From cd8404f0404b842328a1245ac67bf76f3f1d45f3 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Alice=20de=20Bardonn=C3=A8che-Richard?= Date: Wed, 3 Jan 2024 16:12:29 +0100 Subject: [PATCH 01/14] feat: add phase_cross_correlation step --- .../an_estimation_pipeline.json | 31 ++++ pandora2d/__init__.py | 22 ++- pandora2d/check_configuration.py | 45 +++-- pandora2d/estimation/__init__.py | 28 ++++ pandora2d/estimation/estimation.py | 155 ++++++++++++++++++ .../estimation/phase_cross_correlation.py | 140 ++++++++++++++++ pandora2d/img_tools.py | 11 +- pandora2d/state_machine.py | 71 +++++++- setup.cfg | 2 + 9 files changed, 476 insertions(+), 29 deletions(-) create mode 100644 data_samples/json_conf_files/an_estimation_pipeline.json create mode 100644 pandora2d/estimation/__init__.py create mode 100644 pandora2d/estimation/estimation.py create mode 100644 pandora2d/estimation/phase_cross_correlation.py diff --git a/data_samples/json_conf_files/an_estimation_pipeline.json b/data_samples/json_conf_files/an_estimation_pipeline.json new file mode 100644 index 0000000..1b027fd --- /dev/null +++ b/data_samples/json_conf_files/an_estimation_pipeline.json @@ -0,0 +1,31 @@ +{ + "input": { + "left": { + "img": "./maricopa/left.tif", + "nodata": -9999 + }, + "right": { + "img": "./maricopa/right.tif", + "nodata": -9999 + } + }, + "pipeline": { + "estimation": { + "estimation_method": "phase_cross_correlation", + "range_row": 5, + "range_col": 5, + "sample_factor": 100 + }, + "matching_cost": { + "matching_cost_method": "zncc", + "window_size": 5 + }, + "disparity": { + "disparity_method": "wta", + "invalid_disparity": "NaN" + }, + "refinement": { + "refinement_method": "interpolation" + } + } +} diff --git a/pandora2d/__init__.py b/pandora2d/__init__.py index a8ef1d0..fde98e8 100644 --- a/pandora2d/__init__.py +++ b/pandora2d/__init__.py @@ -2,6 +2,7 @@ # coding: utf8 # # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). +# Copyright (c) 2024 CS GROUP France # # This file is part of PANDORA2D # @@ -23,15 +24,15 @@ This module contains functions to run Pandora pipeline. """ -from typing import Dict, List -import xarray as xr +from typing import Dict +import xarray as xr from pandora import read_config_file, setup_logging from pandora.common import save_config from pandora2d import common from pandora2d.check_configuration import check_conf, check_datasets -from pandora2d.img_tools import get_roi_processing, create_datasets_from_inputs +from pandora2d.img_tools import create_datasets_from_inputs, get_roi_processing from pandora2d.state_machine import Pandora2DMachine @@ -69,7 +70,7 @@ def run( pandora2d_machine.run_exit() - return pandora2d_machine.dataset_disp_maps + return pandora2d_machine.dataset_disp_maps, pandora2d_machine.completed_cfg def main(cfg_path: str, path_output: str, verbose: bool) -> None: @@ -103,15 +104,18 @@ def main(cfg_path: str, path_output: str, verbose: bool) -> None: roi = get_roi_processing(cfg["ROI"], col_disparity, row_disparity) # read images - image_datasets = create_datasets_from_inputs(input_config=cfg["input"], roi=roi) + image_datasets = create_datasets_from_inputs( + input_config=cfg["input"], roi=roi, estimation_cfg=cfg["pipeline"].get("estimation") + ) # check datasets: shape, format and content check_datasets(image_datasets.left, image_datasets.right) # run pandora 2D and store disp maps in a dataset - dataset_disp_maps = run(pandora2d_machine, image_datasets.left, image_datasets.right, cfg) + dataset_disp_maps, completed_cfg = run(pandora2d_machine, image_datasets.left, image_datasets.right, cfg) - # save dataset - common.save_dataset(dataset_disp_maps, path_output) + # save dataset if not empty + if bool(dataset_disp_maps.data_vars): + common.save_dataset(dataset_disp_maps, path_output) # save config - save_config(path_output, user_cfg) + save_config(path_output, completed_cfg) diff --git a/pandora2d/check_configuration.py b/pandora2d/check_configuration.py index de0c08a..c0b320c 100644 --- a/pandora2d/check_configuration.py +++ b/pandora2d/check_configuration.py @@ -2,6 +2,7 @@ # coding: utf8 # # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). +# Copyright (c) 2024 CS GROUP France # # This file is part of PANDORA2D # @@ -22,14 +23,21 @@ """ This module contains functions allowing to check the configuration given to Pandora pipeline. """ -from typing import Dict -import xarray as xr -from json_checker import Checker, Or, And -import numpy as np -from pandora.check_configuration import check_disparities_from_input, check_images, get_config_input, check_dataset -from pandora.check_configuration import concat_conf, update_conf, rasterio_can_open_mandatory +from typing import Dict +import numpy as np +import xarray as xr +from json_checker import And, Checker, Or +from pandora.check_configuration import ( + check_dataset, + check_disparities_from_input, + check_images, + concat_conf, + get_config_input, + rasterio_can_open_mandatory, + update_conf, +) from pandora2d.state_machine import Pandora2DMachine @@ -58,12 +66,14 @@ def check_datasets(left: xr.Dataset, right: xr.Dataset) -> None: raise ValueError("left and right datasets must have the same shape") -def check_input_section(user_cfg: Dict[str, dict]) -> Dict[str, dict]: +def check_input_section(user_cfg: Dict[str, dict], estimation_config: dict = None) -> Dict[str, dict]: """ Complete and check if the dictionary is correct :param user_cfg: user configuration :type user_cfg: dict + :param estimation_config: get estimation config if in user_config + :type estimation_config: dict :return: