diff --git a/bash_helper_scripts/get_val_corrected_single_file.sh b/bash_helper_scripts/get_val_corrected_single_file.sh
new file mode 100755
index 0000000000000000000000000000000000000000..1a3a2a84bc8ca22113a9991526bdf1b73ced855b
--- /dev/null
+++ b/bash_helper_scripts/get_val_corrected_single_file.sh
@@ -0,0 +1,10 @@
+#!/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/Plot89_tile_-25_0.las $TARGET_FOLDER
+
+cp /home/nibio/mutable-outside-world/data/corrected/validation/plot85_tile_-25_0.las $TARGET_FOLDER
+
diff --git a/metrics/instance_segmentation_metrics_austrian.py b/metrics/instance_segmentation_metrics_austrian.py
index a338ca0df00aa7b369716e9c89f3d39e37764f2b..0acfdc6796078e732d89d82b147ae2d251e1b2e6 100644
--- a/metrics/instance_segmentation_metrics_austrian.py
+++ b/metrics/instance_segmentation_metrics_austrian.py
@@ -328,10 +328,7 @@ class InstanceSegmentationMetrics:
# do this if there is at least one label
if metric_dict:
for label in metric_dict.keys():
- print('label: ', label)
for parameter in interesting_parameters:
- print('parameter: ', parameter)
- print('metric_dict[label][parameter]: ', metric_dict[label][parameter])
metric_dict_weighted_by_tree_hight[parameter] += metric_dict[label]['high_of_tree_gt'] * metric_dict[label][parameter]
# divide by the sum of the hights of the trees
for parameter in interesting_parameters:
diff --git a/metrics/instance_segmentation_metrics_in_folder.py b/metrics/instance_segmentation_metrics_in_folder.py
index ccc57c93702e3996b1c5281e5c8ae1d85d458ab8..e9b4eca42a34a3289e5396597dbe3b634cb4b1a5 100644
--- a/metrics/instance_segmentation_metrics_in_folder.py
+++ b/metrics/instance_segmentation_metrics_in_folder.py
@@ -6,7 +6,7 @@ from joblib import Parallel, delayed
import laspy
from metrics.instance_segmentation_metrics import InstanceSegmentationMetrics
-from nibio_postprocessing.attach_labels_to_las_file import AttachLabelsToLasFile
+from nibio_postprocessing.attach_labels_to_las_file_pred2gt import AttachLabelsToLasFilePred2Gt
class InstanceSegmentationMetricsInFolder():
GT_LABEL_NAME = 'treeID'
@@ -160,12 +160,12 @@ class InstanceSegmentationMetricsInFolder():
# create the output folder path
save_to_csv_path = os.path.join(self.output_folder_path, gt_las_file_core_name + '.csv')
# attach labels to the las file
- AttachLabelsToLasFile(
+ AttachLabelsToLasFilePred2Gt(
gt_las_file_path,
target_las_file_path,
update_las_file_path = os.path.join(self.output_folder_path, gt_las_file_core_name + '.las'),
gt_label_name=self.GT_LABEL_NAME,
- target_label_name=self.GT_LABEL_NAME,
+ target_label_name=self.TARGET_LABEL_NAME,
verbose=self.verbose
).main()
diff --git a/nibio_postprocessing/attach_labels_to_las_file.py b/nibio_postprocessing/attach_labels_to_las_file_gt2pred.py
similarity index 97%
rename from nibio_postprocessing/attach_labels_to_las_file.py
rename to nibio_postprocessing/attach_labels_to_las_file_gt2pred.py
index 26de21386d4445313d6bd4d2eaed002a9d61f04e..22191a964af179f74b1fc991465fc96a8d2e07bc 100644
--- a/nibio_postprocessing/attach_labels_to_las_file.py
+++ b/nibio_postprocessing/attach_labels_to_las_file_gt2pred.py
@@ -7,7 +7,7 @@ from sklearn.neighbors import KDTree
import logging
logging.basicConfig(level=logging.INFO)
-class AttachLabelsToLasFile():
+class AttachLabelsToLasFileGt2Pred():
def __init__(
self,
gt_las_file_path,
@@ -109,7 +109,7 @@ if __name__ == '__main__':
args = parser.parse_args()
# create an instance of AttachLabelsToLasFile class
- attach_labels_to_las_file = AttachLabelsToLasFile(
+ attach_labels_to_las_file = AttachLabelsToLasFileGt2Pred(
gt_las_file_path=args.gt_las_file_path,
target_las_file_path=args.target_las_file_path,
update_las_file_path=args.update_las_file_path,
diff --git a/nibio_postprocessing/attach_labels_to_las_file_pred2gt.py b/nibio_postprocessing/attach_labels_to_las_file_pred2gt.py
new file mode 100644
index 0000000000000000000000000000000000000000..5e23dc134a2e5aab5ec927c478dca1e460f24f69
--- /dev/null
+++ b/nibio_postprocessing/attach_labels_to_las_file_pred2gt.py
@@ -0,0 +1,131 @@
+import laspy
+import argparse
+import pandas as pd
+import numpy as np
+from sklearn.neighbors import KDTree
+
+import logging
+logging.basicConfig(level=logging.INFO)
+
+class AttachLabelsToLasFilePred2Gt():
+ def __init__(
+ self,
+ gt_las_file_path,
+ target_las_file_path,
+ update_las_file_path,
+ gt_label_name='gt_label', # 'gt_label'
+ target_label_name='target_label', # 'pred_label'
+ verbose=False
+ ):
+
+ self.gt_las_file_path = gt_las_file_path
+ self.target_las_file_path = target_las_file_path
+ self.update_las_file_path = update_las_file_path
+ self.gt_label_name = gt_label_name
+ self.target_label_name = target_label_name
+ self.verbose = verbose
+
+
+ def attach_labels(self):
+ # read las file
+ gt_las = laspy.read(self.gt_las_file_path)
+ target_las = laspy.read(self.target_las_file_path)
+
+ # read x, y, z and gt_label from gt las file to variables and set a size of sample_size
