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