cfg: global configuration :rtype: cfg: dict """ @@ -71,6 +81,14 @@ def check_input_section(user_cfg: Dict[str, dict]) -> Dict[str, dict]: # Add missing steps and inputs defaults values in user_cfg cfg = update_conf(default_short_configuration_input, user_cfg) + # test disparities + if estimation_config is None: + check_disparities_from_input(cfg["input"]["col_disparity"], None) + check_disparities_from_input(cfg["input"]["row_disparity"], None) + else: + # add wrong disparity for checking only + cfg = update_conf(default_configuration_disp, user_cfg) + # check schema configuration_schema = {"input": input_configuration_schema} checker = Checker(configuration_schema) @@ -79,10 +97,6 @@ def check_input_section(user_cfg: Dict[str, dict]) -> Dict[str, dict]: # test images check_images(cfg["input"]) - # test disparities - check_disparities_from_input(cfg["input"]["col_disparity"], None) - check_disparities_from_input(cfg["input"]["row_disparity"], None) - return cfg @@ -158,7 +172,7 @@ def check_conf(user_cfg: Dict, pandora2d_machine: Pandora2DMachine) -> dict: # check input user_cfg_input = get_config_input(user_cfg) - cfg_input = check_input_section(user_cfg_input) + cfg_input = check_input_section(user_cfg_input, user_cfg["pipeline"].get("estimation")) user_cfg_roi = get_roi_config(user_cfg) cfg_roi = check_roi_section(user_cfg_roi) @@ -166,7 +180,9 @@ def check_conf(user_cfg: Dict, pandora2d_machine: Pandora2DMachine) -> dict: # check pipeline cfg_pipeline = check_pipeline_section(user_cfg, pandora2d_machine) - check_right_nodata_condition(cfg_input, cfg_pipeline) + # The estimation step can be utilized independently. + if "matching_cost" in cfg_pipeline["pipeline"]: + check_right_nodata_condition(cfg_input, cfg_pipeline) cfg = concat_conf([cfg_input, cfg_roi, cfg_pipeline]) @@ -181,6 +197,7 @@ def check_right_nodata_condition(cfg_input: Dict, cfg_pipeline: Dict) -> None: :param cfg_pipeline: pipeline section of configuration :type cfg_pipeline: Dict """ + if not isinstance(cfg_input["input"]["right"]["nodata"], int) and cfg_pipeline["pipeline"]["matching_cost"][ "matching_cost_method" ] in ["sad", "ssd"]: @@ -244,6 +261,8 @@ def get_roi_config(user_cfg: Dict[str, dict]) -> Dict[str, dict]: } } +default_configuration_disp = {"input": {"col_disparity": [-9999, -9999], "row_disparity": [-9999, -9999]}} + roi_configuration_schema = { "row": {"first": And(int, lambda x: x >= 0), "last": And(int, lambda x: x >= 0)}, "col": {"first": And(int, lambda x: x >= 0), "last": And(int, lambda x: x >= 0)}, diff --git a/pandora2d/estimation/__init__.py b/pandora2d/estimation/__init__.py new file mode 100644 index 0000000..bf8cbec --- /dev/null +++ b/pandora2d/estimation/__init__.py @@ -0,0 +1,28 @@ +#!/usr/bin/env python +# coding: utf8 +# +# Copyright (c) 2024 Centre National d'Etudes Spatiales (CNES). +# Copyright (c) 2024 CS GROUP France +# +# This file is part of PANDORA2D +# +# https://github.com/CNES/Pandora2D +# +# 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. +# +""" +Init file for estimation module +""" + +from . import phase_cross_correlation +from .estimation import AbstractEstimation diff --git a/pandora2d/estimation/estimation.py b/pandora2d/estimation/estimation.py new file mode 100644 index 0000000..78ae201 --- /dev/null +++ b/pandora2d/estimation/estimation.py @@ -0,0 +1,155 @@ +#!/usr/bin/env python +# coding: utf8 +# +# Copyright (c) 2024 Centre National d'Etudes Spatiales (CNES). +# Copyright (c) 2024 CS GROUP France +# +# This file is part of PANDORA2D +# +# https://github.com/CNES/Pandora2D +# +# 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 functions associated to the estimation computation step. +""" +from __future__ import annotations + +import logging +from abc import ABCMeta, abstractmethod +from typing import Dict, Tuple + +import numpy as np +import xarray as xr + + +class AbstractEstimation: + """ + Abstract Estimation class + """ + + __metaclass__ = ABCMeta + + estimation_methods_avail: Dict = {} + _estimation_method = None + cfg = None + + def __new__(cls, cfg: dict | None = None): + """ + Return the plugin associated with the estimation_method given in the configuration + + :param cfg: configuration {'estimation_method': value} + :type cfg: dictionary + """ + if cls is AbstractEstimation: + if isinstance(cfg["estimation_method"], str): + try: + return super(AbstractEstimation, cls).__new__( + cls.estimation_methods_avail[cfg["estimation_method"]] + ) + except KeyError: + logging.error("No estimation method named % supported", cfg["estimation_method"]) + raise KeyError + else: + if isinstance(cfg["estimation_method"], unicode): # type: ignore # pylint: disable=undefined-variable + # creating a plugin from registered short name given as unicode (py2 & 3 compatibility) + try: + return super(AbstractEstimation, cls).__new__( + cls.estimation_methods_avail[cfg["estimation_method"].encode("utf-8")] + ) + except KeyError: + logging.error( + "No estimation method named % supported", + cfg["estimation_method"], + ) + raise KeyError + else: + return super(AbstractEstimation, cls).