def scale_query_to_tile(self, dsquery, dstile):
"""Scales down query dataset to the tile dataset"""
querysize = dsquery.RasterXSize
tilesize = dstile.RasterXSize
tilebands = dstile.RasterCount
if self.options.resampling == 'average':
for i in range(1, tilebands + 1):
res = gdal.RegenerateOverview(dsquery.GetRasterBand(i),
dstile.GetRasterBand(i),
'average')
if res != 0:
self.error("RegenerateOverview() failed")
else:
# 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,
self.resampling)
if res != 0:
self.error("ReprojectImage() failed on %s, error %d" %
(tilefilename, res))
def resample(gdal_raster, epsg_code, output_filename, method='mode', x_res=None, y_res=None, \
output_width=None, output_height=None, output_format="GTiff", output_datatype=gdal.GDT_Float32, \
creation_options=["COMPRESS=LZW"]):
"""
a wrapper around a couple of other boilerplate gdal functions to have a one-off way of
resampling a dataset
"""
input_extent = raster_bbox(
gdal_raster.GetGeoTransform(),
size=[gdal_raster.RasterXSize, gdal_raster.RasterYSize])
out = generate_raster(input_extent,
epsg_code=3338,
output_filename=output_filename,
x_res=x_res,
y_res=y_res,
output_width=output_width,
output_height=output_height,
output_format=output_format,
output_datatype=output_datatype,
creation_options=creation_options)
gdal.RegenerateOverview(gdal_raster.GetRasterBand(1), out.GetRasterBand(1),
method)
out.GetRasterBand(1).ComputeStatistics(0)
out.FlushCache()
return out
def resample_average(path, dsquery, dstile):
for i in range(1, dstile.RasterCount + 1):
res = gdal.RegenerateOverview(dsquery.GetRasterBand(i),
dstile.GetRasterBand(i), "average")
if res != 0:
raise ImageOutputException(
"RegenerateOverview() failed with error %d" % res)
write_method(path, dstile)
def _gdal_resample_raster(self, out_raster, factor):
""" Resample raster using GDAL utility
:param factor:
:return:
"""
with GdalOpen(self.raster_file) as source_ds:
dst_ds = self._gdal_drv.Create(out_raster, self.x_size * factor, self.y_size * factor, 1,
source_ds.GetRasterBand(1).DataType)
resample_geo_transform = (self.x_origin, self.res / factor, 0, self.y_origin, 0, -self.res / factor)
dst_ds.SetGeoTransform(resample_geo_transform)
dst_ds.SetProjection(wkt_from(self.crs))
gdal.RegenerateOverview(source_ds.GetRasterBand(1), dst_ds.GetRasterBand(1), 'mode')
def scale_query_to_tile(self, dsquery, dstile, tilefilename=''):
"""Scales down query dataset to the tile dataset"""
querysize = dsquery.RasterXSize
tilesize = dstile.RasterXSize
tilebands = dstile.RasterCount
# Function: gdal.RegenerateOverview()
for i in range(1, tilebands + 1):
# Black border around NODATA
#if i != 4:
# dsquery.GetRasterBand(i).SetNoDataValue(0)
res = gdal.RegenerateOverview(dsquery.GetRasterBand(i),
dstile.GetRasterBand(i), 'average')
if res != 0:
self.error("RegenerateOverview() failed on %s, error %d" %
(tilefilename, res))
def scaleTile(dsquery, dstile, resampling, tile=''):
querysize = dsquery.RasterXSize
tile_size = dstile.RasterXSize
tilebands = dstile.RasterCount
if 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:
QgsMessageLog.logMessage(
"RegenerateOverview() failed on %s, error %d" %
(tile, res), CATEGORY, Qgis.Info)
elif resampling == 'antialias' and numpy_available:
# 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((tile_size, tile_size), Image.ANTIALIAS)
if os.path.exists(tile):
im0 = Image.open(tile)
im1 = Image.composite(im1, im0, im1)
im1.save(tile, 'PNG')
else:
if resampling == 'near':
gdal_resampling = gdal.GRA_NearestNeighbour
elif resampling == 'bilinear':
gdal_resampling = gdal.GRA_Bilinear
elif resampling == 'cubic':
gdal_resampling = gdal.GRA_Cubic
elif resampling == 'cubicspline':
gdal_resampling = gdal.GRA_CubicSpline
elif resampling == 'lanczos':
gdal_resampling = gdal.GRA_Lanczos
elif resampling == 'mode':
gdal_resampling = gdal.GRA_Mode
elif resampling == 'max':
gdal_resampling = gdal.GRA_Max
elif resampling == 'min':
gdal_resampling = gdal.GRA_Min
elif resampling == 'med':
gdal_resampling = gdal.GRA_Med
elif resampling == 'q1':
gdal_resampling = gdal.GRA_Q1
elif resampling == 'q3':
gdal_resampling = gdal.GRA_Q3
# Other algorithms are implemented by gdal.ReprojectImage().
dsquery.SetGeoTransform((0.0, tile_size / float(querysize), 0.0, 0.0,
0.0, tile_size / 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:
QgsMessageLog.logMessage(
"ReprojectImage() failed on %s, error %d" % (tile, res),
CATEGORY, Qgis.Info)