Training PointCNN

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03-10-2021 07:43 PM
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LMAllenJacobson
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I am training pointCNN in ArcGIS pro 2.7.1 and Python 3.7.9. I am using synthetic point clouds, which I made using photogrammetry. I can run pointCNN, but it is not classifying points in my test dataset. If I run point.cnn.compute_precision_recall(), it shows that the algorithm converged on one class. 

LMAllenJacobson_0-1615432793912.png

if I change the hyperparameters, I cannot improve the result, I can only switch the result:

LMAllenJacobson_1-1615432964233.png

Does this indicate that pointCNN is not running properly? or that I need more training data?

For reference, here is my script:

LMAllenJacobson_2-1615433441702.png

Also, I'm curious if this problem is related to how I created my training dataset. I created training and validating datasets using the following steps. 1) I segmented the point cloud in CloudCompare and I exported these segments as .LAS. 2)  I imported the .LAS point clouds into ArcGIS pro by creating a LAS dataset and adding the file. 3) I classified all the points in each segment as a single class- I used class 2 and 6 even though I am not using a point cloud that includes buildings and ground. 4) I exported each classified segment using the "Extract Las" function, this gives me a .las and .lasx files. 5) I created a train and val directors, each directory contains 4 files: 1 .las and 1 .lasx for the class 2 and 1.las and 1 .lasx for class 6.

 

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