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Merge pull request #23 from MStarmans91/development
Release 3.1.4
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| Original file line number | Diff line number | Diff line change |
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| <?xml version="1.0" encoding="UTF-8"?> | ||
| <module type="WEB_MODULE" version="4"> | ||
| <component name="FacetManager"> | ||
| <facet type="Python" name="Python"> | ||
| <configuration sdkName="" /> | ||
| </facet> | ||
| </component> | ||
| <component name="NewModuleRootManager" inherit-compiler-output="true"> | ||
| <exclude-output /> | ||
| <content url="file://$MODULE_DIR$" /> | ||
| <orderEntry type="inheritedJdk" /> | ||
| <orderEntry type="sourceFolder" forTests="false" /> | ||
| </component> | ||
| </module> |
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| Original file line number | Diff line number | Diff line change |
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| #!/usr/bin/env python | ||
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| # Copyright 2016-2020 Biomedical Imaging Group Rotterdam, Departments of | ||
| # Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands | ||
| # | ||
| # 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. | ||
|
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| import configparser | ||
| import numpy as np | ||
| import os | ||
| import PREDICT.addexceptions as ae | ||
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| def load_config(config_file_path): | ||
| if not os.path.exists(config_file_path): | ||
| e = f'File {config_file_path} does not exist!' | ||
| raise ae.PREDICTKeyError(e) | ||
|
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| settings = configparser.ConfigParser() | ||
| settings.read(config_file_path) | ||
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| settings_dict = {'ImageFeatures': dict(), 'DataPaths': dict(), | ||
| 'General': dict()} | ||
|
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| # Extract some general settings | ||
| settings_dict['General']['Joblib_ncores'] =\ | ||
| settings['General'].getint('Joblib_ncores') | ||
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| settings_dict['General']['Joblib_backend'] =\ | ||
| str(settings['General']['Joblib_backend']) | ||
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| # Extract image feature specific settings | ||
| settings_dict['ImageFeatures']['image_type'] =\ | ||
| [str(item).strip() for item in | ||
| settings['ImageFeatures']['image_type'].split(',')] | ||
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| settings_dict['ImageFeatures']['shape'] =\ | ||
| settings['ImageFeatures'].getboolean('shape') | ||
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| settings_dict['ImageFeatures']['histogram'] =\ | ||
| settings['ImageFeatures'].getboolean('histogram') | ||
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| settings_dict['ImageFeatures']['orientation'] =\ | ||
| settings['ImageFeatures'].getboolean('orientation') | ||
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| settings_dict['ImageFeatures']['texture_Gabor'] =\ | ||
| settings['ImageFeatures'].getboolean('texture_Gabor') | ||
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| settings_dict['ImageFeatures']['texture_GLCM'] =\ | ||
| settings['ImageFeatures'].getboolean('texture_GLCM') | ||
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| settings_dict['ImageFeatures']['texture_GLCMMS'] =\ | ||
| settings['ImageFeatures'].getboolean('texture_GLCMMS') | ||
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| settings_dict['ImageFeatures']['texture_GLRLM'] =\ | ||
| settings['ImageFeatures'].getboolean('texture_GLRLM') | ||
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| settings_dict['ImageFeatures']['texture_GLSZM'] =\ | ||
| settings['ImageFeatures'].getboolean('texture_GLSZM') | ||
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| settings_dict['ImageFeatures']['texture_NGTDM'] =\ | ||
| settings['ImageFeatures'].getboolean('texture_NGTDM') | ||
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| settings_dict['ImageFeatures']['texture_LBP'] =\ | ||
| settings['ImageFeatures'].getboolean('texture_LBP') | ||
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| settings_dict['ImageFeatures']['coliage'] =\ | ||
| settings['ImageFeatures'].getboolean('coliage') | ||
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| settings_dict['ImageFeatures']['vessel'] =\ | ||
| settings['ImageFeatures'].getboolean('vessel') | ||
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| settings_dict['ImageFeatures']['log'] =\ | ||
| settings['ImageFeatures'].getboolean('log') | ||
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| settings_dict['ImageFeatures']['phase'] =\ | ||
| settings['ImageFeatures'].getboolean('phase') | ||
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| # Parameters for computing features | ||
