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39 lines
1.3 KiB
Python
39 lines
1.3 KiB
Python
from __future__ import division
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import numpy as np
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import rasterio
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import subprocess
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with rasterio.Env(CPL_DEBUG=True):
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# Read raster bands directly to Numpy arrays.
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with rasterio.open('tests/data/RGB.byte.tif') as src:
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r, g, b = src.read()
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# Combine arrays using the 'iadd' ufunc. Expecting that the sum will
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# exceed the 8-bit integer range, initialize it as 16-bit. Adding other
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# arrays to it in-place converts those arrays up and preserves the type
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# of the total array.
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total = np.zeros(r.shape, dtype=rasterio.uint16)
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for band in (r, g, b):
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total += band
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total = total // 3
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# Write the product as a raster band to a new 8-bit file. For keyword
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# arguments, we start with the meta attributes of the source file, but
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# then change the band count to 1, set the dtype to uint8, and specify
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# LZW compression.
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kwargs = src.meta
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kwargs.update(
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dtype=rasterio.uint8,
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count=1,
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compress='lzw')
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with rasterio.open('example-total.tif', 'w', **kwargs) as dst:
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dst.write(total.astype(rasterio.uint8), indexes=1)
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# Dump out gdalinfo's report card and open the image.
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info = subprocess.check_output(
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['gdalinfo', '-stats', 'example-total.tif'])
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print(info)
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subprocess.call(['open', 'example-total.tif'])
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