# This file is part of Sympathy for Data.
# Copyright (c) 2017, Combine Control Systems AB
#
# Sympathy for Data is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, version 3 of the License.
#
# Sympathy for Data is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with Sympathy for Data. If not, see <http://www.gnu.org/licenses/>.
from sympathy.api import node
from sympathy.api.nodeconfig import Port, Ports, Tag, Tags
from sympathy.utils import port
from skimage import io, data
from sylib.imageprocessing.image import ImagePort
import sylib.imageprocessing
import numpy as np
import os.path
[docs]class LoadImage(node.Node):
"""
Loads an image from a file given by a datasource.
"""
name = 'Load Image'
author = 'Mathias Broxvall'
version = '0.1'
icon = 'image_load.svg'
description = 'Loads an image from a datasource'
nodeid = 'syip.loadimage'
tags = Tags(Tag.ImageProcessing.IO)
parameters = node.parameters()
parameters.set_boolean(
'as_greyscale', label='As greyscale',
description='Transforms image to greyscale if not already such',
value=False)
inputs = Ports(
[Port.Datasource('Source of image data. Must be a file on disk',
name='source')])
outputs = Ports(
[ImagePort('Output image', name='image')])
def execute(self, node_context):
source = node_context.input['source']
if source.decode_type() != 'FILE':
raise NotImplementedError(
'Image loading from databases not implemented.')
source_path = source.decode_path()
as_greyscale = node_context.parameters['as_greyscale'].value
image = io.imread(source_path, as_gray=as_greyscale)
if image.dtype == np.uint8:
image = image / 255
node_context.output['image'].set_image(image)
[docs]class LoadImageList(node.Node):
"""
Loads a list of images from a file given a list of datasources.
"""
name = 'Load Image List'
author = 'Mathias Broxvall'
version = '0.1'
icon = 'image_load.svg'
description = 'Loads an image from a datasource'
nodeid = 'syip.loadimage_list'
tags = Tags(Tag.ImageProcessing.IO)
parameters = node.parameters()
parameters.set_boolean(
'as_greyscale', label='As greyscale',
description='Transforms image to greyscale if not already such',
value=False)
inputs = Ports([port.CustomPort(
'[datasource]',
'Source of image data. Must be a file on disk',
name='source')])
outputs = Ports(
[port.CustomPort('[image]', 'Output image', name='image')])
def execute(self, node_context):
for idx, source in enumerate(node_context.input['source']):
self.set_progress((100*idx) / len(node_context.input['source']))
if source.decode_type() != 'FILE':
raise NotImplementedError(
'Image loading from databases not implemented.')
source_path = source.decode_path()
as_greyscale = node_context.parameters['as_greyscale'].value
image = io.imread(source_path, as_gray=as_greyscale)
if image.dtype == np.uint8:
image = image / 255
image_obj = sylib.imageprocessing.image.File()
image_obj.set_image(image)
node_context.output['image'].append(image_obj)
[docs]class ExampleImage(node.Node):
"""
Loads an image from the built-in default example images in scikit-image
"""
name = 'Example Image'
author = 'Mathias Broxvall'
version = '0.1'
icon = 'image_examples.svg'
description = (
'Loads an image from the built-in default example images in '
'scikit-image')
nodeid = 'syip.exampleimage'
tags = Tags(Tag.ImageProcessing.IO)
parameters = node.parameters()
parameters.set_string(
'source', value='coins', label='Image',
description='Selected predefined image',
editor=node.editors.combo_editor(
sorted([
'astronaut', 'camera', 'candy', 'checkerboard',
'chelsea (cat)', 'clock',
'coffee', 'coins', 'horse', 'hubble deep field', 'page',
'motorcycle_left', 'motorcycle_right',
'immunohistochemistry', 'moon', 'rocket', 'text']))
)
outputs = Ports([ImagePort('Output image', name='output')])
def execute(self, node_context):
source_name = node_context.parameters['source'].value
if source_name == 'astronaut':
im = data.astronaut()
elif source_name == 'camera':
im = data.camera()
elif source_name == 'checkerboard':
im = data.checkerboard()
elif source_name == 'chelsea (cat)':
im = data.chelsea()
elif source_name == 'clock':
im = data.clock()
elif source_name == 'coffee':
im = data.coffee()
elif source_name == 'coins':
im = data.coins()
elif source_name == 'horse':
im = data.horse()
elif source_name == 'hubble deep field':
im = data.hubble_deep_field()
elif source_name == 'immunohistochemistry':
im = data.immunohistochemistry()
elif source_name == 'moon':
im = data.moon()
elif source_name == 'rocket':
im = data.rocket()
elif source_name == 'text':
im = data.text()
elif source_name == 'page':
im = data.page()
elif source_name == 'motorcycle_left':
im = data.stereo_motorcycle()[0]
elif source_name == 'motorcycle_right':
im = data.stereo_motorcycle()[1]
elif source_name == 'candy':
path = os.path.join(
os.path.dirname(sylib.imageprocessing.__file__),
"candy.png")
im = io.imread(path, as_gray=False)
else:
im = np.zeros((512, 512, 3))
if im.dtype == 'uint8':
im = im/256.0
node_context.output['output'].set_image(im)