__new__(cls) + return None + + @classmethod + def register_subclass(cls, short_name: str): + """ + Allows to register the subclass with its short name + + :param short_name: the subclass to be registered + :type short_name: string + """ + + def decorator(subclass): + """ + Registers the subclass in the available methods + + :param subclass: the subclass to be registered + :type subclass: object + """ + cls.estimation_methods_avail[short_name] = subclass + return subclass + + return decorator + + def desc(self) -> None: + """ + Describes the estimation method + :return: None + """ + print(f"{self._estimation_method} estimation measure") + + @abstractmethod + def compute_estimation(self, img_left: xr.Dataset, img_right: xr.Dataset) -> Tuple[list, list, np.ndarray, dict]: + """ + Compute the phase cross correlation method + + :param img_left: xarray.Dataset containing : + - im : 2D (row, col) xarray.DataArray + :type img_left: xr.Dataset + :param img_right: xarray.Dataset containing : + - im : 2D (row, col) xarray.DataArray + :type img_right: xr.Dataset + :return:row disparity: list + col disparity: list + Calculated shifts: list + Extra information about estimation : dict + :rtype: list, list, np.ndarray, dict + """ + + @staticmethod + def update_cfg_with_estimation( + cfg: Dict, disp_col: list, disp_row: list, shifts: np.ndarray, extra_dict: dict = None + ) -> Dict: + """ + Save calculated shifts in a configuration dictionary + + :param cfg: user configuration + :type cfg: dict + :param disp_col: list of min and max disparity in column + :type disp_col: [int, int] + :param disp_row: list of min and max disparity in row + :type disp_row: [int, int] + :param shifts: computed global shifts between left and right + :type shifts: [np.float32, np.float32] + :param extra_dict: Dictionary containing extra information about estimation + :type extra_dict: dict + :return: cfg: global configuration + :rtype: cfg: dict + """ + + cfg["input"]["col_disparity"] = disp_col + cfg["input"]["row_disparity"] = disp_row + + cfg["pipeline"]["estimation"]["estimated_shifts"] = shifts.tolist() + if extra_dict is not None: + for key, value in extra_dict.items(): + cfg["pipeline"]["estimation"][key] = value + + return cfg diff --git a/pandora2d/estimation/phase_cross_correlation.py b/pandora2d/estimation/phase_cross_correlation.py new file mode 100644 index 0000000..f74dfc9 --- /dev/null +++ b/pandora2d/estimation/phase_cross_correlation.py @@ -0,0 +1,140 @@ +#!/usr/bin/env python +# coding: utf8 +# +# Copyright (c) 2024 Centre National d'Etudes Spatiales (CNES). +# Copyright (c) 2024 CS GROUP France +# +# This file is part of PANDORA2D +# +# https://github.com/CNES/Pandora2D +# +# 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 functions associated to the phase cross correlation method used in the estimation step. +""" + +import logging +from typing import Dict, Tuple + +import numpy as np +import xarray as xr +from json_checker import And, Checker +from skimage.registration import phase_cross_correlation + +from . import estimation + + +@estimation.AbstractEstimation.register_subclass("phase_cross_correlation") +class PhaseCrossCorrelation(estimation.AbstractEstimation): + """ + PhaseCrossCorrelation class allows to perform estimation + """ + + _range_col = None + _range_row = None + _sample_factor = None + + # Default configuration, do not change these values + _RANGE_COL = 5 + _RANGE_ROW = 5 + _SAMPLE_FACTOR = 1 + + def __init__(self, cfg: Dict) -> None: + """ + :param cfg: optional configuration, {'range_col': int, 'range_row': int, 'sample_factor': int} + :type cfg: dict + :return: None + """ + + self.cfg = self.check_conf(cfg) + self._range_col = self.cfg["range_col"] + self._range_row = self.cfg["range_row"] + self._sample_factor = self.cfg["sample_factor"] + self._estimation_method = self.cfg["estimation_method"] + + def check_conf(self, cfg: Dict) -> Dict: + """ + Check the estimation configuration + + :param cfg: user_config for refinement + :type cfg: dict + :return: cfg: global configuration + :rtype: cfg: dict + """ + + # Give the default value if the required element is not in the conf + if "range_col" not in cfg: + cfg["range_col"] = self._RANGE_COL + + if "range_row" not in cfg: + cfg["range_row"] = self._RANGE_ROW + + if "sample_factor" not in cfg: + cfg["sample_factor"] = self._SAMPLE_FACTOR + + # Estimation schema config + schema = { + "estimation_method": And(str, lambda estimation_method: estimation_method in ["phase_cross_correlation"]), + "range_col": And(int, lambda range_col: range_col > 2), + "range_row": And(int, lambda range_row: range_row > 2), + "sample_factor": And(int, lambda sf: sf % 10 == 0 or sf == 1, lambda sf: sf > 0), + } + + checker = Checker(schema) + checker.validate(cfg) + + return cfg + + def compute_estimation(self, img_left: xr.Dataset, img_right: xr.Dataset) -> Tuple[list, list, np.ndarray, dict]: + """ + Compute the phase cross correlation method + + :param img_left: xarray.Dataset containing : + - im : 2D (row, col) xarray.DataArray + :type img_left: xr.Dataset + :param img_right: xarray.Dataset containing : + - im : 2D (row, col) xarray.DataArray + :type img_right: xr.Dataset + :return: row disparity: list + col disparity: list + Calculated shifts: np.ndarray + Extra information about estimation: dict + :rtype: list, list, np.ndarray, dict + """ + + # https://scikit-image.org/docs/stable/api/ + # skimage.registration.html#skimage.registration.phase_cross_correlation + shifts, error, phasediff = phase_cross_correlation( + img_left["im"].data, img_right["im"].data, upsample_factor=self._sample_factor + ) + + # reformat outputs + phasediff = "{:.