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# Copyright 2014 Diamond Light Source Ltd. |
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# |
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# Licensed under the Apache License, Version 2.0 (the "License"); |
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# you may not use this file except in compliance with the License. |
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# You may obtain a copy of the License at |
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# |
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# http://www.apache.org/licenses/LICENSE-2.0 |
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# |
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# Unless required by applicable law or agreed to in writing, software |
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# distributed under the License is distributed on an "AS IS" BASIS, |
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
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# See the License for the specific language governing permissions and |
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# limitations under the License. |
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""" |
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.. module:: crop_projections |
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:platform: Unix |
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:synopsis: A plugin to crop projections images without the need to specify |
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preview dimensions. |
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.. moduleauthor:: Malte Storm<[email protected]> |
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""" |
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from savu.plugins.plugin import Plugin |
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from savu.plugins.driver.cpu_plugin import CpuPlugin |
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from savu.plugins.utils import register_plugin |
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@register_plugin |
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class CropProjections(Plugin, CpuPlugin): |
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""" |
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A plugin to apply apply a crop to projection images without the need to \ |
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specify preview dimensions. The crop will always be applied symmetrically \ |
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to the original image. |
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:u*param cropX: Crop in pixels applied to the x-dimensions (on each side).\ |
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Default: 0. |
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:u*param cropY: Crop in pixels applied to the y-dimensions (on each side).\ |
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Default: 0. |
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:u*param mode: Select the mode: (absolute|relative|automatic). \ |
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Absolute will use the sizeX/Y parameters to determine the final size, \ |
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relative will crop the images by the amount specified in cropX/Y and \ |
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automatic will use metadata to determine the cropping size. \ |
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Default: 'absolute'. |
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:u*param sizeX: The x-size of the cropped image in pixels. A setting of -1\ |
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means the original size will be preserved. Default: -1. |
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:u*param sizeY: The y-size of the cropped image in pixels. A setting of -1\ |
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means the original size will be preserved. Default: -1. |
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""" |
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def __init__(self): |
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super(CropProjections, self).__init__("CropProjections") |
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def pre_process(self): |
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pass |
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def process_frames(self, data): |
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#in_dataset, out_dataset = self.get_datasets() |
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#print(in_dataset[0].meta_data.get("indices2crop")) |
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#indices2crop = in_dataset[0].meta_data.get('indices2crop') |
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#shapeX = int(indices2crop[1]-indices2crop[0]) |
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#shapeY = int(indices2crop[3]-indices2crop[2]) |
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#print(shapeX, shapeY) |
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return data[0][self.new_slice] |
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def post_process(self): |
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pass |
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def setup(self): |
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in_dataset, out_dataset = self.get_datasets() |
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in_pData, out_pData = self.get_plugin_datasets() |
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in_pData[0].plugin_data_setup('PROJECTION', 'single') |
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det_y = in_dataset[0].get_data_dimension_by_axis_label('detector_y') |
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det_x = in_dataset[0].get_data_dimension_by_axis_label('detector_x') |
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self.shape = list(in_dataset[0].get_shape()) |
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self.core_dims = in_pData[0].get_core_dimensions() |
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img_dims = self.get_in_datasets()[0].get_shape() |
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if self.parameters['mode'] == 'absolute': |
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sizeX = self.parameters['sizeX'] |
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sizeY = self.parameters['sizeY'] |
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if sizeX > 0: |
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xslice = slice(self.shape[det_x] / 2 - sizeX / 2, |
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self.shape[det_x] / 2 + sizeX / 2 + sizeX % 2) |
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self.shape[det_x] = 2 * (sizeX / 2) + sizeX % 2 |
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else: |
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xslice = slice(0, self.shape[det_x]) |
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if sizeY > 0: |
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yslice = slice(self.shape[det_y] / 2 - sizeY / 2, |
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self.shape[det_y] / 2 + sizeY / 2 + sizeY % 2) |
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self.shape[det_y] = 2 * (sizeY / 2) + sizeY % 2 |
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else: |
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yslice = slice(0, self.shape[det_y]) |
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self.new_slice = [yslice, xslice] |
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elif self.parameters['mode'] == 'relative': |
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cropX = self.parameters['cropX'] |
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cropY = self.parameters['cropY'] |
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self.new_slice = [slice(cropY, img_dims[det_y] - cropY), |
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slice(cropX, img_dims[det_x] - cropX)] |
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self.shape[det_x] -= 2 * cropX |
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self.shape[det_y] -= 2 * cropY |
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elif self.parameters['mode'] == 'automatic': |
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print(in_dataset[0].get_name()) |
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print(in_dataset[0].meta_data.get_dictionary().keys()) |
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for key, value in in_dataset[0].meta_data.get_dictionary().iteritems(): |
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print (key, value) |
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#print(in_dataset[0].meta_data.get('indices2crop')) |
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# getting indices to crop the data |
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#sample_data[int(indices2crop[2]):int(indices2crop[3]),int(indices2crop[0]):int(indices2crop[1])] |
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#indices2crop = in_dataset[0].meta_data.get('indices2crop') |
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#shapeX = int(indices2crop[1]-indices2crop[0]) |
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#shapeY = int(indices2crop[3]-indices2crop[2]) |
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#self.new_slice = [slice(indices2crop[0], indices2crop[1]), |
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# slice(indices2crop[2], indices2crop[3])] |
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#self.new_slice = [slice(indices2crop[2], indices2crop[3]), |
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# slice(indices2crop[0], indices2crop[1])] |
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#print(shapeX, shapeY) |
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#self.shape[det_x] = shapeX |
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#self.shape[det_y] = shapeY |
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#print(img_dims[det_x], img_dims[det_y]) |
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self.new_slice = (None, None) |
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out_dataset[0].create_dataset(patterns=in_dataset[0], |
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axis_labels=in_dataset[0], |
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shape=tuple(self.shape)) |
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out_pData[0].plugin_data_setup('PROJECTION', 'single') |
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DiamondLightSource /
Savu
