def add_sicd_from_ortho_helper(kmz_document,
ortho_helper,
inc_image_corners=False,
inc_valid_data=False,
inc_scp=False,
inc_collection_wedge=False,
block_size=10,
dmin=30,
mmult=4):
"""
Adds for a SICD to the provided open kmz from an ortho-rectification helper.
Parameters
----------
kmz_document : Document
ortho_helper : OrthorectificationHelper
inc_image_corners : bool
Include the image corners, if possible?
inc_valid_data : bool
Include the valid image area, if possible?
inc_scp : bool
Include the scp?
inc_collection_wedge : bool
Include the aperture location and collection wedge?
block_size : None|int|float
The block size for the iterator
dmin : int|float
The remap parameters - the default is the high contrast remap value.
mmult : int|float
The remap parameters - the default is the high contrast remap value.
Returns
-------
None
"""
if not isinstance(ortho_helper, OrthorectificationHelper):
raise TypeError(
'ortho_helper must be an OrthorectificationHelper instance, got '
'type {}'.format(type(ortho_helper)))
if not isinstance(kmz_document, Document):
raise TypeError(
'kmz_document must be an sarpy.io.kml.Document instance, got '
'type {}'.format(type(kmz_document)))
# create a folder for these sicd details
sicd = ortho_helper.sicd
folder = kmz_document.add_container(
the_type='Folder',
name=_get_sicd_name(sicd),
description=_get_sicd_description(sicd))
# write the sicd details aside from the overlay
add_sicd_geometry_elements(sicd,
kmz_document,
folder,
inc_image_corners=inc_image_corners,
inc_valid_data=inc_valid_data,
inc_scp=inc_scp,
inc_collection_wedge=inc_collection_wedge)
# create the ortho-rectification iterator
calculator = FullResolutionFetcher(ortho_helper.reader,
index=ortho_helper.index,
dimension=1,
block_size=block_size)
ortho_iterator = OrthorectificationIterator(
ortho_helper, calculator=calculator, dmin=dmin,
mmult=mmult) # use the high contrast remap params
# write the image overlay
_write_sicd_overlay(ortho_iterator, kmz_document, folder)
def create_detected_image_sidd(ortho_helper,
output_directory,
output_file=None,
block_size=10,
dimension=0,
bounds=None,
version=2,
include_sicd=True,
remap_function=None):
"""
Create a SIDD version of a basic detected image from a SICD type reader.
Parameters
----------
ortho_helper : OrthorectificationHelper
The ortho-rectification helper object.
output_directory : str
The output directory for the given file.
output_file : None|str
The file name, this will default to a sensible value.
block_size : int
The approximate processing block size to fetch, given in MB. The
minimum value for use here will be 1.
dimension : int
Which dimension to split over in block processing? Must be either 0 or 1.
bounds : None|numpy.ndarray|list|tuple
The sicd pixel bounds of the form `(min row, max row, min col, max col)`.
This will default to the full image.
version : int
The SIDD version to use, must be one of 1 or 2.
include_sicd : bool
Include the SICD structure in the SIDD file?
remap_function : None|MonochromaticRemap
The applied remap function. If one is not provided, then a default is
used. Required global parameters will be calculated if they are missing,
so the internal state of this remap function may be modified.