{}e}".format(phasediff, 8) + # -shifts because of pandora2d convention + min_col = round(-shifts[1]) - int(self._range_col) + max_col = round(-shifts[1]) + int(self._range_col) + + min_row = round(-shifts[0]) - int(self._range_row) + max_row = round(-shifts[0]) + int(self._range_row) + + row_disparity = [min_row, max_row] + col_disparity = [min_col, max_col] + + logging.info("Estimation result is %s in columns and %s in row", -shifts[1], -shifts[0]) + logging.debug("Translation invariant normalized RMS error between left and right is %s", error) + logging.debug("Global phase difference between the two images is %s", phasediff) + + extra_dict = {"error": error, "phase_diff": phasediff} + + return row_disparity, col_disparity, -shifts, extra_dict diff --git a/pandora2d/img_tools.py b/pandora2d/img_tools.py index 7059b46..2c54c7f 100644 --- a/pandora2d/img_tools.py +++ b/pandora2d/img_tools.py @@ -42,7 +42,7 @@ class Datasets(NamedTuple): right: xr.Dataset -def create_datasets_from_inputs(input_config: Dict, roi: Dict = None) -> Datasets: +def create_datasets_from_inputs(input_config: Dict, roi: Dict = None, estimation_cfg: Dict = None) -> Datasets: """ Read image and return the corresponding xarray.DataSet @@ -56,6 +56,8 @@ def create_datasets_from_inputs(input_config: Dict, roi: Dict = None) -> Dataset with margins : left, up, right, down :type roi: dict + :param estimation_cfg: dictionary containing estimation configuration + :type estimation_cfg: dict :return: Datasets NamedTuple with two attributes `left` and `right` each containing a xarray.DataSet containing the variables : @@ -66,7 +68,12 @@ def create_datasets_from_inputs(input_config: Dict, roi: Dict = None) -> Dataset :rtype: Datasets """ - check_disparities(input_config) + if estimation_cfg is None: + check_disparities(input_config) + else: + input_config["col_disparity"] = [-9999, -9999] + input_config["row_disparity"] = [-9999, -9999] + return Datasets( pandora_img_tools.create_dataset_from_inputs(input_config["left"], roi).pipe( add_left_disparity_grid, input_config diff --git a/pandora2d/state_machine.py b/pandora2d/state_machine.py index 36fac29..f1b0f75 100644 --- a/pandora2d/state_machine.py +++ b/pandora2d/state_machine.py @@ -2,6 +2,7 @@ # coding: utf8 # # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). +# Copyright (c) 2024 CS GROUP France # # This file is part of PANDORA2D # @@ -23,9 +24,10 @@ This module contains class associated to the pandora state machine """ -from typing import Dict, TYPE_CHECKING, List, TypedDict, Literal, Optional, Union import logging from operator import add +from typing import TYPE_CHECKING, Dict, List, Literal, Optional, TypedDict, Union + import numpy as np import xarray as xr from typing_extensions import Annotated @@ -42,10 +44,11 @@ from transitions.extensions import GraphMachine as Machine except ImportError: from transitions import Machine + from transitions import MachineError from pandora.margins import GlobalMargins -from pandora2d import matching_cost, disparity, refinement, common +from pandora2d import common, disparity, estimation, matching_cost, refinement, img_tools class MarginsProperties(TypedDict): @@ -57,10 +60,11 @@ class MarginsProperties(TypedDict): class Pandora2DMachine(Machine): """ - Pandora2DMacine class to create and use a state machine + Pandora2DMachine class to create and use a state machine """ _transitions_run = [ + {"trigger": "estimation", "source": "begin", "dest": "assumption", "after": "estimation_run"}, { "trigger": "matching_cost", "source": "begin", @@ -68,12 +72,26 @@ class Pandora2DMachine(Machine): "prepare": "matching_cost_prepare", "after": "matching_cost_run", }, + { + "trigger": "matching_cost", + "source": "assumption", + "dest": "cost_volumes", + "prepare": "matching_cost_prepare", + "after": "matching_cost_run", + }, {"trigger": "disparity", "source": "cost_volumes", "dest": "disp_maps", "after": "disp_maps_run"}, {"trigger": "refinement", "source": "disp_maps", "dest": "disp_maps", "after": "refinement_run"}, ] _transitions_check = [ + {"trigger": "estimation", "source": "begin", "dest": "assumption", "after": "estimation_check_conf"}, {"trigger": "matching_cost", "source": "begin", "dest": "cost_volumes", "after": "matching_cost_check_conf"}, + { + "trigger": "matching_cost", + "source": "assumption", + "dest": "cost_volumes", + "after": "matching_cost_check_conf", + }, {"trigger": "disparity", "source": "cost_volumes", "dest": "disp_maps", "after": "disparity_check_conf"}, {"trigger": "refinement", "source": "disp_maps", "dest": "disp_maps", "after": "refinement_check_conf"}, ] @@ -100,11 +118,12 @@ def __init__( self.disp_max_row: np.ndarray = None self.pipeline_cfg: Dict = {"pipeline": {}} + self.completed_cfg: Dict = {} self.cost_volumes: xr.Dataset = xr.Dataset() self.dataset_disp_maps: xr.Dataset = xr.Dataset() - # Define avalaible states - states_ = ["begin", "cost_volumes", "disp_maps"] + # Define available states + states_ = ["begin", "assumption", "cost_volumes", "disp_maps"] # Instance matching_cost self.matching_cost_: Union[matching_cost.MatchingCost, None] = None @@ -239,6 +258,20 @@ def get_global_margins(self): return [max(x, y) for x, y in zip(max_margins, aggregate_margins)] + def estimation_check_conf(self, cfg: Dict[str, dict], input_step: str) -> None: + """ + Check the estimation computation configuration + + :param cfg: configuration + :type cfg: dict + :param input_step: current step + :type input_step: string + :return: None + """ + + estimation_ = estimation.AbstractEstimation(cfg["pipeline"][input_step]) # type: ignore[abstract] + self.pipeline_cfg["pipeline"][input_step] = estimation_.cfg + def matching_cost_check_conf(self, cfg: Dict[str, dict], input_step: str) -> None: """ Check the disparity computation configuration @@ -299,6 +332,34 @@ def matching_cost_prepare(self, cfg: Dict[str, dict], input_step: str) -> None: self.left_img, self.right_img, self.disp_min_col, self.disp_max_col, cfg["pipeline"][input_step] ) + def estimation_run(self, cfg: Dict[str, dict], input_step: str) -> None: + """ + Shift's estimation step + + :param cfg: pipeline configuration + :type cfg: dict + :param input_step: step to trigger + :type input_step: str + :return: None + """ + + logging.info("Estimation computation...") + estimation_ = estimation.AbstractEstimation(cfg["pipeline"][input_step]) # type: ignore[abstract] + + row_disparity, col_disparity, shifts, extra_dict = estimation_.compute_estimation(self.left_img, self.right_img) + + self.left_img = img_tools.add_disparity_grid(self.left_img, col_disparity, row_disparity) + # Column's min, max disparities + self.disp_min_col = self.left_img["col_disparity"].sel(band_disp="min").data + self.disp_max_col = self.left_img["col_disparity"].sel(band_disp="max").data + # Row's min, max disparities + self.disp_min_row = self.left_img["row_disparity"].sel(band_disp="min").data + self.disp_max_row = self.left_img["row_disparity"].sel(band_disp="max").data + + self.completed_cfg = estimation_.update_cfg_with_estimation( + cfg, col_disparity, row_disparity, shifts, extra_dict + ) + def matching_cost_run(self, _, __) -> None: """ Matching cost computation diff --git a/setup.cfg b/setup.cfg index 055f405..a5ee30d 100644 --- a/setup.cfg +++ b/setup.cfg @@ -1,4 +1,5 @@ # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). +# Copyright (c) 2024 CS GROUP France # # This file is part of Pandora2D # (see https://github.com/CNES/Pandora2d). @@ -64,6 +65,7 @@ install_requires = numba>=0.47.0;python_version<'3.8' pandora==1.6.* typing_extensions + scikit-image package_dir = . = pandora2d From bad8f1677f2e58b7ed45def815ea37e25730ce20 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Alice=20de=20Bardonn=C3=A8che-Richard?= Date: Wed, 3 Jan 2024 16:40:33 +0100 Subject: [PATCH 02/14] test: update tests + add pcc tests --- tests/common.py | 2 + tests/test_check_configuration.py | 1 + tests/test_estimation.py | 188 ++++++++++++++++++ .../test_create_datasets_from_input.py | 18 ++ 4 files changed, 209 insertions(+) create mode 100644 tests/test_estimation.py diff --git a/tests/common.py b/tests/common.py index 965b28e..f42a3d5 100644 --- a/tests/common.py +++ b/tests/common.py @@ -2,6 +2,7 @@ # coding: utf8 # # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). +# Copyright (c) 2024 CS GROUP France # # This file is part of PANDORA2D # @@ -68,6 +69,7 @@ correct_pipeline = { "pipeline": { + "estimation": {"estimation_method": "phase_cross_correlation"}, "matching_cost": {"matching_cost_method": "zncc", "window_size": 5}, "disparity": {"disparity_method": "wta", "invalid_disparity": -99}, "refinement": {"refinement_method": "interpolation"}, diff --git a/tests/test_check_configuration.py b/tests/test_check_configuration.py index 60f0bc2..8b42706 100644 --- a/tests/test_check_configuration.py +++ b/tests/test_check_configuration.py @@ -2,6 +2,7 @@ # coding: utf8 # # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). +# Copyright (c) 2024 CS GROUP France # # This file is part of PANDORA2D # diff --git a/tests/test_estimation.py b/tests/test_estimation.py new file mode 100644 index 0000000..42f79dc --- /dev/null +++ b/tests/test_estimation.py @@ -0,0 +1,188 @@ +#!/usr/bin/env python +# coding: utf8 +# +# Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). +# Copyright (c) 2024 CS GROUP France +# +# This file is part of PANDORA2D +# +# https://github.com/CNES/Pandora2D +# +# 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. +# + +""" +Test Matching cost class +""" + +# pylint: disable=redefined-outer-name + + +import numpy as np +import pytest +import json_checker +import xarray as xr +from pandora2d import estimation + + +@pytest.fixture() +def estimation_class(): + """Build estimation object.""" + estimation_class = estimation.AbstractEstimation( # type: ignore[abstract] + { + "estimation_method": "phase_cross_correlation", + "range_col": 5, + "range_row": 5, + "sample_factor": 10, + } + ) + return estimation_class + + +@pytest.fixture() +def stereo_object(): + """Create a stereo object""" + + # Create a stereo object + data = np.array( + ([-9999, -9999, -9999], [1, 1, 1], [3, 4, 5]), + dtype=np.float64, + ) + mask = np.array(([1, 1, 1], [0, 0, 0], [0, 0, 0]), dtype=np.int16) + left = xr.Dataset( + {"im": (["row", "col"], data), "msk": (["row", "col"], mask)}, + coords={"row": np.arange(data.shape[0]), "col": np.arange(data.shape[1])}, + ) + left.attrs = { + "no_data_img": -9999, + "valid_pixels": 0, + "no_data_mask": 1, + "crs": None, + "col_disparity_source": [-1, 0], + "row_disparity_source": [-1, 0], + } + + data = np.array( + ([1, 1, 1], [3, 4, 5], [1, 1, 1]), + dtype=np.float64, + ) + mask = np.array(([0, 0, 0], [0, 0, 0], [0, 0, 0]), dtype=np.int16) + right = xr.Dataset( + {"im": (["row", "col"], data), "msk": (["row", "col"], mask)}, + coords={"row": np.arange(data.shape[0]), "col": np.arange(data.shape[1])}, + ) + right.attrs = { + "no_data_img": -9999, + "valid_pixels": 0, + "no_data_mask": 1, + "crs": None, + } + + return left, right + + +@pytest.mark.parametrize( + ["estimation_method", "range_col", "range_row", "sample_factor", "error"], + [ + pytest.param("another_method", 5, 5, 10, KeyError, id="Wrong method"), + pytest.param( + "phase_cross_correlation", -1, 5, 10, json_checker.core.exceptions.DictCheckerError, id="negative range_col" + ), + pytest.param( + "phase_cross_correlation", "5", 5, 10, json_checker.core.exceptions.DictCheckerError, id="string range_col" + ), + pytest.param( + "phase_cross_correlation", 