kopia lustrzana https://github.com/OpenDroneMap/ODM
235 wiersze
7.6 KiB
Python
235 wiersze
7.6 KiB
Python
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#!/usr/bin/env python
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#******************************************************************************
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# $Id$
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#
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# Project: GDAL Python Interface
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# Purpose: Script to merge greyscale as intensity into an RGB(A) image, for
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# instance to apply hillshading to a dem colour relief.
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# Author: Frank Warmerdam, warmerdam@pobox.com
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# Trent Hare (USGS)
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#
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#******************************************************************************
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# Copyright (c) 2009, Frank Warmerdam
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# Copyright (c) 2010, Even Rouault <even dot rouault at mines-paris dot org>
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#
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# Permission is hereby granted, free of charge, to any person obtaining a
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# copy of this software and associated documentation files (the "Software"),
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# to deal in the Software without restriction, including without limitation
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# the rights to use, copy, modify, merge, publish, distribute, sublicense,
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# and/or sell copies of the Software, and to permit persons to whom the
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# Software is furnished to do so, subject to the following conditions:
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#
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# The above copyright notice and this permission notice shall be included
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# in all copies or substantial portions of the Software.
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#
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# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
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# OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
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# THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
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# DEALINGS IN THE SOFTWARE.
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#******************************************************************************
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import sys
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import numpy
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from osgeo import gdal
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# =============================================================================
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# rgb_to_hsv()
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#
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# rgb comes in as [r,g,b] with values in the range [0,255]. The returned
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# hsv values will be with hue and saturation in the range [0,1] and value
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# in the range [0,255]
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#
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def rgb_to_hsv( r,g,b ):
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maxc = numpy.maximum(r,numpy.maximum(g,b))
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minc = numpy.minimum(r,numpy.minimum(g,b))
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v = maxc
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minc_eq_maxc = numpy.equal(minc,maxc)
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# compute the difference, but reset zeros to ones to avoid divide by zeros later.
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ones = numpy.ones((r.shape[0],r.shape[1]))
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maxc_minus_minc = numpy.choose( minc_eq_maxc, (maxc-minc,ones) )
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s = (maxc-minc) / numpy.maximum(ones,maxc)
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rc = (maxc-r) / maxc_minus_minc
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gc = (maxc-g) / maxc_minus_minc
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bc = (maxc-b) / maxc_minus_minc
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maxc_is_r = numpy.equal(maxc,r)
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maxc_is_g = numpy.equal(maxc,g)
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maxc_is_b = numpy.equal(maxc,b)
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h = numpy.zeros((r.shape[0],r.shape[1]))
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h = numpy.choose( maxc_is_b, (h,4.0+gc-rc) )
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h = numpy.choose( maxc_is_g, (h,2.0+rc-bc) )
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h = numpy.choose( maxc_is_r, (h,bc-gc) )
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h = numpy.mod(h/6.0,1.0)
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hsv = numpy.asarray([h,s,v])
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return hsv
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# =============================================================================
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# hsv_to_rgb()
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#
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# hsv comes in as [h,s,v] with hue and saturation in the range [0,1],
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# but value in the range [0,255].
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def hsv_to_rgb( hsv ):
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h = hsv[0]
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s = hsv[1]
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v = hsv[2]
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#if s == 0.0: return v, v, v
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i = (h*6.0).astype(int)
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f = (h*6.0) - i
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p = v*(1.0 - s)
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q = v*(1.0 - s*f)
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t = v*(1.0 - s*(1.0-f))
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r = i.choose( v, q, p, p, t, v )
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g = i.choose( t, v, v, q, p, p )
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b = i.choose( p, p, t, v, v, q )
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rgb = numpy.asarray([r,g,b]).astype(numpy.uint8)
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return rgb
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# =============================================================================
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# Usage()
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def Usage():
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print("""Usage: hsv_merge.py [-q] [-of format] src_color src_greyscale dst_color
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where src_color is a RGB or RGBA dataset,
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src_greyscale is a greyscale dataset (e.g. the result of gdaldem hillshade)
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dst_color will be a RGB or RGBA dataset using the greyscale as the
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intensity for the color dataset.
