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CVBpy 14.0
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CVBpy 14.0
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Definition of search parameters. More...
Inherits object.
Properties | |
| derivative_patch_size = property | |
| int: Get or set smoothing area in pixels for gradient and normal calculation. More... | |
| hypotheses_threshold = property | |
| float: Get or set minimum feature score for hypotheses generation. More... | |
| icp_max_iterations = property | |
| int: Get or set the maximum number of iterations of the ICP algorithm. More... | |
| icp_shrink = property | |
| int: Get or set the subsample factor for ICP. More... | |
| indifferent_radius = property | |
| float: Get or set fraction of template size which accounts for a single object. More... | |
| max_inconsistency = property | |
| float: Get or set maximum inconsistency. More... | |
| max_occlusion = property | |
| float: Get or set maximum occlusion. More... | |
| min_coverage = property | |
| float: Get or set minimum coverage. More... | |
| min_score = property | |
| float: Get or set minimum score. More... | |
| parts_to_find = property | |
| int: Get or set the maximum number of objects to find. More... | |
| precision_threshold = property | |
| float: Get or set precision threshold. More... | |
| raw_results_only = property | |
| bool: Get or set the raw results flag. More... | |
Definition of search parameters.
Search parameters strongly influence the search results. Likewise, they havegreat influence on the timing of a search operation.
Default search parameters.
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int: Get or set smoothing area in pixels for gradient and normal calculation.
The value should be odd. Typical values are in the range 3..9. The minimum value is 3.
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float: Get or set minimum feature score for hypotheses generation.
The value controls which areas of the depth image are used as candidates for closer examination. Typical values are in the range between 0.9 ... 1.0. The minimum value is 0.5.
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int: Get or set the maximum number of iterations of the ICP algorithm.
Increasing the value may increase the accuracy of the result, while possibly increasing the processing time. A typical value is 10. The minimum value is 1.
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int: Get or set the subsample factor for ICP.
The minimum allowed value of 1 means no reduction(highest accuracy). With increasing reduction, the processing speed increases, but at the same time the accuracy of the results also decrease.Typical values are in a range 1..4. The minimum value is 1.
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float: Get or set fraction of template size which accounts for a single object.
The minimum value is 0.5.
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float: Get or set maximum inconsistency.
This value is a threshold (0..1) that specifies the maximum allowed part of the model view to be inconsistent with the point cloud data in order for the hit to be counted. Inconsistency is defined to be point cloud data which is beyond the model. A typical value may be 0.2. It is influenced by precision_threshold.
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float: Get or set maximum occlusion.
This value is a threshold (0..1) that specifies the maximum allowed part of the model view which is occluded by the point cloud data in order for the hit to be counted. Occlusion is defined to be point cloud data lying between the model and the sensor. A typical value may be 0.2. It is influenced by precision_threshold.
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float: Get or set minimum coverage.
This value is a threshold (0..1) that specifies the minimum required coverage of the model view by the point cloud data in order for the hit to be counted. A typical value may be 0.8. It is influenced by precision_threshold.
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float: Get or set minimum score.
This value is a threshold (0..1) that determines whether the candidate is counted as a hit. For this, a hash similarity score between final model view and point cloud data must exceed this limit. A typical value may be 0.8.
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int: Get or set the maximum number of objects to find.
A value of zero means that all objects should be found.
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float: Get or set precision threshold.
This value determines which deviation is considered tolerable, inconsistent or occlusion. The value depends on the quality of the point cloud data. A typical value is 2 mm, the minimum allowed value is 0.
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bool: Get or set the raw results flag.
If this flag is set, candidate locations are considered as hits without further investigation of these candidates. In this case, only parameters hypotheses_threshold, parts_to_find and min_score are decisive for finding objects.