5, 0, 10, json_checker.core.exceptions.DictCheckerError, id="0 as range_row" + ), + pytest.param( + "phase_cross_correlation", 5, [2, 3], 10, json_checker.core.exceptions.DictCheckerError, id="list range_row" + ), + pytest.param( + "phase_cross_correlation", 5, 5, 0, json_checker.core.exceptions.DictCheckerError, id="0 for sample factor" + ), + pytest.param( + "phase_cross_correlation", + 5, + 5, + 15, + json_checker.core.exceptions.DictCheckerError, + id="not a multiple of 10 sample factor", + ), + ], +) +def test_false_check_conf(estimation_method, range_col, range_row, sample_factor, error): + """ + test check_conf of estimation with wrongs pipelines + """ + + with pytest.raises(error): + estimation.AbstractEstimation( + { + "estimation_method": estimation_method, + "range_col": range_col, + "range_row": range_row, + "sample_factor": sample_factor, + } + ) # type: ignore[abstract] + + +def test_check_conf(): + """ + test check_conf of estimation with a correct pipeline + """ + estimation.AbstractEstimation( + { + "estimation_method": "phase_cross_correlation", + "range_col": 5, + "range_row": 5, + "sample_factor": 10, + } + ) # type: ignore[abstract] + + +def test_update_cfg_with_estimation(estimation_class): + """ + test update_cfg_with_estimation function + """ + + gt_cfg = { + "input": {"col_disparity": [-2, 2], "row_disparity": [-2, 2]}, + "pipeline": {"estimation": {"estimated_shifts": [-0.5, 1.3], "error": [1.0], "phase_diff": [1.0]}}, + } + + cfg = estimation_class.update_cfg_with_estimation( + {"input": {}, "pipeline": {"estimation": {}}}, + [-2, 2], + [-2, 2], + -np.array([0.5, -1.3]), + {"error": np.array([1.0]), "phase_diff": np.array([1.0])}, + ) + + assert gt_cfg == cfg + + +def test_estimation_computation(stereo_object, estimation_class): + """ + test estimation_computation with phase_cross_correlation + """ + + left, right = stereo_object + estimation_ = estimation_class + + row_disparity, col_disparity, shifts, extra_dict = estimation_.compute_estimation(left, right) + + assert col_disparity == [-5, 5] + assert row_disparity == [-6, 4] + assert np.array_equal(shifts, [-0.8, 0]) + assert extra_dict["error"] == 0.9999999999855407 + assert extra_dict["phase_diff"] == "1.06382330e-18" diff --git a/tests/test_img_tools/test_create_datasets_from_input.py b/tests/test_img_tools/test_create_datasets_from_input.py index 5055093..5d3120b 100644 --- a/tests/test_img_tools/test_create_datasets_from_input.py +++ b/tests/test_img_tools/test_create_datasets_from_input.py @@ -165,3 +165,21 @@ def test_fails_when_disparity_max_lt_disparity_min(self, input_section, disparit with pytest.raises(ValueError) as exc_info: img_tools.create_datasets_from_inputs(input_section) assert exc_info.value.args[0] == "Min disparity (8) should be lower than Max disparity (-10)" + + def test_create_dataset_from_inputs_with_estimation_step(self, input_section): + """ + test dataset_from_inputs with an estimation step and no disparity range + """ + + configuration_with_estimation = {"input": input_section} + del configuration_with_estimation["input"]["row_disparity"] + del configuration_with_estimation["input"]["col_disparity"] + configuration_with_estimation["pipeline"] = {"estimation": {"estimation_method": "phase_cross_correlation"}} + result = img_tools.create_datasets_from_inputs( + input_section, estimation_cfg=configuration_with_estimation["pipeline"].get("estimation") + ) + + assert result.left.attrs["col_disparity_source"] == [-9999, -9999] + assert result.left.attrs["row_disparity_source"] == [-9999, -9999] + assert result.right.attrs["col_disparity_source"] == [9999, 9999] + assert result.right.attrs["row_disparity_source"] == [9999, 9999] From fcb3afc03ed25281109b643fc7f36134b58a163e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Alice=20de=20Bardonn=C3=A8che-Richard?= Date: Mon, 22 Jan 2024 16:30:18 +0100 Subject: [PATCH 03/14] fix: save configuration without estimation --- pandora2d/__init__.py | 12 ++++++------ pandora2d/state_machine.py | 11 +++++------ 2 files changed, 11 insertions(+), 12 deletions(-) diff --git a/pandora2d/__init__.py b/pandora2d/__init__.py index fde98e8..95c03a5 100644 --- a/pandora2d/__init__.py +++ b/pandora2d/__init__.py @@ -40,7 +40,7 @@ def run( pandora2d_machine: Pandora2DMachine, img_left: xr.Dataset, img_right: xr.Dataset, - cfg_pipeline: Dict[str, dict], + cfg: Dict[str, dict], ): """ Run the Pandora 2D pipeline @@ -57,16 +57,16 @@ def run( - im : 2D (row, col) xarray.DataArray - msk (optional): 2D (row, col) xarray.DataArray :type img_right: xarray.Dataset - :param cfg_pipeline: pipeline configuration - :type cfg_pipeline: Dict[str, dict] + :param cfg: configuration + :type cfg: Dict[str, dict] :return: None """ - pandora2d_machine.run_prepare(img_left, img_right) + pandora2d_machine.run_prepare(img_left, img_right, cfg) - for e in list(cfg_pipeline["pipeline"]): - pandora2d_machine.run(e, cfg_pipeline) + for e in list(cfg["pipeline"]): + pandora2d_machine.run(e, cfg) pandora2d_machine.run_exit() diff --git a/pandora2d/state_machine.py b/pandora2d/state_machine.py index f1b0f75..50fb2c4 100644 --- a/pandora2d/state_machine.py +++ b/pandora2d/state_machine.py @@ -23,7 +23,7 @@ """ This module contains class associated to the pandora state machine """ - +import copy import logging from operator import add from typing import TYPE_CHECKING, Dict, List, Literal, Optional, TypedDict, Union @@ -139,11 +139,7 @@ def __init__( logging.getLogger("transitions").setLevel(logging.WARNING) - def run_prepare( - self, - img_left: xr.Dataset, - img_right: xr.Dataset, - ) -> None: + def run_prepare(self, img_left: xr.Dataset, img_right: xr.Dataset, cfg: dict) -> None: """ Prepare the machine before running @@ -157,6 +153,8 @@ def run_prepare( - im : 2D (row, col) xarray.DataArray - msk : 2D (row, col) xarray.DataArray :type img_right: xarray.Dataset + :param cfg: configuration + :type cfg: Dict[str, dict] """ self.left_img = img_left @@ -167,6 +165,7 @@ def run_prepare( # Row's min, max disparities self.disp_min_row = img_left["row_disparity"].sel(band_disp="min").data self.disp_max_row = img_left["row_disparity"].sel(band_disp="max").data + self.completed_cfg = copy.copy(cfg) self.add_transitions(self._transitions_run) From 0ca65bb1d42c0b65dd1082850bf8b6682ac26d3e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Alice=20de=20Bardonn=C3=A8che-Richard?