| settings_dict['ImageFeatures']['parameters'] = dict() | ||
|
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| # Gabor settings | ||
| settings_dict['ImageFeatures']['parameters']['gabor_settings'] = dict() | ||
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| gabor_frequencies = [str(item).strip() for item in | ||
| settings['ImageFeatures']['gabor_frequencies'] | ||
| .split(',')] | ||
| gabor_frequencies = np.asarray(gabor_frequencies).astype(np.float) | ||
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| gabor_angles = [str(item).strip() for item in | ||
| settings['ImageFeatures']['gabor_angles'] | ||
| .split(',')] | ||
| gabor_angles = np.asarray(gabor_angles).astype(np.float) | ||
| # Convert gabor angle to radians from angles | ||
| gabor_angles = np.radians(gabor_angles) | ||
|
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| settings_dict['ImageFeatures']['parameters']['gabor_settings']['gabor_frequencies'] =\ | ||
| gabor_frequencies | ||
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| settings_dict['ImageFeatures']['parameters']['gabor_settings']['gabor_angles'] =\ | ||
| gabor_angles | ||
|
|
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| # GLCM | ||
| settings_dict['ImageFeatures']['parameters']['GLCM'] = dict() | ||
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| settings_dict['ImageFeatures']['parameters']['GLCM']['levels'] =\ | ||
| int(settings['ImageFeatures']['GLCM_levels']) | ||
|
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| GLCM_angles = [str(item).strip() for item in | ||
| settings['ImageFeatures']['GLCM_angles'] | ||
| .split(',')] | ||
| settings_dict['ImageFeatures']['parameters']['GLCM']['angles'] =\ | ||
| [float(g) for g in GLCM_angles] | ||
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| GLCM_distances = [str(item).strip() for item in | ||
| settings['ImageFeatures']['GLCM_distances'] | ||
| .split(',')] | ||
| settings_dict['ImageFeatures']['parameters']['GLCM']['distances'] =\ | ||
| [float(g) for g in GLCM_distances] | ||
|
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| # LBP | ||
| settings_dict['ImageFeatures']['parameters']['LBP'] = dict() | ||
|
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| LBP_radius = [str(item).strip() for item in | ||
| settings['ImageFeatures']['LBP_radius'] | ||
| .split(',')] | ||
| settings_dict['ImageFeatures']['parameters']['LBP']['radius'] =\ | ||
| [int(g) for g in LBP_radius] | ||
|
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| LBP_npoints = [str(item).strip() for item in | ||
| settings['ImageFeatures']['LBP_npoints'] | ||
| .split(',')] | ||
| settings_dict['ImageFeatures']['parameters']['LBP']['N_points'] =\ | ||
| [int(g) for g in LBP_npoints] | ||
|
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| # Phase features | ||
| settings_dict['ImageFeatures']['parameters']['phase'] = dict() | ||
|
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| phase_minwavelength = [str(item).strip() for item in | ||
| settings['ImageFeatures']['phase_minwavelength'] | ||
| .split(',')] | ||
| settings_dict['ImageFeatures']['parameters']['phase']['minwavelength'] =\ | ||
| [int(g) for g in phase_minwavelength] | ||
|
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| phase_nscale = [str(item).strip() for item in | ||
| settings['ImageFeatures']['phase_nscale'] | ||
| .split(',')] | ||
| settings_dict['ImageFeatures']['parameters']['phase']['nscale'] =\ | ||
| [int(g) for g in phase_nscale] | ||
|
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| # log features | ||
| settings_dict['ImageFeatures']['parameters']['log'] = dict() | ||
|
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| log_sigma = [str(item).strip() for item in | ||
| settings['ImageFeatures']['log_sigma'] | ||
| .split(',')] | ||
| settings_dict['ImageFeatures']['parameters']['log']['sigma'] =\ | ||
| [int(g) for g in log_sigma] | ||
|
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| # vessel features | ||
| settings_dict['ImageFeatures']['parameters']['vessel'] = dict() | ||
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| vessel_scale_range = [str(item).strip() for item in | ||
| settings['ImageFeatures']['vessel_scale_range'] | ||
| .split(',')] | ||
| settings_dict['ImageFeatures']['parameters']['vessel']['scale_range'] =\ | ||
| [float(g) for g in vessel_scale_range] | ||
|
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| vessel_scale_step = [str(item).strip() for item in | ||
| settings['ImageFeatures']['vessel_scale_step'] | ||
| .split(',')] | ||
| settings_dict['ImageFeatures']['parameters']['vessel']['scale_step'] =\ | ||
| [float(g) for g in vessel_scale_step] | ||
|
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| settings_dict['ImageFeatures']['parameters']['vessel']['radius'] =\ | ||
| int(settings['ImageFeatures']['vessel_radius']) | ||
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| return settings_dict |
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