Segmentation fault on filters.covariancefeatures #3848
Comments
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Indeed, it looks like the OptimalKNN dimension ends up with 0's and the covariance features filter doesn't know how to handle these. Need to investigate why optimal neighborhoods is yielding a 0 and provide better error checking in the covariance filter. |
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A workaround for now would be to use the assign filter to manually override OptimalKNN, e.g., to knn=8, where it is 0. This could be inserted into your pipeline between the two filters @digital-idiot. I have yet to determine why the updated knn and radius values are not being set (something with the entropy calculation, probably resulting in a NaN/inf). One thing we could do would be to at least fix the initialized values of knn and radius here: PDAL/filters/OptimalNeighborhoodFilter.cpp Lines 86 to 87 in 6cb54d8 It would make more sense to bind these to the min_k and distance to the min_kth neighbor. That way, if things fail for some reason, we at least have usable values. |
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@chambbj Thank you for suggesting the workaround, it works well.
Do you have any suggestion how to debug this and pin point which points and why they are causing |
Workflow
filters.optimalneighborhoodfilters.covariancefeaturesPipeline
[ { "filename": "pc_area20.las" }, { "type": "filters.optimalneighborhood", "min_k": 8, "max_k": 50 }, { "type": "filters.covariancefeatures", "knn": 8, "threads": 4, "optimized": true, "feature_set": "Dimensionality" }, { "type": "writers.las", "filename": "test.las", "extra_dims": "all" } ]Encountered behavior
Expected behavior
Pipeline successfully generates processed point cloud or report appropriate error in the input dataset. The pipeline tested to be working till
filters.optimalneighborhoodstage. It fails onfilters.covariancefeaturesstage. Expermented with differentfeature_setbut outcome did not change.Reproduce
System/installation information:
Python environment information
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