= Date: Mon, 22 Jan 2024 16:32:52 +0100 Subject: [PATCH 04/14] test: add cfg in run_prepare API --- tests/test_pandora2d.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/tests/test_pandora2d.py b/tests/test_pandora2d.py index d2cdb82..4a0ca17 100644 --- a/tests/test_pandora2d.py +++ b/tests/test_pandora2d.py @@ -74,10 +74,11 @@ def test_run_prepare() -> None: } img_left, img_right = create_datasets_from_inputs(input_config=input_config) - pandora2d_machine.run_prepare(img_left, img_right) + pandora2d_machine.run_prepare(img_left, img_right, input_config) assert pandora2d_machine.left_img == img_left assert pandora2d_machine.right_img == img_right + assert pandora2d_machine.completed_cfg == input_config np.testing.assert_array_equal( pandora2d_machine.disp_min_col, np.full((img_left.sizes["row"], img_left.sizes["col"]), -2) ) From 3778563bb3805984e680d85b0a4728e8f5119449 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Alice=20de=20Bardonn=C3=A8che-Richard?= Date: Tue, 9 Jan 2024 13:33:53 +0100 Subject: [PATCH 05/14] feat: add optical_flow refinement method --- .../json_conf_files/a_basic_pipeline.json | 2 +- pandora2d/common.py | 8 +- pandora2d/estimation/__init__.py | 1 - pandora2d/estimation/estimation.py | 1 - .../estimation/phase_cross_correlation.py | 1 - pandora2d/img_tools.py | 1 + pandora2d/matching_cost/matching_cost.py | 2 + pandora2d/refinement/__init__.py | 3 +- pandora2d/refinement/interpolation.py | 21 +- pandora2d/refinement/optical_flow.py | 344 ++++++++++++++++++ pandora2d/refinement/refinement.py | 25 +- pandora2d/state_machine.py | 24 +- 12 files changed, 410 insertions(+), 23 deletions(-) create mode 100644 pandora2d/refinement/optical_flow.py diff --git a/data_samples/json_conf_files/a_basic_pipeline.json b/data_samples/json_conf_files/a_basic_pipeline.json index ea154f3..ef5b582 100644 --- a/data_samples/json_conf_files/a_basic_pipeline.json +++ b/data_samples/json_conf_files/a_basic_pipeline.json @@ -21,7 +21,7 @@ "invalid_disparity": "NaN" }, "refinement": { - "refinement_method": "interpolation" + "refinement_method": "optical_flow" } } } diff --git a/pandora2d/common.py b/pandora2d/common.py index 2f9e645..f8a6427 100644 --- a/pandora2d/common.py +++ b/pandora2d/common.py @@ -2,6 +2,7 @@ # coding: utf8 # # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). +# Copyright (c) 2024 CS GROUP France # # This file is part of PANDORA2D # @@ -53,7 +54,7 @@ def save_dataset(dataset: xr.Dataset, output: str) -> None: write_data_array(dataset["col_map"], os.path.join(output, "columns_disparity.tif")) -def dataset_disp_maps(delta_row: np.ndarray, delta_col: np.ndarray) -> xr.Dataset: +def dataset_disp_maps(delta_row: np.ndarray, delta_col: np.ndarray, attributes: dict = None) -> xr.Dataset: """ Create the dataset containing disparity maps @@ -61,6 +62,8 @@ def dataset_disp_maps(delta_row: np.ndarray, delta_col: np.ndarray) -> xr.Datase :type delta_row: np.ndarray :param delta_col: disparity map for col :type delta_col: np.ndarray + :param attributes: disparity map for col + :type attributes: dict :return: dataset: Dataset with the disparity maps with the data variables : - row_map 2D xarray.DataArray (row, col) @@ -81,4 +84,7 @@ def dataset_disp_maps(delta_row: np.ndarray, delta_col: np.ndarray) -> xr.Datase # merge two dataset into one dataset = dataset_row.merge(dataset_col, join="override", compat="override") + if attributes is not None: + dataset.attrs = attributes + return dataset diff --git a/pandora2d/estimation/__init__.py b/pandora2d/estimation/__init__.py index bf8cbec..8313cef 100644 --- a/pandora2d/estimation/__init__.py +++ b/pandora2d/estimation/__init__.py @@ -1,7 +1,6 @@ #!/usr/bin/env python # coding: utf8 # -# Copyright (c) 2024 Centre National d'Etudes Spatiales (CNES). # Copyright (c) 2024 CS GROUP France # # This file is part of PANDORA2D diff --git a/pandora2d/estimation/estimation.py b/pandora2d/estimation/estimation.py index 78ae201..97c9ad1 100644 --- a/pandora2d/estimation/estimation.py +++ b/pandora2d/estimation/estimation.py @@ -1,7 +1,6 @@ #!/usr/bin/env python # coding: utf8 # -# Copyright (c) 2024 Centre National d'Etudes Spatiales (CNES). # Copyright (c) 2024 CS GROUP France # # This file is part of PANDORA2D diff --git a/pandora2d/estimation/phase_cross_correlation.py b/pandora2d/estimation/phase_cross_correlation.py index f74dfc9..576e737 100644 --- a/pandora2d/estimation/phase_cross_correlation.py +++ b/pandora2d/estimation/phase_cross_correlation.py @@ -1,7 +1,6 @@ #!