pdal subsampling implemented

bash_helper_scripts/get_val_corrected.sh

+#!/bin/bash
+
+TARGET_FOLDER=/home/nibio/mutable-outside-world/code/gitlab_fsct/instance_segmentation_classic/maciek
+# clean the folder
+rm -rf $TARGET_FOLDER/*
+
+cp /home/nibio/mutable-outside-world/data/corrected/validation/*.las $TARGET_FOLDER
+

nibio_preprocessing/pdal_subsampling_center_nn.py

+import json
+import pdal
+
+
+class PDALSubsamplingCenterNN:
+    def __init__(self, input_file, output_file, voxel_size):
+        self.input_file = input_file
+        self.output_file = output_file
+        self.voxel_size = voxel_size
+
+    def subsample(self):
+        pipeline = [
+            {
+                "type": "readers.las",
+                "filename": self.input_file,
+            },
+            {
+                "type": "filters.voxelcenternearestneighbor",
+                "cell": self.voxel_size,
+            },
+            {
+                "type": "writers.las",
+                "filename": self.output_file,
+                "extra_dims": "all"
+            },
+        ]
+
+        pipeline = pdal.Pipeline(json.dumps(pipeline))
+        pipeline.execute()
+
+        return pipeline
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nibio_preprocessing/pdal_subsampling_center_nn_folders.py

+import argparse
+import glob
+import json
+import os
+import pdal
+from tqdm import tqdm
+
+import laspy
+
+from nibio_preprocessing.pdal_subsampling_center_nn import PDALSubsamplingCenterNN
+from nibio_postprocessing.attach_labels_to_las_file import AttachLabelsToLasFile
+
+class PDALSubsamplingCenterNNFolders:
+    def __init__(self, input_folder, output_folder, voxel_size, verbose):
+        self.input_folder = input_folder
+        self.output_folder = output_folder
+        self.voxel_size = voxel_size
+        self.verbose = verbose
+
+    def subsample_folders(self):
+        # get all files in the folder
+        input_files = glob.glob(self.input_folder + '/*.las')
+        # print name of files
+        if self.verbose:
+            print("Input files: {}".format(input_files))
+
+        # if output folder does not exist create it
+        if not os.path.isdir(self.output_folder):
+            os.mkdir(self.output_folder)
+
+        # sort the files
+        input_files.sort()
+        # subsample each file
+        for input_file in tqdm(input_files):
+            file_name = os.path.basename(input_file)
+            # create output file path
+            output_file_path = os.path.join(self.output_folder, file_name)
+            # create instance of PDALSubsamplingCenterNN
+            subsample = PDALSubsamplingCenterNN(
+                input_file, output_file_path, self.voxel_size)
+            # subsample
+            subsample.subsample()
+
+    def transfer_extra_fields(self):
+        # transfer extra fields from input to output
+        # get all files in the folder
+        input_files = glob.glob(self.input_folder + '/*.las')
+        output_files = glob.glob(self.output_folder + '/*.las')
+        # print name of files
+        if self.verbose:
+            print("Input files: {}".format(input_files))
+            print("Output files: {}".format(output_files))
+        
+        # sort the files
+        input_files.sort()
+        output_files.sort()
+        
+        # check if the number of input and output files are the same
+        if len(input_files) != len(output_files):
+            raise Exception("Number of input and output files are not the same")
+
+        # read input files and output files one by one using laspy
+        for input_file, output_file in tqdm(zip(input_files, output_files)):
+            # use AttachLabelsToLasFile to transfer extra fields
+            transfer = AttachLabelsToLasFile(
+                gt_las_file_path=input_file,
+                target_las_file_path=output_file,
+                update_las_file_path=output_file,
+                gt_label_name='label',
+                target_label_name='label',
+                verbose=self.verbose
+                )
+            transfer.main()
+
+            # transfer instance segmentation labels
+            transfer = AttachLabelsToLasFile(
+                gt_las_file_path=input_file,
+                target_las_file_path=output_file,
+                update_las_file_path=output_file,
+                gt_label_name='treeID',
+                target_label_name='treeID',
+                verbose=self.verbose
+                )
+            transfer.main()
+
+    def main(self):
+        # subsample
+        self.subsample_folders()
+        # transfer extra fields
+        self.transfer_extra_fields()
+
+        if self.verbose:
+            print("Done subsampling and transferring extra fields")
+
+if __name__ == "__main__":
+    # parse input arguments
+    parser = argparse.ArgumentParser(
+        description='Subsample point cloud with PDAL')
+    parser.add_argument('--input_folder', dest='input_folder',
+                        type=str, help='Input folder', default='./data/')
+    parser.add_argument('--output_folder', dest='output_folder',
+                        type=str, help='Output folder', default='./output_folder')
+    parser.add_argument('--voxel_size', dest='voxel_size',
+                        type=float, help='Voxel size', default=0.02)
+    parser.add_argument('--verbose', dest='verbose',
+                        type=bool, help='Verbose', default=False)
+    args = parser.parse_args()
+
+    # create instance of PDALSubsamplingCenterNNFolders
+    subsample_folders = PDALSubsamplingCenterNNFolders(
+        args.input_folder, args.output_folder, args.voxel_size, True)
+    # subsample
+    subsample_folders.main()
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