Returns
-------
None
Examples
--------
.. code-block:: python
import os
from sarpy.io.complex.converter import open_complex
from sarpy.processing.ortho_rectify import BivariateSplineMethod, NearestNeighborMethod, PGProjection
from sarpy.io.product.sidd_product_creation import create_detected_image_sidd
reader = open_complex('<sicd type object file name>')
ortho_helper = NearestNeighborMethod(reader, index=0)
# create a sidd version 2 file for the whole file
create_detected_image_sidd(ortho_helper, '<output directory>', block_size=10, version=2)
"""
if not os.path.isdir(output_directory):
raise SarpyIOError(
'output_directory {} does not exist or is not a directory'.format(
output_directory))
if not isinstance(ortho_helper, OrthorectificationHelper):
raise TypeError(
'ortho_helper is required to be an instance of OrthorectificationHelper, '
'got type {}'.format(type(ortho_helper)))
if remap_function is None:
remap_function = DEFAULT_IMG_REMAP(override_name='IMG_DEFAULT')
_validate_remap_function(remap_function)
# construct the ortho-rectification iterator - for a basic data fetcher
calculator = FullResolutionFetcher(ortho_helper.reader,
dimension=dimension,
index=ortho_helper.index,
block_size=block_size)
ortho_iterator = OrthorectificationIterator(ortho_helper,
calculator=calculator,
bounds=bounds,
remap_function=remap_function,
recalc_remap_globals=False)
# create the sidd structure
ortho_bounds = ortho_iterator.ortho_bounds
sidd_structure = create_sidd_structure(ortho_helper,
ortho_bounds,
product_class='Detected Image',
pixel_type='MONO{}I'.format(
remap_function.bit_depth),
version=version)
# set suggested name
sidd_structure.NITF[
'SUGGESTED_NAME'] = ortho_helper.sicd.get_suggested_name(
ortho_helper.index) + '_IMG'
# create the sidd writer
full_filename = _validate_filename(output_directory, output_file,
sidd_structure)
writer = SIDDWriter(full_filename, sidd_structure,
ortho_helper.sicd if include_sicd else None)
# iterate and write
for data, start_indices in ortho_iterator:
writer(data, start_indices=start_indices, index=0)
def create_csi_sidd(ortho_helper,
output_directory,
output_file=None,
dimension=0,
block_size=30,
bounds=None,
version=2,
include_sicd=True,
remap_function=None):
"""
Create a SIDD version of a Color Sub-Aperture Image from a SICD type reader.
Parameters
----------
ortho_helper : OrthorectificationHelper
The ortho-rectification helper object.
output_directory : str
The output directory for the given file.
output_file : None|str
The file name, this will default to a sensible value.
dimension : int
The dimension over which to split the sub-aperture.
block_size : int
The approximate processing block size to fetch, given in MB. The
minimum value for use here will be 1.
bounds : None|numpy.ndarray|list|tuple
The sicd pixel bounds of the form `(min row, max row, min col, max col)`.
This will default to the full image.
version : int
The SIDD version to use, must be one of 1 or 2.
include_sicd : bool
Include the SICD structure in the SIDD file?
remap_function : None|MonochromaticRemap
The applied remap function. For csi processing, this must explicitly be
an 8-bit remap. If one is not provided, then a default is used. Required
global parameters will be calculated if they are missing, so the internal
state of this remap function may be modified.
Returns
-------
None
Examples
--------
.. code-block:: python
import os
from sarpy.io.complex.converter import open_complex
from sarpy.io.product.sidd_product_creation import create_csi_sidd
from sarpy.processing.csi import CSICalculator
from sarpy.processing.ortho_rectify import NearestNeighborMethod
reader = open_complex('<sicd type object file name>')
ortho_helper = NearestNeighborMethod(reader, index=0)
create_csi_sidd(ortho_helper, '<output directory>', dimension=0, version=2)
"""
if not os.path.isdir(output_directory):
raise SarpyIOError(
'output_directory {} does not exist or is not a directory'.format(
output_directory))
if not isinstance(ortho_helper, OrthorectificationHelper):
raise TypeError(
'ortho_helper is required to be an instance of OrthorectificationHelper, '
'got type {}'.format(type(ortho_helper)))
# construct the CSI calculator class
csi_calculator = CSICalculator(ortho_helper.reader,
dimension=dimension,
index=ortho_helper.index,
block_size=block_size)
if remap_function is None:
remap_function = DEFAULT_CSI_REMAP(override_name='CSI_DEFAULT',
bit_depth=8)
_validate_remap_function(remap_function)
if remap_function.bit_depth != 8:
raise ValueError(
'The CSI SIDD specifically requires an 8-bit remap function.')