/usr/bin/env python # coding: utf8 # -# Copyright (c) 2024 Centre National d'Etudes Spatiales (CNES). # Copyright (c) 2024 CS GROUP France # # This file is part of PANDORA2D diff --git a/pandora2d/img_tools.py b/pandora2d/img_tools.py index 2c54c7f..b8cdb88 100644 --- a/pandora2d/img_tools.py +++ b/pandora2d/img_tools.py @@ -2,6 +2,7 @@ # coding: utf8 # # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). +# Copyright (c) 2024 CS GROUP France # # This file is part of PANDORA2D # diff --git a/pandora2d/matching_cost/matching_cost.py b/pandora2d/matching_cost/matching_cost.py index 7df6f59..28b2a3e 100644 --- a/pandora2d/matching_cost/matching_cost.py +++ b/pandora2d/matching_cost/matching_cost.py @@ -2,6 +2,7 @@ # coding: utf8 # # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). +# Copyright (c) 2024 CS GROUP France # # This file is part of PANDORA2D # @@ -252,5 +253,6 @@ def compute_cost_volumes( del cost_volumes.attrs["disparity_source"] cost_volumes.attrs["col_disparity_source"] = img_left.attrs["col_disparity_source"] cost_volumes.attrs["row_disparity_source"] = img_left.attrs["row_disparity_source"] + cost_volumes.attrs["step"] = self.cfg["step"] return cost_volumes diff --git a/pandora2d/refinement/__init__.py b/pandora2d/refinement/__init__.py index 21a5a84..5c53fd6 100644 --- a/pandora2d/refinement/__init__.py +++ b/pandora2d/refinement/__init__.py @@ -2,6 +2,7 @@ # coding: utf8 # # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). +# Copyright (c) 2024 CS GROUP France # # This file is part of PANDORA2D # @@ -23,6 +24,6 @@ Init file for refinement module """ -from . import interpolation +from . import interpolation, optical_flow from . import dichotomy from .refinement import AbstractRefinement diff --git a/pandora2d/refinement/interpolation.py b/pandora2d/refinement/interpolation.py index c6efcc7..6867a80 100644 --- a/pandora2d/refinement/interpolation.py +++ b/pandora2d/refinement/interpolation.py @@ -2,6 +2,7 @@ # coding: utf8 # # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). +# Copyright (c) 2024 CS GROUP France # # This file is part of PANDORA2D # @@ -126,13 +127,19 @@ def compute_cost_matrix(self, p_args) -> Tuple[float, float]: return res - def refinement_method(self, cost_volumes: xr.Dataset, pixel_maps: xr.Dataset) -> Tuple[np.ndarray, np.ndarray]: + def refinement_method( + self, cost_volumes: xr.Dataset, disp_map: xr.Dataset, img_left: xr.Dataset, img_right: xr.Dataset + ) -> Tuple[np.ndarray, np.ndarray]: """ Compute refine disparity maps :param cost_volumes: Cost_volumes has (row, col, disp_col, disp_row) dimensions :type cost_volumes: xr.Dataset - :param pixel_maps: dataset of pixel disparity maps - :type pixel_maps: xr.Dataset + :param disp_map: dataset of pixel disparity maps + :type disp_map: xr.Dataset + :param img_left: left image dataset + :type img_left: xarray.Dataset + :param img_right: right image dataset + :type img_right: xarray.Dataset :return: delta_col, delta_row: subpixel disparity maps :rtype: Tuple[np.array, np.array] """ @@ -144,8 +151,8 @@ def refinement_method(self, cost_volumes: xr.Dataset, pixel_maps: xr.Dataset) -> cost_matrix = np.rollaxis(np.rollaxis(data, 3, 0), 3, 1).reshape((ndisprow, ndispcol, nrow * ncol)) # flatten pixel maps for multiprocessing - liste_row = list(pixel_maps["row_map"].data.flatten().tolist()) - liste_col = list(pixel_maps["col_map"].data.flatten().tolist()) + liste_row = list(disp_map["row_map"].data.flatten().tolist()) + liste_col = list(disp_map["col_map"].data.flatten().tolist()) # args for multiprocessing args = [ @@ -160,7 +167,7 @@ def refinement_method(self, cost_volumes: xr.Dataset, pixel_maps: xr.Dataset) -> delta_row = np.array(map_carte)[:, 1] # reshape disparity maps - delta_col = np.reshape(delta_col, (pixel_maps["col_map"].data.shape[0], pixel_maps["col_map"].data.shape[1])) - delta_row = np.reshape(delta_row, (pixel_maps["col_map"].data.shape[0], pixel_maps["col_map"].data.shape[1])) + delta_col = np.reshape(delta_col, (disp_map["col_map"].data.shape[0], disp_map["col_map"].data.shape[1])) + delta_row = np.reshape(delta_row, (disp_map["col_map"].data.shape[0], disp_map["col_map"].data.shape[1])) return delta_col, delta_row diff --git a/pandora2d/refinement/optical_flow.py b/pandora2d/refinement/optical_flow.py new file mode 100644 index 0000000..5a33769 --- /dev/null +++ b/pandora2d/refinement/optical_flow.py @@ -0,0 +1,344 @@ +#!/usr/bin/env python +# coding: utf8 +# +# Copyright (c) 2024 CS GROUP France +# +# This file is part of PANDORA2D +# +# https://github.com/CNES/Pandora2D +# +# 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 functions associated to the optical flow method used in the refinement step. +""" +from typing import Dict, Tuple + +import numpy as np +import xarray as xr +from json_checker import And, Checker +from scipy.ndimage import map_coordinates +from pandora.margins import Margins + +from . import refinement + + +@refinement.AbstractRefinement.register_subclass("optical_flow") +class OpticalFlow(refinement.AbstractRefinement): + """ + OpticalFLow class allows to perform the subpixel cost refinement step + """ + + _nbr_iteration = None + _invalid_disp = None + + _NBR_ITERATION = 4 + + def __init__(self, cfg: dict = None, step: list = None, window_size: int = 5) -> None: + """ + :param cfg: optional configuration, {} + :type cfg: dict + :return: None + """ + + self.cfg = self.check_conf(cfg) + self._nbr_iteration = self.cfg["nbr_iteration"] + self._refinement_method = self.cfg["refinement_method"] + self._window_size = window_size + self._step = [1, 1] if step is None else step + + @property + def margins(self): + values = (self._window_size // 2 * ele for _ in range(2) for ele in self._step) + return Margins(*values) + + def check_conf(self, cfg: Dict) -> Dict: + """ + