#!/usr/bin/env python
# coding: utf8
#
# Copyright (c) 2020 Centre National d'Etudes Spatiales (CNES).
#
# This file is part of CARS
# (see https://github.com/CNES/cars).
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# pylint: disable=too-many-lines
"""
This module is responsible for the filling disparity algorithms:
thus it fills the disparity map with values estimated according to
their neighbourhood.
"""
# Third party imports
import numpy as np
import xarray as xr
# Cars import
from cars.core import constants as cst
[docs]
def add_empty_filling_band(
output_dataset: xr.Dataset,
filling_types: list,
):
"""
Add filling attribute to dataset or band to filling attribute
if it already exists
:param output_dataset: output dataset
:param filling: input mask of filled pixels
:param band_filling: type of filling (zero padding or plane)
"""
nb_band = len(filling_types)
nb_row = len(output_dataset.coords[cst.ROW])
nb_col = len(output_dataset.coords[cst.COL])
filling = np.zeros((nb_band, nb_row, nb_col), dtype=bool)
filling = xr.Dataset(
data_vars={
cst.EPI_FILLING: ([cst.BAND_FILLING, cst.ROW, cst.COL], filling)
},
coords={
cst.BAND_FILLING: filling_types,
cst.ROW: output_dataset.coords[cst.ROW],
cst.COL: output_dataset.coords[cst.COL],
},
)
# Add band to EPI_FILLING attribute or create the attribute
return xr.merge([output_dataset, filling])
[docs]
def update_filling(
output_dataset: xr.Dataset,
filling: np.ndarray = None,
filling_type: str = None,
):
"""
Update filling attribute of dataset with an additional mask
:param output_dataset: output dataset
:param filling: input mask of filled pixels
:param band_filling: type of filling (zero padding or plane)
"""
# Select accurate band of output according to the type of filling
filling_type = {cst.BAND_FILLING: filling_type}
# Add True values from inputmask to output accurate band
filling = filling.astype(bool)
output_dataset[cst.EPI_FILLING].sel(**filling_type).values[filling] = True