[pdal] PDAL Python working with an specific dimension (classification)

[Miguel Guerrero]

Hello,
I hope this email finds you well.
First off, thanks for a great job implementing the PDAL for Python.
I have a LiDAR dataset in LAS format that has been pre-classified. I want
to apply some filters to one or multiples classes. I followed the samples
shown on https://pdal.io/stages/filters.html and
https://github.com/PDAL/python. I am able to get the filters to work but
the final output only contains the classes 1 and/or 2, when in reality I
would like to get the rest of the classes that were not used in the
filtering process.
Any direction or suggestion would be greatly appreciated.

My best regards,

Miguel

Here is my code:

import os

# Input and validation of source directory
while True:
    srcDirectory = os.path.normpath(input("Enter directory containing
LAS files: "))
    if os.path.exists(srcDirectory) is True and srcDirectory != ".":
        break
    else:
        print(srcDirectory, "is not a valid directory")

# Input and validation of destination directory
while True:
    dstDirectory = os.path.normpath(input("Enter directory to store
processed files: "))
    if os.path.exists(dstDirectory) is True and dstDirectory != ".":
        break
    else:
        print (dstDirectory, "is not a valid directory")

print ("")

# Change the working directory to the source directory
os.chdir(srcDirectory)
print ("Working directory is" + " " + os.getcwd())

# Blank line for better visualization
print ("")

# Create list of files in source directory
filesList = os.listdir(srcDirectory)

for file in filesList:
    if file.endswith('las'):
        fileIn = (srcDirectory + "\\" + file).replace('\\', '/')
        fileOut = (dstDirectory + "\\" + file).replace('\\', '/')

        json = """
            {
              "pipeline": [
                {
                    "type": "readers.las",
                    "filename": "%s"
                }
              ]
            }"""

        import pdal
        import numpy as np
        pipeline = pdal.Pipeline(json % fileIn)
        count = pipeline.execute()

        arr = pipeline.arrays[0]
        print(len(arr))

        lasClass26 = arr[arr['Classification'] == 26]
        print(len(lasClass26))

        clamp = u"""{
          "pipeline":[
            {
                "type":"filters.csf"
            },
            {
                "type":"filters.range",
                "limits":"Classification[0:30]"
            },
            "%s"
          ]
        }""" % (fileOut)

        p = pdal.Pipeline(clamp, [lasClass26])
        count = p.execute()
        clamped = p.arrays[0]
        print(count)
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