100 lines
2.5 KiB
Python
100 lines
2.5 KiB
Python
#!/usr/bin/env python
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# file rasterize-lidar.py
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# author Florent Guiotte <florent.guiotte@irisa.fr>
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# version 0.0
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# date 18 févr. 2021
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"""Create raster of LiDAR features.
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Use npz point clouds from Idefix.
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"""
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import json
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import argparse
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from multiprocessing import Pool
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from tqdm.auto import tqdm
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from pathlib import Path
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import idefix as ix
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parser = argparse.ArgumentParser(description='Compute features rasters from .npz point cloud.',
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formatter_class=argparse.RawDescriptionHelpFormatter,
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epilog="""
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The config file can contain any parameters of the
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idefix.helpers.rasterize function in a json file.
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You can define 'global' parameters (for all the rasters) and raster
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specific parameters in a list 'rasters'.
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See the following `config.json` example file:
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{
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"global": {
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"resolution": 5,
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"interpolation": "idw",
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"out_dir": "./results"
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},
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"rasters": [
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{
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"feature": "elevation",
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"bin_structure": "voxel",
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"bin_method": "mean",
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"squash_method": ["top", "bottom", "std"]
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},
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{
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"feature": "elevation",
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"bin_structure": "pixel",
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"bin_method": "mean"
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},
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{
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"bin_structure": "pixel",
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"bin_method": "density"
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},
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{
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"feature": "num_returns",
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"bin_structure": "pixel",
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"bin_method": "mode"
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}
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]
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}
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""")
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parser.add_argument('-c', '--config', type=str, help='json file to setup the rasterization processes', dest='c')
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parser.add_argument('-n', '--nprocess', type=int, help='number of child processes to use', default=1, dest='n')
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parser.add_argument('in_dir', type=str, help='the path to the point cloud directory')
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parser.add_argument('out_dir', type=str, help='path to output raster results')
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args = parser.parse_args()
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def _map_rasterize(kwargs):
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return ix.helpers.rasterize(**kwargs)
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def main():
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in_dir = Path(args.in_dir)
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out_dir = Path(args.out_dir)
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out_dir.mkdir(exist_ok=True)
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pc_files = list(in_dir.glob('*.npz'))
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config = {'global': {'out_dir': out_dir}}
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config.update(json.load(open(args.c)) if args.c else {})
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globalc = config['global']
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rasters = config['rasters'] if 'rasters' in config else [{}]
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queue = []
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for pc_file in pc_files:
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for raster in rasters:
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job = globalc.copy()
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job.update(raster)
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job.update({'pc_file': pc_file})
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queue += [job]
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pool = Pool(processes=args.n)
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for _ in tqdm(pool.imap_unordered(_map_rasterize, queue), total=len(queue)):
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pass
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if __name__ == '__main__':
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main()
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