#!/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) )