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Messages - JesseG138

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Hi, Allan!

There was some changes regarding this issue in 2.1.0. Please take a look and tell if there is any problem remain.

Regards, Egor

I have installed the newest version 2.1.0 and ran a ground classification routine and it appears that the issue has been resolved!! Very happy to see this and am upgrading my main processing machine now. Thank you to the team for resolving this issue!!

Workaround for the moment, is to use 1.8.5.
I did it that way.
The Project-Files can be opened in 1.8.5 and 2.X without any compatibility issues.

This is true if you are only processing photogrammtery data BUT if you are combining photogrammetric data with LiDAR data than it is not as compatible. That is the main benefit of version 2+(LiDAR tools) and I am really wishing there was a real fix since the new LiDAR tools in version 2 are extremely useful. Hoping the team can figure this out so I can finially update to a new version. 5 months of working around the issuie has been rough.

Hello all,

Please check, if you are getting expected ground points classification results in version 2.0.2 pre-release (build 16220):

You will see that there's a new parameter - Max. Terrain Slope, set it to 0 value to get results similar to 1.8.4 classification for photogrammetric point clouds.

Hello Alexey,
I have installed the new version 2.0.2 and ran the ground classification routine using the Max Terrain Slope of 0 as instructed. Unfortunately I am still getting similar results as with 2.0.0 and have points incorrectly classified as noise when there is any points above them. In this case even points falling under the power lines are being classified as noise.  Please see the attached image.

Thank you Alexey, I have been very busy in the field but will get this installed and tested early next week and report back with my results.

Thank you for reporting the issue, we are analyzing the problem now.

Hello Alexey, has there been any development on a  resolution for this problem? I am really missing the LiDAR functionality that 2.0 brought with it. Please let me know if there is any way I can help through sharing data sets or anything else. Thank you

Thank you for reporting the issue, we are analyzing the problem now.
Thank you for letting us know Alexey. I am hoping you find a fix for this since version 1.8.5 does not handle large point clouds as well as 2.0.1 does and the added lidar functionality in 2.0 is very valuable to my workflow in combining lidar and photogrammetry derived point clouds. Please let me know if there is anything I can do to help(provide logs, data, etc.)

Thank you for verifying it is not an isolated problem. I am really hoping there is a quick fix for this since version 2.0 seems to handle large point clouds much better than 1.8.5 which was a very welcomed improvement when working with LiDAR and photogrammetry data in the same project.

 A little background... I am a land surveyor in Washington State, USA and I currently use a DJI M300RTK and the P1 camera and L1 LiDAR sensor to survey various types of topography. I have been using Metashape for over 6 years but for one reason or another never set up an account for the forums.

 I noticed an extreme difference in how the automatic ground classification is classifying Low Points(Noise). All points under any other points are being classified as Low Points(Noise), even points that are under trees and building overhangs. This causes lots of problems since we need the ground points to be classified as ground in these areas to reconstruct an accurate 3D model of the terrain. We have large trees on nearly every site we survey so we end up with huge portions of the point cloud classified as noise rather than ground and must then do hours of manual classification to reclassify the noise points into the ground class. The algorithm is also not classifying random points around the point cloud that in previous versions meet the classification tolerances. 

 The automatic "classify points" routine does not do this but is not tweakable and ends up wrongly classifying large portions of the point cloud leading to the need for more manual classification. I also noticed that changing the "Confidence" setting in the classify points dialogue no longer has any effect on the resulting classification. I tried a range from 0.01 to 1.0 and got identical results each time.

Version 1.8.5 does not have this problem with the classify ground points routine and works as it has for all the years past. I have attached screen shots of the ground classification results in version 2.0.0 and from version 1.8.5 for comparison as well as shots from version 2.0.0 showing the results of the "classify points" routine ran with 0.01 confidence and 1.0 confidence settings.

I am hoping there is a fix for this since the added lidar functionality of version 2 is very helpful when working with and combining photo/lidar datasets so I would hate to have to stay in 1.8.5.
Please advise if anyone else is seeing the same thing in the new versions. I have already tried clearing all my settings to defaults which had no effect so I am fairly certain that it has to do with the new classification routine that incorporates the return number for lidar point clouds.

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