def array_to_raster_clone(a, proto, xoff=None, yoff=None):
'''
Creates a raster from a given array and a prototype raster dataset, with
optional x- and y-offsets if the array was clipped. Arguments:
a A NumPy array
proto A prototype dataset
xoff The offset in the x-direction; should be provided when clipped
yoff The offset in the y-direction; should be provided when clipped
'''
try:
rast = gdal_array.OpenNumPyArray(a)
except AttributeError:
# For backwards compatibility with older version of GDAL
rast = gdal.Open(gdalnumeric.GetArrayFilename(a))
except:
rast = gdal_array.OpenArray(a)
kwargs = dict()
if xoff is not None and yoff is not None:
kwargs = dict(xoff=xoff, yoff=yoff)
# Copy the projection info and metadata from a prototype dataset
if type(proto) == str:
proto = gdal.Open(proto)
gdalnumeric.CopyDatasetInfo(proto, rast, **kwargs)
return rast
def array_to_raster(a, gt, wkt, xoff=None, yoff=None, dtype=None):
'''
Creates a raster from a given array, with optional x- and y-offsets
if the array was clipped. Arguments:
a A NumPy array
gt A GDAL GeoTransform tuple
wkt Well-Known Text projection
xoff The offset in the x-direction; should be provided when clipped
yoff The offset in the y-direction; should be provided when clipped
dtype The data type to coerce on the array
'''
if dtype is not None:
a = a.astype(dtype)
try:
rast = gdal_array.OpenNumPyArray(a)
except AttributeError:
# For backwards compatibility with older version of GDAL
rast = gdal.Open(gdalnumeric.GetArrayFilename(a))
kwargs = dict()
if xoff is not None and yoff is not None:
kwargs = dict(xoff=xoff, yoff=yoff)
rast.SetGeoTransform(gt)
rast.SetProjection(wkt)
return rast
def array_to_raster(a, gt, wkt, xoff=None, yoff=None, dtype=None):
'''
Creates a raster from a given array, with optional x- and y-offsets
if the array was clipped. Arguments:
a A NumPy array
gt A GDAL GeoTransform tuple
wkt Well-Known Text projection
xoff The offset in the x-direction; should be provided when clipped
yoff The offset in the y-direction; should be provided when clipped
dtype The data type to coerce on the array
'''
if dtype is not None:
a = a.astype(dtype)
try:
rast = gdal_array.OpenNumPyArray(a)
except AttributeError:
# For backwards compatibility with older version of GDAL
rast = gdal.Open(gdalnumeric.GetArrayFilename(a))
except:
rast = gdal_array.OpenArray(a)
rast.SetGeoTransform(gt)
rast.SetProjection(wkt)
if xoff is not None and yoff is not None:
# Bit of a hack; essentially, re-create the raster but with the
# correct X and Y offsets (don't know how to do this without the
# use of CopyDatasetInfo())
return array_to_raster_clone(a, rast, xoff, yoff)
return rast
def process(self, obj_data):
"""
Project data in an image wrapper
@param obj_data: Image wrapper
"""
for index, (label, data) in enumerate(obj_data.getIterator()):
wkt = obj_data.info(label)['WKT']
geotransform = obj_data.info(label)['GeoTransform']
if (self.center_coords.lower() == 'first' and index == 0) or \
self.center_coords.lower() == 'all':
center_lon, center_lat = self._get_center_coords(
wkt, geotransform, data.shape)
ds = gdal_array.OpenNumPyArray(data)
ds.SetGeoTransform(geotransform)
ds.SetProjection(obj_data.info(label)['WKT'])
gdal_dtype = get_gdal_dtype(data.dtype)
reprojected_ds = project_insar_data(ds,
center_lon,
center_lat,
data_type=gdal_dtype)
obj_data.updateData(label, reprojected_ds.ReadAsArray())
obj_data.info(label)['WKT'] = reprojected_ds.GetProjection()
obj_data.info(
label)['GeoTransform'] = reprojected_ds.GetGeoTransform()
def OpenArray(array, prototype_ds=None, xoff=0, yoff=0):
