Python osgeo.gdal.GRA_Cubic() Examples
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code examples of osgeo.gdal.GRA_Cubic().
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Example #1
Source File: base.py From geoio with MIT License | 5 votes |
def _upsample_from_gdalobj(self,src,dst,method='bilinear'): """Hidden to run the actual reprojection gdal code that is called from two higher level methods.""" # Set reprojection method if isinstance(method,int): pass elif method == "nearest": method = gdal.GRA_NearestNeighbour elif method == "bilinear": method = gdal.GRA_Bilinear elif method == "cubic": method = gdal.GRA_Cubic elif method == "average": method = gdal.GRA_Average else: raise ValueError("requested method is not understood.") # Do the reprojection gdal.ReprojectImage(src, dst, self.meta.projection_string, dst.GetProjection(), method) # Return data and free the temp image. return dst.ReadAsArray()
Example #2
Source File: gdal2tiles.py From gdal2tiles with MIT License | 4 votes |
def scale_query_to_tile(dsquery, dstile, tiledriver, options, tilefilename=''): """Scales down query dataset to the tile dataset""" querysize = dsquery.RasterXSize tilesize = dstile.RasterXSize tilebands = dstile.RasterCount if options.resampling == 'average': # Function: gdal.RegenerateOverview() for i in range(1, tilebands+1): # Black border around NODATA res = gdal.RegenerateOverview(dsquery.GetRasterBand(i), dstile.GetRasterBand(i), 'average') if res != 0: exit_with_error("RegenerateOverview() failed on %s, error %d" % ( tilefilename, res)) elif options.resampling == 'antialias': # Scaling by PIL (Python Imaging Library) - improved Lanczos array = numpy.zeros((querysize, querysize, tilebands), numpy.uint8) for i in range(tilebands): array[:, :, i] = gdalarray.BandReadAsArray(dsquery.GetRasterBand(i+1), 0, 0, querysize, querysize) im = Image.fromarray(array, 'RGBA') # Always four bands im1 = im.resize((tilesize, tilesize), Image.ANTIALIAS) if os.path.exists(tilefilename): im0 = Image.open(tilefilename) im1 = Image.composite(im1, im0, im1) im1.save(tilefilename, tiledriver) else: if options.resampling == 'near': gdal_resampling = gdal.GRA_NearestNeighbour elif options.resampling == 'bilinear': gdal_resampling = gdal.GRA_Bilinear elif options.resampling == 'cubic': gdal_resampling = gdal.GRA_Cubic elif options.resampling == 'cubicspline': gdal_resampling = gdal.GRA_CubicSpline elif options.resampling == 'lanczos': gdal_resampling = gdal.GRA_Lanczos # Other algorithms are implemented by gdal.ReprojectImage(). dsquery.SetGeoTransform((0.0, tilesize / float(querysize), 0.0, 0.0, 0.0, tilesize / float(querysize))) dstile.SetGeoTransform((0.0, 1.0, 0.0, 0.0, 0.0, 1.0)) res = gdal.ReprojectImage(dsquery, dstile, None, None, gdal_resampling) if res != 0: exit_with_error("ReprojectImage() failed on %s, error %d" % (tilefilename, res))
Example #3
Source File: gdal2tiles.py From gdal2tiles with MIT License | 4 votes |
def scale_query_to_tile(dsquery, dstile, tiledriver, options, tilefilename=''): """Scales down query dataset to the tile dataset""" querysize = dsquery.RasterXSize tilesize = dstile.RasterXSize tilebands = dstile.RasterCount if options.resampling == 'average': # Function: gdal.RegenerateOverview() for i in range(1, tilebands + 1): # Black border around NODATA res = gdal.RegenerateOverview(dsquery.GetRasterBand(i), dstile.GetRasterBand(i), 'average') if res != 0: exit_with_error("RegenerateOverview() failed on %s, error %d" % ( tilefilename, res)) elif options.resampling == 'antialias': # Scaling by PIL (Python Imaging Library) - improved Lanczos array = numpy.zeros((querysize, querysize, tilebands), numpy.uint8) for i in range(tilebands): array[:, :, i] = gdalarray.BandReadAsArray(dsquery.GetRasterBand(i + 1), 0, 0, querysize, querysize) im = Image.fromarray(array, 'RGBA') # Always four bands im1 = im.resize((tilesize, tilesize), Image.ANTIALIAS) if os.path.exists(tilefilename): im0 = Image.open(tilefilename) im1 = Image.composite(im1, im0, im1) im1.save(tilefilename, tiledriver) else: if options.resampling == 'near': gdal_resampling = gdal.GRA_NearestNeighbour elif options.resampling == 'bilinear': gdal_resampling = gdal.GRA_Bilinear elif options.resampling == 'cubic': gdal_resampling = gdal.GRA_Cubic elif options.resampling == 'cubicspline': gdal_resampling = gdal.GRA_CubicSpline elif options.resampling == 'lanczos': gdal_resampling = gdal.GRA_Lanczos # Other algorithms are implemented by gdal.ReprojectImage(). dsquery.SetGeoTransform((0.0, tilesize / float(querysize), 0.0, 0.0, 0.0, tilesize / float(querysize))) dstile.SetGeoTransform((0.0, 1.0, 0.0, 0.0, 0.0, 1.0)) res = gdal.ReprojectImage(dsquery, dstile, None, None, gdal_resampling) if res != 0: exit_with_error("ReprojectImage() failed on %s, error %d" % (tilefilename, res))