Segmentation fault during creation of second pass

[EstebanMendez]

Hi,

I get a segfault for a .laz file that I am trying to classify using docker. It looks like it fails during the creation of the second pass.

./pcclassify /data/21A027_628_58_0000.laz ./classified.ply /data/model.bin

I am uncertain if it it is a bug, but rather an older LAS specification version or similar that is causing the issue. You have specified that version 1.4 is required for training - is it the same for pcclassify? If this is the case, do you have any recommendation for conversion. I did try to convert it without any success. The location of the laser data is in the southern part of Sweden.

Please let me know if I need to provide you with any additional information.

Output of lasinfo: Heading '21A027_628_58_0000.laz' with 11317852 points lasinfo (240220) report for '21A027_628_58_0000.laz' reporting all LAS header entries: file signature: 'LASF' file source ID: 0 global_encoding: 1 project ID GUID data 1-4: 00000000-0000-0000-0000-000000000000 version major.minor: 1.2 system identifier: '' generating software: 'LASzip DLL 2.4 r0 (150731)' file creation day/year: 336/2021 header size: 227 offset to point data: 227 number var. length records: 0 point data format: 1 point data record length: 28 number of point records: 11317852 number of points by return: 7718162 1749178 983754 571157 295601 scale factor x y z: 0.01 0.01 0.01 offset x y z: 535000 6715000 0 min x y z: 580000.00 6280000.00 -390.66 max x y z: 582499.99 6282499.99 341.04 LASzip compression (version 2.4r0 c2 50000): POINT10 2 GPSTIME11 2 reporting minimum and maximum for all LAS point record entries ... X 4500000 4749999 Y -43500000 -43250001 Z -39066 34104 intensity 382 65535 return_number 1 5 number_of_returns 1 5 edge_of_flight_line 0 0 scan_direction_flag 0 1 classification 1 18 scan_angle_rank -18 18 user_data 0 0 point_source_ID 13603 13605 gps_time 300525420.164837 300527088.064599 number of first returns: 7718162 number of intermediate returns: 1849949 number of last returns: 7719279 number of single returns: 5969538 overview over number of returns of given pulse: 5969538 1531136 1237623 1102336 1477219 0 0 histogram of classification of points: 4987784 unclassified (1) 6310052 ground (2) 8978 noise (7) 2528 water (9) 8420 bridge deck (17) 90 Reserved for ASPRS Definition (18)

[pierotofy]

Can you share the .laz file? I could try to take a look.

[EstebanMendez]

Sure, here you go: https://www.dropbox.com/scl/fi/x80gaacczqmfyhlj8574j/21A027_628_58_0000.zip?rlkey=kxi6noiaybo7hyd5h4qik1xri&dl=0

If you prefer another delivery method just let me know, I can't upload it as an attachment since the file limit is 25MB. I got the data from the Swedish government, as it is publicly available. The files they are serving are about 50MBs and I suppose it is the unmodified (no lastools etc) version that you want.

Thanks in advance.

[pierotofy]

Seems to be a crash due to the lack of colors in the input.

I've just added https://github.com/uav4geo/OpenPointClass/commit/0f23e58dc08ee6fdc9f6789bbdba9f97487255cd which sets a default color if there are no colors in the input point set. Note that you will likely need to train a new model on non-colored data for it to work.

Try to rebuild/retry? :pray:

[EstebanMendez]

Works like a charm! Thank you very, very much.

A final note on my end is if you have any recommendation with regards to "training a new model on non-colored data"? What I have found so-far are the examples provided in this repository: https://github.com/OpenDroneMap/ODMSemantic3D If the approach in the ODMSemantic3D is the recommended approach, then, how much data would be sufficient and how accurate would I need to be.

Again, thanks a bunch!

[pierotofy]

The consensus with these classifiers is that the more data, the better, although at some point you'll have diminishing returns. Glad it worked!