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preprocess_sk.py
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preprocess_sk.py
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# Copyright 2024 - Valeo Comfort and Driving Assistance - valeo.ai
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from tqdm import tqdm
from multiprocessing import Pool
from utils.utils import get_cpu_limit
from preprocess.SemanticKITTIPreprocess import KITTIPreprocessor
if __name__ == "__main__":
SCAN_WINDOW = 40 # Number of frames to aggregate in the clusterization
DOWNSAMPLING_RESOLUTION = [0.05,0.05,0.05,5]
GROUND_METHOD = "patchworkpp"
ds = KITTIPreprocessor(data_dir="datasets/semantickitti/",
scan_window=SCAN_WINDOW,
split='trainval',
downsampling_resolution=DOWNSAMPLING_RESOLUTION,
ground_method=GROUND_METHOD)
num_cpus = get_cpu_limit()
print(f"Using {num_cpus} threads")
with Pool(num_cpus) as p:
list(tqdm(p.imap(ds.__getitem__, range(len(ds))), total=len(ds)))