# construct the ortho-rectification iterator
ortho_iterator = OrthorectificationIterator(ortho_helper,
calculator=csi_calculator,
bounds=bounds,
remap_function=remap_function,
recalc_remap_globals=False)
# create the sidd structure
ortho_bounds = ortho_iterator.ortho_bounds
sidd_structure = create_sidd_structure(
ortho_helper,
ortho_bounds,
product_class='Color Subaperture Image',
pixel_type='RGB24I',
version=version)
# set suggested name
sidd_structure.NITF[
'SUGGESTED_NAME'] = csi_calculator.sicd.get_suggested_name(
csi_calculator.index) + '_CSI'
# create the sidd writer
full_filename = _validate_filename(output_directory, output_file,
sidd_structure)
writer = SIDDWriter(full_filename, sidd_structure,
csi_calculator.sicd if include_sicd else None)
# iterate and write
for data, start_indices in ortho_iterator:
writer(data, start_indices=start_indices, index=0)
def create_csi_sidd(ortho_helper,
output_directory,
output_file=None,
dimension=0,
block_size=30,
bounds=None,
version=2):
"""
Create a SIDD version of a Color Sub-Aperture Image from a SICD type reader.
Parameters
----------
ortho_helper : OrthorectificationHelper
The ortho-rectification helper object.
output_directory : str
The output directory for the given file.
output_file : None|str
The file name, this will default to a sensible value.
dimension : int
The dimension over which to split the sub-aperture.
block_size : int
The approximate processing block size to fetch, given in MB. The
minimum value for use here will be 1.
bounds : None|numpy.ndarray|list|tuple
The sicd pixel bounds of the form `(min row, max row, min col, max col)`.
This will default to the full image.
version : int
The SIDD version to use, must be one of 1 or 2.
Returns
-------
None
Examples
--------
.. code-block:: python
import os
from sarpy.io.complex.converter import open_complex
from sarpy.io.product.sidd_product_creation import create_csi_sidd
from sarpy.processing.csi import CSICalculator
from sarpy.processing.ortho_rectify import NearestNeighborMethod
reader = open_complex('<sicd type object file name>')
ortho_helper = NearestNeighborMethod(reader, index=0)
create_csi_sidd(ortho_helper, '<output directory>', dimension=0, version=2)
"""
if not os.path.isdir(output_directory):
raise IOError(
'output_directory {} does not exist or is not a directory'.format(
output_directory))
if not isinstance(ortho_helper, OrthorectificationHelper):
raise TypeError(
'ortho_helper is required to be an instance of OrthorectificationHelper, '
'got type {}'.format(type(ortho_helper)))
# construct the CSI calculator class
csi_calculator = CSICalculator(ortho_helper.reader,
dimension=dimension,
index=ortho_helper.index,
block_size=block_size)
# construct the ortho-rectification iterator
ortho_iterator = OrthorectificationIterator(ortho_helper,
calculator=csi_calculator,
bounds=bounds)
# create the sidd structure
ortho_bounds = ortho_iterator.ortho_bounds
sidd_structure = create_sidd_structure(
ortho_helper,
ortho_bounds,
product_class='Color Subaperture Image',
pixel_type='RGB24I',
version=version)
# set suggested name
sidd_structure._NITF = {
'SUGGESTED_NAME':
csi_calculator.sicd.get_suggested_name(csi_calculator.index) + '_CSI',
}
# create the sidd writer
full_filename = _validate_filename(output_directory, output_file,
sidd_structure)
writer = SIDDWriter(full_filename, sidd_structure, csi_calculator.sicd)
# iterate and write
for data, start_indices in ortho_iterator:
writer(data, start_indices=start_indices, index=0)
def add_sicd_from_ortho_helper(kmz_document,
ortho_helper,
inc_image_corners=False,
inc_valid_data=False,
inc_scp=False,
inc_collection_wedge=False,
block_size=10,
remap_function=None):
"""
Adds for a SICD to the provided open kmz from an ortho-rectification helper.
Parameters
----------
kmz_document : Document
ortho_helper : OrthorectificationHelper
inc_image_corners : bool
Include the image corners, if possible?
inc_valid_data : bool
Include the valid image area, if possible?
inc_scp : bool
Include the scp?
inc_collection_wedge : bool
Include the aperture location and collection wedge?
block_size : None|int|float
The block size for the iterator
remap_function : None|RemapFunction
The remap function to apply, or a suitable default will be chosen.