+ gt = gt_las.xyz
+ target = target_las.xyz
+ gt_label = gt_las[self.gt_label_name]
+
+ # create a tree from target las file
+ tree = KDTree(gt, leaf_size=50, metric='euclidean')
+ # find the nearest neighbor for each point in target las file
+ ind = tree.query(target, k=1, return_distance=False)
+
+ # # map target labels to gt labels
+ # target_labels = gt_label[ind]
+
+ # get point format of target las file
+ point_format = gt_las.point_format
+ # get header of target las file
+ header = gt_las.header
+
+ # create a new las file with the same header as target las file
+ new_header = laspy.LasHeader(point_format=point_format.id, version=header.version)
+ # add gt_label and target_label extra dimensions to the new las file
+ # get extra dimensions from target las file
+ gt_extra_dimensions = list(gt_las.point_format.extra_dimension_names)
+
+ # add extra dimensions to new las file
+ for item in gt_extra_dimensions:
+ new_header.add_extra_dim(laspy.ExtraBytesParams(name=item, type=np.int32))
+
+ # add gt_label and target_label extra dimensions to the new las file
+ new_header.add_extra_dim(laspy.ExtraBytesParams(name=self.target_label_name, type=np.int32))
+
+ new_las = laspy.LasData(new_header)
+
+ # copy x, y, z, gt_label and target_label from target las file to the new las file
+ new_las.x = gt_las.x
+ new_las.y = gt_las.y
+ new_las.z = gt_las.z
+
+ # copy contents of extra dimensions from target las file to the new las file
+ for item in gt_extra_dimensions:
+ new_las[item] = gt_las[item]
+
+ # prepare target labels
+ target_labels = np.empty((gt_label.shape), dtype=np.int32)
+ target_labels[:] = -1 # fill all with -1 (unlabeled), there are more gt labels than target labels
+
+ target_labels[ind] = target_las[self.target_label_name].reshape(-1, 1) # fill with target labels
+ new_las[self.target_label_name] = target_labels
+ # write the new las file
+ new_las.write(self.update_las_file_path)
+
+ def main(self):
+ self.attach_labels(
+ )
+ if self.verbose:
+ # write a report using logging
+ logging.info('gt_las_file_path: {}'.format(self.gt_las_file_path))
+ logging.info('target_las_file_path: {}'.format(self.target_las_file_path))
+ logging.info('update_las_file_path: {}'.format(self.update_las_file_path))
+ logging.info('gt_label_name: {}'.format(self.gt_label_name))
+ logging.info('target_label_name: {}'.format(self.target_label_name))
+
+ # print the size of the las files
+ gt_las = laspy.read(self.gt_las_file_path)
+ target_las = laspy.read(self.target_las_file_path)
+ gt_las_size = gt_las.x.shape[0]
+ target_las_size = target_las.x.shape[0]
+ logging.info('gt_las_size: {}'.format(gt_las_size))
+ logging.info('target_las_size: {}'.format(target_las_size))
+
+
+if __name__ == '__main__':
+ parser = argparse.ArgumentParser('Attach labels to las file')
+ parser.add_argument('--gt_las_file_path', type=str, required=True)
+ parser.add_argument('--target_las_file_path', type=str, required=True)
+ parser.add_argument('--update_las_file_path', type=str, required=True)
+ parser.add_argument('--gt_label_name', type=str, default='gt_label')
+ parser.add_argument('--target_label_name', type=str, default='target_label')
+ parser.add_argument('--verbose', action='store_true', help="Print information about the process")
+ args = parser.parse_args()
+
+ # create an instance of AttachLabelsToLasFile class
+ attach_labels_to_las_file = AttachLabelsToLasFilePred2Gt(
+ gt_las_file_path=args.gt_las_file_path,
+ target_las_file_path=args.target_las_file_path,
+ update_las_file_path=args.update_las_file_path,
+ gt_label_name=args.gt_label_name,
+ target_label_name=args.target_label_name,
+ verbose=args.verbose
+
+ )
+
+ # call main function
+ attach_labels_to_las_file.main()
+
+
+
+
diff --git a/nibio_preprocessing/pdal_subsampling_center_nn_folders.py b/nibio_preprocessing/pdal_subsampling_center_nn_folders.py
index 01ee74b9ec8abb1d6081012c0bb83fc0d4feb63d..877df270ad38988620a394c676bc753cf75199d2 100644
--- a/nibio_preprocessing/pdal_subsampling_center_nn_folders.py
+++ b/nibio_preprocessing/pdal_subsampling_center_nn_folders.py
@@ -8,7 +8,7 @@ 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
+from nibio_postprocessing.attach_labels_to_las_file_gt2pred import AttachLabelsToLasFileGt2Pred
class PDALSubsamplingCenterNNFolders:
def __init__(self, input_folder, output_folder, voxel_size, verbose):
@@ -62,7 +62,7 @@ class PDALSubsamplingCenterNNFolders:
# 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(
+ transfer = AttachLabelsToLasFileGt2Pred(
gt_las_file_path=input_file,
target_las_file_path=output_file,
update_las_file_path=output_file,
@@ -73,7 +73,7 @@ class PDALSubsamplingCenterNNFolders:
transfer.main()
# transfer instance segmentation labels
- transfer = AttachLabelsToLasFile(
+ transfer = AttachLabelsToLasFileGt2Pred(
gt_las_file_path=input_file,
target_las_file_path=output_file,
update_las_file_path=output_file,