),
'size': 'Size of horizontal/vertial parts of the octagon',
'other size': 'Size of diagonal parts of the octagon',
'algorithm': (
lambda par: morphology.octagon(par['size'].value,
par['other size'].value))
},
'rectangle': {
'description': (
'Generates a rectangle-shaped binary structuring element.'),
'width': 'Width of rectangle',
'height': 'Height of rectangle',
'algorithm': lambda par: morphology.rectangle(par['width'].value,
par['height'].value)
},
}
options_list = [
'width', 'height', 'size', 'channels', 'other size'
]
options_types = {
'width': int,
'height': int,
'size': int,
'other size': int,
'channels': int,
}
options_default = {
'width': 512,
'height': 512,
'size': 5,
'other size': 5,
'channels': 1,
}
parameters = node.parameters()
parameters.set_string(
'algorithm', value=next(iter(algorithms)), description='', label='Algorithm')
ImageFiltering_abstract.generate_parameters(
parameters, options_types, options_default)
outputs = Ports([
Image('Resulting image', name='output'),
])
__doc__ = ImageFiltering_abstract.generate_docstring(
description, algorithms, options_list, None, outputs)
def execute(self, node_context):
params = node_context.parameters
alg_name = params['algorithm'].value
alg = self.algorithms[alg_name]['algorithm']
result = alg(params)
node_context.output['output'].set_image(result)