48 lines
2.0 KiB
Python
48 lines
2.0 KiB
Python
#! /usr/bin/env python
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from dynamic_reconfigure.parameter_generator_catkin import bool_t
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from dynamic_reconfigure.parameter_generator_catkin import double_t
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from dynamic_reconfigure.parameter_generator_catkin import int_t
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from dynamic_reconfigure.parameter_generator_catkin import str_t
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# set up parameters that we care about
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PACKAGE = 'pcl_ros'
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def add_common_parameters(gen):
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# add(self, name, paramtype, level, description, default = None, min = None,
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# max = None, edit_method = '')
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gen.add('max_iterations', int_t, 0,
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'The maximum number of iterations the algorithm will run for',
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50, 0, 100000)
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gen.add('probability', double_t, 0,
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'The desired probability of choosing at least one sample free from outliers',
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0.99, 0.5, 0.99)
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gen.add('distance_threshold', double_t, 0,
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'The distance to model threshold',
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0.02, 0, 1.0)
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gen.add('optimize_coefficients', bool_t, 0,
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'Model coefficient refinement',
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True)
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gen.add('radius_min', double_t, 0,
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'The minimum allowed model radius (where applicable)',
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0.0, 0, 1.0)
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gen.add('radius_max', double_t, 0,
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'The maximum allowed model radius (where applicable)',
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0.05, 0, 1.0)
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gen.add('eps_angle', double_t, 0,
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('The maximum allowed difference between the model normal '
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'and the given axis in radians.'),
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0.17, 0.0, 1.5707)
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gen.add('min_inliers', int_t, 0,
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'The minimum number of inliers a model must have in order to be considered valid.',
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0, 0, 100000)
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gen.add('input_frame', str_t, 0,
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('The input TF frame the data should be transformed into, '
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'if input.header.frame_id is different.'),
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'')
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gen.add('output_frame', str_t, 0,
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('The output TF frame the data should be transformed into, '
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'if input.header.frame_id is different.'),
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'')
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