File size: 1,832 Bytes
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import glob
import os
from PIL import Image
import subprocess
import pdb
from osgeo import gdal
# gdal_rasterize -l LSM_Chile_sectors_class_epsg3857 -a class -ts 25729.0 13441.0 -a_nodata 0.0 -te -7663806.3641 -2396313.3772 -7633077.4844 -2380260.4069 -ot Float32 -of GTiff "C:/Dropbox/TUM SIPEO/Projekte/RS mining facilities/L-ASM Mining Dataset/ds/LSM_Chile_sectors_class_epsg3857.geojson" C:/Users/matthias/AppData/Local/Temp/processing_KFVIRc/2f32c9c1db924811af36352bf5f8fdf4/OUTPUT.tif
# creates mask files based on images and geojson file
Image.MAX_IMAGE_PIXELS = 10000000000
path_images = "C:/data/mine-sectors/mapbox_mines_0.8m_RGB/"
path_images = "../../ssd/mine-sector-detection/images/"
path_json = "./"
os.makedirs("./out", exist_ok=True)
# pdb.set_trace()
for file in sorted(glob.glob(path_images + "*.jp2")):
# pdb.set_trace()
ds = gdal.Open(file, gdal.GA_ReadOnly)
geoTransform = ds.GetGeoTransform()
minx = geoTransform[0]
maxy = geoTransform[3]
maxx = minx + geoTransform[1] * ds.RasterXSize
miny = maxy + geoTransform[5] * ds.RasterYSize
data = None
rb = (ds.GetRasterBand(1)).ReadAsArray()
pixelsize = str(rb.shape[1]) + " " + str(rb.shape[0])
print(file)
print([minx, miny, maxx, maxy])
print(pixelsize)
# "-te -7825738.2085 -2675527.0926 -7821399.2129 -2672659.5097 " \
string = "gdal_rasterize -l LSM_Chile_sectors_class_epsg3857 -a class -ts " + pixelsize + \
" -te " + str(minx) + " " + str(miny) + " " + str(maxx) + " " + str(maxy) + " " \
"-ot Byte -of GTiff '" + path_json + "LSM_Chile_sectors_class_epsg3857.geojson' " \
"./out/mask_" + os.path.basename(file)[:-4] + ".tif"
print(string)
# input("press enter")
os.system(string)
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