#!/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.
#
"""
this module contains the abstract matching application class.
"""
import logging
from abc import ABCMeta, abstractmethod
from typing import Dict
from cars.applications.application import Application
from cars.applications.application_template import ApplicationTemplate
[docs]@Application.register("dense_matching")
class DenseMatching(ApplicationTemplate, metaclass=ABCMeta):
"""
AbstractDenseMatching
"""
available_applications: Dict = {}
default_application = "census_sgm_default"
def __new__(cls, conf=None): # pylint: disable=W0613
"""
Return the required application
:raises:
- KeyError when the required application is not registered
:param conf: configuration for matching
:return: a application_to_use object
"""
matching_method = cls.default_application
if bool(conf) is False or "method" not in conf:
logging.info(
"Dense Matching method not specified, "
"default {} is used".format(matching_method)
)
else:
matching_method = conf.get("method", cls.default_application)
if matching_method not in cls.available_applications:
logging.error(
"No matching application named {} registered".format(
matching_method
)
)
raise KeyError(
"No matching application named {} registered".format(
matching_method
)
)
logging.info(
"The AbstractDenseMatching({}) application will be used".format(
matching_method
)
)
return super(DenseMatching, cls).__new__(
cls.available_applications[matching_method]
)
[docs] def __init_subclass__(cls, short_name, **kwargs): # pylint: disable=E0302
super().__init_subclass__(**kwargs)
for name in short_name:
cls.available_applications[name] = cls
def __init__(self, conf=None):
"""
Init function of DenseMatching
:param conf: configuration
:return: an application_to_use object
"""
super().__init__(conf=conf)
[docs] @abstractmethod
def get_optimal_tile_size(self, disp_range_grid, max_ram_per_worker):
"""
Get the optimal tile size to use during dense matching.
:param disp_range_grid: minimum and maximum disparity grid
:param max_ram_per_worker: maximum ram per worker
:return: optimal tile size
"""
[docs] @abstractmethod
def get_margins_fun(self, grid_left, disp_range_grid):
"""
Get Margins function that generates margins needed by
matching method, to use during resampling
:param grid_left: left epipolar grid
:param disp_range_grid: minimum and maximum disparity grid
:return: function that generates margin for given roi
"""
[docs] @abstractmethod
def generate_disparity_grids(
self,
sensor_image_right,
grid_right,
geometry_plugin_with_dem_min,
geometry_plugin_with_dem_max,
geom_plugin_with_dem_and_geoid,
dmin=None,
dmax=None,
altitude_delta_min=None,
altitude_delta_max=None,
dem_min=None,
dem_max=None,
pair_folder=None,
loc_inverse_orchestrator=None,
):
"""
Generate disparity grids min and max, with given step
global mode: uses dmin and dmax
local mode: uses dems
:param sensor_image_right: sensor image
:type sensor_image_right: dict
:param grid_right: right epipolar grid
:type grid_right: CarsDataset
:param geometry_plugin_with_dem_min: geometry plugin with dem min
:type geometry_plugin_with_dem_min: GeometryPlugin
:param geometry_plugin_with_dem_max: geometry plugin with dem max
:type geometry_plugin_with_dem_max: GeometryPlugin
:param geom_plugin_with_dem_and_geoid: geometry plugin with dem mean
used to generate epipolar grids
:type geom_plugin_with_dem_and_geoid: GeometryPlugin
:param dmin: minimum disparity
:type dmin: float
:param dmax: maximum disparity
:type dmax: float
:param altitude_delta_max: Delta max of altitude
:type altitude_delta_max: int
:param altitude_delta_min: Delta min of altitude
:type altitude_delta_min: int
:param dem_min: path to minimum dem
:type dem_min: str
:param dem_max: path to maximum dem
:type dem_max: str
:param pair_folder: folder used for current pair
:type pair_folder: str
:param loc_inverse_orchestrator: orchestrator to perform inverse locs
:type loc_inverse_orchestrator: Orchestrator
:return disparity grid range, containing grid min and max
:rtype: CarsDataset
"""
[docs] @abstractmethod
def run(
self,
epipolar_images_left,
epipolar_images_right,
local_tile_optimal_size_fun,
orchestrator=None,
pair_folder=None,
pair_key="PAIR_0",
disp_range_grid=None,
compute_disparity_masks=False,
disp_to_alt_ratio=None,
margins_to_keep=0,
):
"""
Run Matching application.
Create CarsDataset filled with xarray.Dataset, corresponding
to epipolar disparities, on the same geometry than
epipolar_images_left.
:param epipolar_images_left: tiled left epipolar CarsDataset contains:
- N x M Delayed tiles. \
Each tile will be a future xarray Dataset containing:
- data with keys : "im", "msk", "color"
- attrs with keys: "margins" with "disp_min" and "disp_max"\
"transform", "crs", "valid_pixels", "no_data_mask",\
"no_data_img"
- attributes containing:
"largest_epipolar_region","opt_epipolar_tile_size"
:type epipolar_images_left: CarsDataset
:param epipolar_images_right: tiled right epipolar CarsDataset contains:
- N x M Delayed tiles. \
Each tile will be a future xarray Dataset containing:
- data with keys : "im", "msk", "color"
- attrs with keys: "margins" with "disp_min" and "disp_max"
"transform", "crs", "valid_pixels", "no_data_mask",
"no_data_img"
- attributes containing:
"largest_epipolar_region","opt_epipolar_tile_size"
:type epipolar_images_right: CarsDataset
:param local_tile_optimal_size_fun: function to compute local
optimal tile size
:type local_tile_optimal_size_fun: func
:param orchestrator: orchestrator used
:param pair_folder: folder used for current pair
:type pair_folder: str
:param pair_key: pair id
:type pair_key: str
:param disp_range_grid: minimum and maximum disparity grid
:type disp_range_grid: CarsDataset
:param disp_to_alt_ratio: disp to alti ratio used for performance map
:type disp_to_alt_ratio: float
:param margins_to_keep: margin to keep after dense matching
:type margins_to_keep: int
:return: disparity map: \
The CarsDataset contains:
- N x M Delayed tiles.\
Each tile will be a future xarray Dataset containing:
- data with keys : "disp", "disp_msk"
- attrs with keys: profile, window, overlaps
- attributes containing:
"largest_epipolar_region","opt_epipolar_tile_size",
"disp_min_tiling", "disp_max_tiling"
:rtype: CarsDataset
"""