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""")
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sys.exit(1)
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# =============================================================================
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# Mainline
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# =============================================================================
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argv = gdal.GeneralCmdLineProcessor( sys.argv )
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if argv is None:
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sys.exit( 0 )
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format = 'GTiff'
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src_color_filename = None
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src_greyscale_filename = None
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dst_color_filename = None
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quiet = False
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# Parse command line arguments.
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i = 1
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while i < len(argv):
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arg = argv[i]
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if arg == '-of':
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i = i + 1
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format = argv[i]
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elif arg == '-q' or arg == '-quiet':
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quiet = True
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elif src_color_filename is None:
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src_color_filename = argv[i]
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elif src_greyscale_filename is None:
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src_greyscale_filename = argv[i]
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elif dst_color_filename is None:
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dst_color_filename = argv[i]
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else:
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Usage()
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i = i + 1
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if dst_color_filename is None:
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Usage()
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datatype = gdal.GDT_Byte
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hilldataset = gdal.Open( src_greyscale_filename, gdal.GA_ReadOnly )
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colordataset = gdal.Open( src_color_filename, gdal.GA_ReadOnly )
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#check for 3 or 4 bands in the color file
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if (colordataset.RasterCount != 3 and colordataset.RasterCount != 4):
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print('Source image does not appear to have three or four bands as required.')
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sys.exit(1)
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#define output format, name, size, type and set projection
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out_driver = gdal.GetDriverByName(format)
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outdataset = out_driver.Create(dst_color_filename, colordataset.RasterXSize, \
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colordataset.RasterYSize, colordataset.RasterCount, datatype)
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outdataset.SetProjection(hilldataset.GetProjection())
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outdataset.SetGeoTransform(hilldataset.GetGeoTransform())
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#assign RGB and hillshade bands
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rBand = colordataset.GetRasterBand(1)
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gBand = colordataset.GetRasterBand(2)
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bBand = colordataset.GetRasterBand(3)
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if colordataset.RasterCount == 4:
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aBand = colordataset.GetRasterBand(4)
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else:
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aBand = None
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hillband = hilldataset.GetRasterBand(1)
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hillbandnodatavalue = hillband.GetNoDataValue()
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#check for same file size
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if ((rBand.YSize != hillband.YSize) or (rBand.XSize != hillband.XSize)):
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print('Color and hillshade must be the same size in pixels.')
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sys.exit(1)
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#loop over lines to apply hillshade
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for i in range(hillband.YSize):
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#load RGB and Hillshade arrays
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rScanline = rBand.ReadAsArray(0, i, hillband.XSize, 1, hillband.XSize, 1)
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gScanline = gBand.ReadAsArray(0, i, hillband.XSize, 1, hillband.XSize, 1)
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bScanline = bBand.ReadAsArray(0, i, hillband.XSize, 1, hillband.XSize, 1)
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hillScanline = hillband.ReadAsArray(0, i, hillband.XSize, 1, hillband.XSize, 1)
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#convert to HSV
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hsv = rgb_to_hsv( rScanline, gScanline, bScanline )
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# if there's nodata on the hillband, use the v value from the color
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# dataset instead of the hillshade value.
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if hillbandnodatavalue is not None:
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equal_to_nodata = numpy.equal(hillScanline, hillbandnodatavalue)
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v = numpy.choose(equal_to_nodata,(hillScanline,hsv[2]))
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else:
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v = hillScanline
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#replace v with hillshade
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hsv_adjusted = numpy.asarray( [hsv[0], hsv[1], v] )
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#convert back to RGB
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dst_color = hsv_to_rgb( hsv_adjusted )
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#write out new RGB bands to output one band at a time
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outband = outdataset.GetRasterBand(1)
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outband.WriteArray(dst_color[0], 0, i)
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outband = outdataset.GetRasterBand(2)
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outband.WriteArray(dst_color[1], 0, i)
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outband = outdataset.GetRasterBand(3)
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outband.WriteArray(dst_color[2], 0, i)
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if aBand is not None:
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aScanline = aBand.ReadAsArray(0, i, hillband.XSize, 1, hillband.XSize, 1)
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outband = outdataset.GetRasterBand(4)
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outband.WriteArray(aScanline, 0, i)
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#update progress line
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if not quiet:
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gdal.TermProgress_nocb( (float(i+1) / hillband.YSize) )
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