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 int_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 bool_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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