# Copyright 2019 Diamond Light Source Ltd.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
.. module:: morph_remove_objects
:platform: Unix
:synopsis: Wrapper around skimage morphology to remove objects smaller than the specified size.
.. moduleauthor:: Daniil Kazantsev <scientificsoftware@diamond.ac.uk>
"""
from savu.plugins.plugin import Plugin
from savu.plugins.driver.cpu_plugin import CpuPlugin
from savu.plugins.utils import register_plugin
import numpy as np
# importing skimage functions
from skimage.morphology import *
[docs]@register_plugin
class MorphRemoveObjects(Plugin, CpuPlugin):
def __init__(self):
super(MorphRemoveObjects, self).__init__("MorphRemoveObjects")
[docs] def setup(self):
in_dataset, out_dataset = self.get_datasets()
in_pData, out_pData = self.get_plugin_datasets()
in_pData[0].plugin_data_setup(self.parameters['pattern'], 'single')
out_dataset[0].create_dataset(in_dataset[0], dtype=np.uint8)
out_pData[0].plugin_data_setup(self.parameters['pattern'], 'single')
[docs] def pre_process(self):
# extract given parameters
self.min_size = self.parameters['min_size']
self.connectivity = self.parameters['connectivity']
[docs] def process_frames(self, data):
# run morphological operations here:
#integerMax = np.max(data[0])
if (np.sum(data[0]) > 0):
morph_result = remove_small_objects(data[0].astype(bool), self.min_size, self.connectivity, in_place=False)
#morph_result = morph_result*1
else:
morph_result = np.uint8(np.zeros(np.shape(data[0])))
return morph_result
[docs] def nOutput_datasets(self):
return 1