From 0a932d4e37b641ac6db38b9c2c06ea4307f0c748 Mon Sep 17 00:00:00 2001
From: Maciej Wielgosz <maciej.wielgosz@nibio.no>
Date: Thu, 13 Jul 2023 15:38:54 +0200
Subject: [PATCH] updated for instance segmentation results
---
utils/las2text_mapper.py | 40 +++++++++++++++++++++-------------------
1 file changed, 21 insertions(+), 19 deletions(-)
diff --git a/utils/las2text_mapper.py b/utils/las2text_mapper.py
index 654ae16..addc948 100755
--- a/utils/las2text_mapper.py
+++ b/utils/las2text_mapper.py
@@ -1,10 +1,13 @@
+import argparse
import glob
import os
-import pandas as pd
+from multiprocessing import Pool
+
+import laspy
import numpy as np
+import pandas as pd
from tqdm import tqdm
-import laspy
-import argparse
+
class Las2TextMapper:
@@ -38,43 +41,42 @@ class Las2TextMapper:
# get label
points = np.hstack((points, las.label[..., None]))
# get treeID
- points = np.hstack((points, las.treeID[..., None]))
+ # points = np.hstack((points, las.treeID[..., None]))
+ points = np.hstack((points, las.instance_nr[..., None]))
# put all together to pandas dataframe
points = pd.DataFrame(
points,
- columns=['x', 'y', 'z', 'red', 'green', 'blue', 'label', 'treeID']
+ columns=['x', 'y', 'z', 'red', 'green', 'blue', 'label', 'instance_nr']
+ # columns=['x', 'y', 'z', 'red', 'green', 'blue', 'label', 'treeID']
)
return points
def process_folder(self):
- """process_folder.
-
- Args:
- mode: train, test or validation
- """
- # read all las files in the folder data_dir using glob
list_of_files = glob.glob(self.data_dir + "/*.las", recursive=False)
# if self.save_dir does not exist, create it
if not os.path.exists(self.save_dir):
os.makedirs(self.save_dir)
- # iterate over all files
- for filepath in tqdm(list_of_files):
- if self.verbose:
- print("Processing file: ", filepath)
+ # process each file in parallel
+ with Pool(8) as p:
+ result = list(tqdm(p.map(self.process_single_file, list_of_files), total=len(list_of_files)))
+
+ def process_single_file(self, filepath):
+ if self.verbose:
+ print("Processing file: ", filepath)
# read the las file
- points = self.read_single_las(filepath)
+ points = self.read_single_las(filepath)
# save the points as text file in self.save_dir
- filepath = filepath.split("/")[-1].split(".")[0]
- filepath = self.save_dir + "/" + filepath
+ filepath = filepath.split("/")[-1].split(".")[0]
+ filepath = os.path.join(self.save_dir, filepath)
# save the points
- points.to_csv(filepath + ".txt", sep=',', index=False, header=True)
+ points.to_csv(filepath + ".txt", sep=',', index=False, header=True)
if __name__ == "__main__":
# use argparse to get the data_dir and save_dir
--
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