#ds = gdal.Open( gdalnumeric.GetArrayFilename(array) )
ds = gdal_array.OpenNumPyArray(array)
#ds=gdal_array.OpenArray(array)
if ds is not None and prototype_ds is not None:
if type(prototype_ds).__name__ == 'str':
prototype_ds = gdal.Open(prototype_ds)
if prototype_ds is not None:
gdalnumeric.CopyDatasetInfo(prototype_ds, ds, xoff=xoff, yoff=yoff)
return ds
def __init__(self,
array: np.ndarray,
geotransform: GeoTransform,
epsg: Union[int, EPSG],
nodata: float = None):
"""
@param nodata: which value should be no data
"""
self.data = array
self.geotransform = geotransform
self.epsg = epsg
self.nodata = nodata
self.raster = gdal_array.OpenNumPyArray(array, True)
self.raster.SetGeoTransform(geotransform.to_gdal())
srs = osr.SpatialReference()
srs.ImportFromEPSG(epsg)
self.raster.SetSpatialRef(srs)
def array_to_raster_clone(a, proto, xoff=None, yoff=None):
'''
Creates a raster from a given array and a prototype raster dataset, with
optional x- and y-offsets if the array was clipped. Arguments:
a A NumPy array
proto A prototype dataset
xoff The offset in the x-direction; should be provided when clipped
yoff The offset in the y-direction; should be provided when clipped
'''
rast = gdal_array.OpenNumPyArray(a)
kwargs = dict()
if xoff is not None and yoff is not None:
kwargs = dict(xoff=xoff, yoff=yoff)
# Copy the projection info and metadata from a prototype dataset
if type(proto) == str:
proto = gdal.Open(proto)
gdalnumeric.CopyDatasetInfo(proto, rast, **kwargs)
return rast
def process(self, obj_data):
"""
Project data in an image wrapper
@param obj_data: Image wrapper
"""
egmdf = FILEDF([
AutoList([
'http://download.osgeo.org/proj/vdatum/egm96_15/egm96_15.gtx'
])
])
egmdw = egmdf.output()
egmurl, egmfilename = next(egmdw.getIterator())
for index, (label, data) in enumerate(obj_data.getIterator()):
wkt = obj_data.info(label)['WKT']
geotransform = obj_data.info(label)['GeoTransform']
ds = gdal_array.OpenNumPyArray(data)
ds.SetGeoTransform(geotransform)
ds.SetProjection(obj_data.info(label)['WKT'])
gdal_dtype = get_gdal_dtype(data.dtype)
reprojected_ds = georaster_vertical_datum_shift(
georaster=ds,
old_datum_proj4=
'+proj=longlat +datum=WGS84 +no_defs +geoidgrids=' +
egmfilename,
new_datum_proj4='+proj=longlat +datum=WGS84 +no_defs')
obj_data.updateData(label, reprojected_ds.ReadAsArray())
# %%
b_all=np.dstack((im_b4.get_data(),im_b8.get_data(),im.get_data()))
# %%
segments_slic = slic(b_all, n_segments=round(math.sqrt(ma.count(im.get_data()))*1.5), max_iter=100, compactness=0.5, sigma=1, multichannel=True, convert2lab=True, enforce_connectivity=True, min_size_factor=0.03, max_size_factor=5, slic_zero=True)
# %%
segments=Imagee(segments_slic,im.get_metadata())
# %%
segments.export_as_tif('vyrez_segmenty.tif')
# %%
c=np.dstack((b_all,segments.get_data()))
#vectorize segment data
segments_polygons=gdal_array.OpenNumPyArray(segments.get_data(),binterleave=True)
segments_polygons.SetGeoTransform(segments.get_metadata()['affine_transformation'])
segments_polygons.SetProjection(segments.get_metadata()['proj_wkt'])
srs=osr.SpatialReference()
srs.ImportFromWkt(segments.get_metadata()['proj_wkt'])
#outDriver=ogr.GetDriverByName('MEMORY')
outDriver=ogr.GetDriverByName('ESRI Shapefile')
outDataSource=outDriver.CreateDataSource('segments.shp')
outLayer = outDataSource.CreateLayer("data", srs,geom_type=ogr.wkbPolygon)
pixel_value = ogr.FieldDefn("pixel_value", ogr.OFTInteger)
outLayer.CreateField(pixel_value)
gdal.Polygonize( segments_polygons.GetRasterBand(1) , None, outLayer, 0)
# %%
del(outLayer,outDataSource,outDriver)