"""
if not isinstance(ortho_helper, OrthorectificationHelper):
raise TypeError(
'ortho_helper must be an OrthorectificationHelper instance, got '
'type {}'.format(type(ortho_helper)))
if not isinstance(kmz_document, Document):
raise TypeError(
'kmz_document must be an sarpy.io.kml.Document instance, got '
'type {}'.format(type(kmz_document)))
# create a folder for these sicd details
sicd = ortho_helper.sicd
folder = kmz_document.add_container(
the_type='Folder',
name=_get_sicd_name(sicd),
description=_get_sicd_description(sicd))
# write the sicd details aside from the overlay
add_sicd_geometry_elements(sicd,
kmz_document,
folder,
inc_image_corners=inc_image_corners,
inc_valid_data=inc_valid_data,
inc_scp=inc_scp,
inc_collection_wedge=inc_collection_wedge)
# create the ortho-rectification iterator
if remap_function is None:
remap_function = NRL()
calculator = FullResolutionFetcher(ortho_helper.reader,
index=ortho_helper.index,
dimension=1,
block_size=block_size)
ortho_iterator = OrthorectificationIterator(ortho_helper,
calculator=calculator,
remap_function=remap_function,
recalc_remap_globals=True)
# write the image overlay
_write_sicd_overlay(ortho_iterator, kmz_document, folder)
def create_detected_image_sidd(ortho_helper,
output_directory,
output_file=None,
block_size=10,
dimension=0,
bounds=None,
version=2):
"""
Create a SIDD version of a basic detected image from a SICD type reader.
Parameters
----------
ortho_helper : OrthorectificationHelper
The ortho-rectification helper object.
output_directory : str
The output directory for the given file.
output_file : None|str
The file name, this will default to a sensible value.
block_size : int
The approximate processing block size to fetch, given in MB. The
minimum value for use here will be 1.
dimension : int
Which dimension to split over in block processing? Must be either 0 or 1.
bounds : None|numpy.ndarray|list|tuple
The sicd pixel bounds of the form `(min row, max row, min col, max col)`.
This will default to the full image.
version : int
The SIDD version to use, must be one of 1 or 2.
Returns
-------
None
Examples
--------
.. code-block:: python
import logging
logging.basicConfig(level='INFO')
import os
from sarpy.io.complex.converter import open_complex
from sarpy.processing.ortho_rectify import BivariateSplineMethod, NearestNeighborMethod, PGProjection
from sarpy.io.product.sidd_product_creation import create_detected_image_sidd
reader = open_complex('<sicd type object file name>')
ortho_helper = NearestNeighborMethod(reader, index=0)
# create a sidd version 2 file for the whole file
create_detected_image_sidd(ortho_helper, '<output directory>', block_size=10, version=2)
"""
if not os.path.isdir(output_directory):
raise IOError(
'output_directory {} does not exist or is not a directory'.format(
output_directory))
if not isinstance(ortho_helper, OrthorectificationHelper):
raise TypeError(
'ortho_helper is required to be an instance of OrthorectificationHelper, '
'got type {}'.format(type(ortho_helper)))
# construct the ortho-rectification iterator - for a basic data fetcher
calculator = FullResolutionFetcher(ortho_helper.reader,
dimension=dimension,
index=ortho_helper.index,
block_size=block_size)
ortho_iterator = OrthorectificationIterator(ortho_helper,
calculator=calculator,
bounds=bounds)
# create the sidd structure
ortho_bounds = ortho_iterator.ortho_bounds
sidd_structure = create_sidd_structure(ortho_helper,
ortho_bounds,
product_class='Detected Image',
pixel_type='MONO8I',
version=version)
# set suggested name
sidd_structure._NITF = {
'SUGGESTED_NAME':
ortho_helper.sicd.get_suggested_name(ortho_helper.index) + '_IMG',
}
# create the sidd writer
full_filename = _validate_filename(output_directory, output_file,
sidd_structure)
writer = SIDDWriter(full_filename, sidd_structure, ortho_helper.sicd)
# iterate and write
for data, start_indices in ortho_iterator:
writer(data, start_indices=start_indices, index=0)