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csmap-py
![GitHub Release](https://img.shields.io/github/v/release/MIERUNE/csmap-py?label=pip install csmap-py)
module to process CSMap, based on https://www.rinya.maff.go.jp/j/seibi/sagyoudo/attach/pdf/romou-12.pdf
usage: csmap [-h] [--chunk_size CHUNK_SIZE] [--max_workers MAX_WORKERS] [--gf_size GF_SIZE]
[--gf_sigma GF_SIGMA] [--curvature_size CURVATURE_SIZE]
[--height_scale HEIGHT_SCALE HEIGHT_SCALE]
[--slope_scale SLOPE_SCALE SLOPE_SCALE]
[--curvature_scale CURVATURE_SCALE CURVATURE_SCALE]
input_dem_path output_path
positional arguments:
input_dem_path input DEM path
output_path output path
options:
-h, --help show this help message and exit
--chunk_size CHUNK_SIZE
chunk size as pixel, default to 1024
--max_workers MAX_WORKERS
max workers for multiprocessing, default to 1
--gf_size GF_SIZE gaussian filter size, default to 12
--gf_sigma GF_SIGMA gaussian filter sigma, default to 3
--curvature_size CURVATURE_SIZE
curvature filter size, default to 1
--height_scale HEIGHT_SCALE HEIGHT_SCALE
height scale, min max, default to 0.0 1000.0
--slope_scale SLOPE_SCALE SLOPE_SCALE
slope scale, min max, default to 0.0 1.5
--curvature_scale CURVATURE_SCALE CURVATURE_SCALE
curvature scale, min max, default to -0.1 0.1
usage
Command Line Interface
pip install csmap-py
csmap dem.tif csmap.tif
csmap dem.vrt csmap.tif # you can use virtual raster or other gdal supported format
csmap dem.tif csmap.tif --chunk_size 256 --max_workers 4 # you can use multiprocessing
csmap dem.tif csmap.tif --gf_size 3 --gf_sigma 1.0 --curvature_size 1 # you can change filter size
csmap dem.tif csmap.tif --height_scale 0 500 --slope_scale 0 1 --curvature_scale -0.2 0.2 # you can change scale
Python API
from csmap.process import process, CsmapParams
params = CsmapParams() # use default params
# convert dem to csmap
process(
input_dem_path,
output_path,
chunk_size=1024,
params
)
processing image
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