def __call__(self, src_ds):
dst_ds = create_mem(src_ds.RasterXSize, src_ds.RasterYSize,
1, gdal.GDT_Byte)
if not self.palette_file:
# create a color table as a median of the given dataset
ct = gdal.ColorTable()
gdal.ComputeMedianCutPCT(src_ds.GetRasterBand(1),
src_ds.GetRasterBand(2),
src_ds.GetRasterBand(3),
256, ct)
else:
# copy the color table from the given palette file
pct_ds = gdal.Open(self.palette_file)
pct_ct = pct_ds.GetRasterBand(1).GetRasterColorTable()
if not pct_ct:
raise ValueError("The palette file '%s' does not have a Color "
"Table." % self.palette_file)
ct = pct_ct.Clone()
pct_ds = None
dst_ds.GetRasterBand(1).SetRasterColorTable(ct)
gdal.DitherRGB2PCT(src_ds.GetRasterBand(1),
src_ds.GetRasterBand(2),
src_ds.GetRasterBand(3),
dst_ds.GetRasterBand(1), ct)
copy_projection(src_ds, dst_ds)
copy_metadata(src_ds, dst_ds)
return dst_ds
def __call__(self, src_ds):
# setup
src_sr = osr.SpatialReference()
src_sr.ImportFromWkt(src_ds.GetProjection())
dst_sr = osr.SpatialReference()
dst_sr.ImportFromEPSG(self.srid)
if src_sr.IsSame(dst_sr) and (src_ds.GetGeoTransform()[1] > 0) and (src_ds.GetGeoTransform()[5] < 0):
logger.info(
"Source and destination projection are equal and image "
"is not flipped. Thus, no reprojection is required."
)
return src_ds
# create a temporary dataset to get information about the output size
tmp_ds = gdal.AutoCreateWarpedVRT(src_ds, None, dst_sr.ExportToWkt(), gdal.GRA_Bilinear, 0.125)
# create the output dataset
dst_ds = create_mem(
tmp_ds.RasterXSize, tmp_ds.RasterYSize, src_ds.RasterCount, src_ds.GetRasterBand(1).DataType
)
# reproject the image
dst_ds.SetProjection(dst_sr.ExportToWkt())
dst_ds.SetGeoTransform(tmp_ds.GetGeoTransform())
gdal.ReprojectImage(src_ds, dst_ds, src_sr.ExportToWkt(), dst_sr.ExportToWkt(), gdal.GRA_Bilinear)
tmp_ds = None
# copy the metadata
copy_metadata(src_ds, dst_ds)
return dst_ds
def __call__(self, src_ds):
dst_ds = create_mem(src_ds.RasterXSize, src_ds.RasterYSize, len(self.bands), self.datatype)
dst_range = get_limits(self.datatype)
multiple = 0
for dst_index, (src_index, dmin, dmax) in enumerate(self.bands, 1):
# check if next band is equal
if dst_index < len(self.bands) and (src_index, dmin, dmax) == self.bands[dst_index]:
multiple += 1
continue
# check that src band is available
if src_index > src_ds.RasterCount:
continue
# initialize with zeros if band is 0
if src_index == 0:
src_band = src_ds.GetRasterBand(1)
data = numpy.zeros((src_band.YSize, src_band.XSize), dtype=gdal_array.codes[self.datatype])
src_min, src_max = (0, 0)
# use src_ds band otherwise
else:
src_band = src_ds.GetRasterBand(src_index)
data = src_band.ReadAsArray()
src_min, src_max = src_band.ComputeRasterMinMax()
# get min/max values or calculate from band
if dmin is None:
dmin = get_limits(src_band.DataType)[0]
elif dmin == "min":
dmin = src_min
if dmax is None:
dmax = get_limits(src_band.DataType)[1]
elif dmax == "max":
dmax = src_max
src_range = (float(dmin), float(dmax))
# perform clipping and scaling
data = (dst_range[1] - dst_range[0]) * (
(numpy.clip(data, dmin, dmax) - src_range[0]) / (src_range[1] - src_range[0])
)
# set new datatype
data = data.astype(gdal_array.codes[self.datatype])
# write result
dst_band = dst_ds.GetRasterBand(dst_index)
dst_band.WriteArray(data)
# write equal bands at once
if multiple > 0:
for i in range(multiple):
dst_band = dst_ds.GetRasterBand(dst_index - 1 - i)
dst_band.WriteArray(data)
multiple = 0
copy_projection(src_ds, dst_ds)
copy_metadata(src_ds, dst_ds)
return dst_ds
def _generate_footprint_wkt(self, ds):
""" Generate a fooptrint from a raster, using black/no-data as exclusion
"""
# create an empty boolean array initialized as 'False' to store where
# values exist as a mask array.
nodata_map = numpy.zeros((ds.RasterYSize, ds.RasterXSize),
dtype=numpy.bool)
for idx in range(1, ds.RasterCount + 1):
band = ds.GetRasterBand(idx)
raster_data = band.ReadAsArray()
nodata = band.GetNoDataValue()
if nodata is None:
nodata = 0
# apply the output to the map
nodata_map |= (raster_data != nodata)
# create a temporary in-memory dataset and write the nodata mask
# into its single band
tmp_ds = create_mem(ds.RasterXSize + 2, ds.RasterYSize + 2, 1,
gdal.GDT_Byte)
copy_projection(ds, tmp_ds)
tmp_band = tmp_ds.GetRasterBand(1)
tmp_band.WriteArray(nodata_map.astype(numpy.uint8))
# create an OGR in memory layer to hold the created polygon
sr = osr.SpatialReference(); sr.ImportFromWkt(ds.GetProjectionRef())
ogr_ds = ogr.GetDriverByName('Memory').CreateDataSource('out')
layer = ogr_ds.CreateLayer('poly', sr.sr, ogr.wkbPolygon)
fd = ogr.FieldDefn('DN', ogr.OFTInteger)
layer.CreateField(fd)
# polygonize the mask band and store the result in the OGR layer
gdal.Polygonize(tmp_band, tmp_band, layer, 0)
if layer.GetFeatureCount() != 1:
# if there is more than one polygon, compute the minimum bounding polygon
geometry = ogr.Geometry(ogr.wkbPolygon)
while True:
feature = layer.GetNextFeature()
if not feature: break
geometry = geometry.Union(feature.GetGeometryRef())
# TODO: improve this for a better minimum bounding polygon
geometry = geometry.ConvexHull()
else:
# obtain geometry from the first (and only) layer
feature = layer.GetNextFeature()
geometry = feature.GetGeometryRef()
if geometry.GetGeometryType() != ogr.wkbPolygon:
raise RuntimeError("Error during poligonization. Wrong geometry "
"type.")
# check if reprojection to latlon is necessary
if not sr.IsGeographic():
dst_sr = osr.SpatialReference(); dst_sr.ImportFromEPSG(4326)
try:
geometry.TransformTo(dst_sr.sr)
except RuntimeError:
geometry.Transform(osr.CoordinateTransformation(sr.sr, dst_sr.sr))
gt = ds.GetGeoTransform()
resolution = min(abs(gt[1]), abs(gt[5]))
simplification_value = self.simplification_factor * resolution
# simplify the polygon. the tolerance value is *really* vague
try:
# SimplifyPreserveTopology() available since OGR 1.9.0
geometry = geometry.SimplifyPreserveTopology(simplification_value)
except AttributeError:
# use GeoDjango bindings if OGR is too old
geometry = ogr.CreateGeometryFromWkt(GEOSGeometry(geometry.ExportToWkt()).simplify(simplification_value, True).wkt)
return geometry.ExportToWkt()
def apply(self, src_ds):
# setup
dst_sr = osr.SpatialReference()
gcp_sr = osr.SpatialReference()
dst_sr.ImportFromEPSG(self.srid if self.srid is not None else self.gcp_srid)
gcp_sr.ImportFromEPSG(self.gcp_srid)
logger.debug("Using GCP Projection '%s'" % gcp_sr.ExportToWkt())
logger.debug(
"Applying GCPs: MULTIPOINT(%s) -> MULTIPOINT(%s)"
% (
", ".join([("(%f %f)") % (gcp.GCPX, gcp.GCPY) for gcp in self.gcps]),
", ".join([("(%f %f)") % (gcp.GCPPixel, gcp.GCPLine) for gcp in self.gcps]),
)
)
# set the GCPs
src_ds.SetGCPs(self.gcps, gcp_sr.ExportToWkt())
# Try to find and use the best transform method/order.
# Orders are: -1 (TPS), 3, 2, and 1 (all GCP)
# Loop over the min and max GCP number to order map.
for min_gcpnum, max_gcpnum, order in [(3, None, -1), (10, None, 3), (6, None, 2), (3, None, 1)]:
# if the number of GCP matches
if len(self.gcps) >= min_gcpnum and (max_gcpnum is None or len(self.gcps) <= max_gcpnum):
try:
if order < 0:
# let the reftools suggest the right interpolator
rt_prm = rt.suggest_transformer(src_ds)
else:
# use the polynomial GCP interpolation as requested
rt_prm = {"method": rt.METHOD_GCP, "order": order}
logger.debug(
"Trying order '%i' {method:%s,order:%s}"
% (order, rt.METHOD2STR[rt_prm["method"]], rt_prm["order"])
)
# get the suggested pixel size/geotransform
size_x, size_y, geotransform = rt.suggested_warp_output(
src_ds, None, dst_sr.ExportToWkt(), **rt_prm
)
if size_x > 100000 or size_y > 100000:
raise RuntimeError("Calculated size exceeds limit.")
logger.debug("New size is '%i x %i'" % (size_x, size_y))
# create the output dataset
dst_ds = create_mem(size_x, size_y, src_ds.RasterCount, src_ds.GetRasterBand(1).DataType)
# reproject the image
dst_ds.SetProjection(dst_sr.ExportToWkt())
dst_ds.SetGeoTransform(geotransform)
rt.reproject_image(src_ds, "", dst_ds, "", **rt_prm)
copy_metadata(src_ds, dst_ds)
# retrieve the footprint from the given GCPs
footprint_wkt = rt.get_footprint_wkt(src_ds, **rt_prm)
except RuntimeError, e:
logger.debug("Failed using order '%i'. Error was '%s'." % (order, str(e)))
# the given method was not applicable, use the next one
continue
else:
logger.debug("Successfully used order '%i'" % order)
# the transform method was successful, exit the loop
break
def _generate_footprint_wkt(self, ds):
""" Generate a footprint from a raster, using black/no-data as exclusion
"""
# create an empty boolean array initialized as 'False' to store where
# values exist as a mask array.
nodata_map = numpy.zeros((ds.RasterYSize, ds.RasterXSize),
dtype=numpy.bool)
for idx in range(1, ds.RasterCount + 1):
band = ds.GetRasterBand(idx)
raster_data = band.ReadAsArray()
nodata = band.GetNoDataValue()
if nodata is None:
nodata = 0
# apply the output to the map
nodata_map |= (raster_data != nodata)
# create a temporary in-memory dataset and write the nodata mask
# into its single band
tmp_ds = create_mem(ds.RasterXSize + 2, ds.RasterYSize + 2, 1,
gdal.GDT_Byte)
copy_projection(ds, tmp_ds)
tmp_band = tmp_ds.GetRasterBand(1)
tmp_band.WriteArray(nodata_map.astype(numpy.uint8))
# create an OGR in memory layer to hold the created polygon
sr = osr.SpatialReference()
sr.ImportFromWkt(ds.GetProjectionRef())
ogr_ds = ogr.GetDriverByName('Memory').CreateDataSource('out')
layer = ogr_ds.CreateLayer('poly', sr.sr, ogr.wkbPolygon)
fd = ogr.FieldDefn('DN', ogr.OFTInteger)
layer.CreateField(fd)
# polygonize the mask band and store the result in the OGR layer
gdal.Polygonize(tmp_band, tmp_band, layer, 0)
if layer.GetFeatureCount() > 1:
# if there is more than one polygon, compute the minimum
# bounding polygon
geometry = ogr.Geometry(ogr.wkbPolygon)
while True:
feature = layer.GetNextFeature()
if not feature:
break
geometry = geometry.Union(feature.GetGeometryRef())
# TODO: improve this for a better minimum bounding polygon
geometry = geometry.ConvexHull()
elif layer.GetFeatureCount() < 1:
# there was an error during polygonization
raise RuntimeError("Error during polygonization. No feature "
"obtained.")
else:
# obtain geometry from the first (and only) layer
feature = layer.GetNextFeature()
geometry = feature.GetGeometryRef()
if geometry.GetGeometryType() != ogr.wkbPolygon:
raise RuntimeError("Error during polygonization. Wrong geometry "
"type: %s" % ogr.GeometryTypeToName(
geometry.GetGeometryType()))
# check if reprojection to latlon is necessary
if not sr.IsGeographic():
dst_sr = osr.SpatialReference()
dst_sr.ImportFromEPSG(4326)
try:
geometry.TransformTo(dst_sr.sr)
except RuntimeError:
geometry.Transform(osr.CoordinateTransformation(sr.sr, dst_sr.sr))
gt = ds.GetGeoTransform()
resolution = min(abs(gt[1]), abs(gt[5]))
simplification_value = self.simplification_factor * resolution
# simplify the polygon. the tolerance value is *really* vague
try:
# SimplifyPreserveTopology() available since OGR 1.9.0
geometry = geometry.SimplifyPreserveTopology(simplification_value)
except AttributeError:
# use GeoDjango bindings if OGR is too old
geometry = ogr.CreateGeometryFromWkt(
GEOSGeometry(geometry.ExportToWkt()).simplify(
simplification_value, True
).wkt
)
return geometry.ExportToWkt()
def apply(self, src_ds):
# setup
dst_sr = osr.SpatialReference()
gcp_sr = osr.SpatialReference()
dst_sr.ImportFromEPSG(self.srid if self.srid is not None
else self.gcp_srid)
gcp_sr.ImportFromEPSG(self.gcp_srid)
logger.debug("Using GCP Projection '%s'" % gcp_sr.ExportToWkt())
logger.debug("Applying GCPs: MULTIPOINT(%s) -> MULTIPOINT(%s)"
% (", ".join([("(%f %f)") % (gcp.GCPX, gcp.GCPY) for gcp in self.gcps]) ,
", ".join([("(%f %f)") % (gcp.GCPPixel, gcp.GCPLine) for gcp in self.gcps])))
# set the GCPs
src_ds.SetGCPs(self.gcps, gcp_sr.ExportToWkt())
# Try to find and use the best transform method/order.
# Orders are: -1 (TPS), 3, 2, and 1 (all GCP)
# Loop over the min and max GCP number to order map.
for min_gcpnum, max_gcpnum, order in [(3, None, -1), (10, None, 3), (6, None, 2), (3, None, 1)]:
# if the number of GCP matches
if len(self.gcps) >= min_gcpnum and (max_gcpnum is None or len(self.gcps) <= max_gcpnum):
try:
if ( order < 0 ) :
# let the reftools suggest the right interpolator
rt_prm = rt.suggest_transformer( src_ds )
else:
# use the polynomial GCP interpolation as requested
rt_prm = { "method":rt.METHOD_GCP, "order":order }
logger.debug("Trying order '%i' {method:%s,order:%s}" % \
(order, rt.METHOD2STR[rt_prm["method"]] , rt_prm["order"] ) )
# get the suggested pixel size/geotransform
size_x, size_y, geotransform = rt.suggested_warp_output(
src_ds,
None,
dst_sr.ExportToWkt(),
**rt_prm
)
if size_x > 100000 or size_y > 100000:
raise RuntimeError("Calculated size exceeds limit.")
logger.debug("New size is '%i x %i'" % (size_x, size_y))
# create the output dataset
dst_ds = create_mem(size_x, size_y,
src_ds.RasterCount,
src_ds.GetRasterBand(1).DataType)
# reproject the image
dst_ds.SetProjection(dst_sr.ExportToWkt())
dst_ds.SetGeoTransform(geotransform)
rt.reproject_image(src_ds, "", dst_ds, "", **rt_prm )
copy_metadata(src_ds, dst_ds)
# retrieve the footprint from the given GCPs
footprint_wkt = rt.get_footprint_wkt(src_ds, **rt_prm )
except RuntimeError as e:
logger.debug("Failed using order '%i'. Error was '%s'."
% (order, str(e)))
# the given method was not applicable, use the next one
continue
else:
logger.debug("Successfully used order '%i'" % order)
# the transform method was successful, exit the loop
break
else:
# no method worked, so raise an error
raise GCPTransformException("Could not find a valid transform method.")
# reproject the footprint to a lon/lat projection if necessary
if not gcp_sr.IsGeographic():
out_sr = osr.SpatialReference()
out_sr.ImportFromEPSG(4326)
geom = ogr.CreateGeometryFromWkt(footprint_wkt, gcp_sr)
geom.TransformTo(out_sr)
footprint_wkt = geom.ExportToWkt()
logger.debug("Calculated footprint: '%s'." % footprint_wkt)
return dst_ds, footprint_wkt
def apply(self, src_ds):
# setup
dst_sr = osr.SpatialReference()
dst_sr.ImportFromEPSG(self.srid)
logger.debug("Using internal GCP Projection.")
num_gcps = src_ds.GetGCPCount()
# Try to find and use the best transform method/order.
# Orders are: -1 (TPS), 3, 2, and 1 (all GCP)
# Loop over the min and max GCP number to order map.
for min_gcpnum, max_gcpnum, order in [(3, None, -1), (10, None, 3),
(6, None, 2), (3, None, 1)]:
# if the number of GCP matches
if num_gcps >= min_gcpnum and (max_gcpnum is None
or num_gcps <= max_gcpnum):
try:
if (order < 0):
# let the reftools suggest the right interpolator
rt_prm = reftools.suggest_transformer(src_ds)
else:
# use the polynomial GCP interpolation as requested
rt_prm = {
"method": reftools.METHOD_GCP,
"order": order
}
logger.debug("Trying order '%i' {method:%s,order:%s}" %
(order, reftools.METHOD2STR[rt_prm["method"]],
rt_prm["order"]))
# get the suggested pixel size/geotransform
size_x, size_y, gt = reftools.suggested_warp_output(
src_ds, None, dst_sr.ExportToWkt(), **rt_prm)
if size_x > 100000 or size_y > 100000:
raise RuntimeError("Calculated size exceeds limit.")
logger.debug("New size is '%i x %i'" % (size_x, size_y))
# create the output dataset
dst_ds = create_mem(size_x, size_y, src_ds.RasterCount,
src_ds.GetRasterBand(1).DataType)
# reproject the image
dst_ds.SetProjection(dst_sr.ExportToWkt())
dst_ds.SetGeoTransform(gt)
reftools.reproject_image(src_ds, "", dst_ds, "", **rt_prm)
copy_metadata(src_ds, dst_ds)
# retrieve the footprint from the given GCPs
footprint_wkt = reftools.get_footprint_wkt(
src_ds, **rt_prm)
except RuntimeError, e:
logger.debug("Failed using order '%i'. Error was '%s'." %
(order, str(e)))
# the given method was not applicable, use the next one
continue
else:
logger.debug("Successfully used order '%i'" % order)
# the transform method was successful, exit the loop
break
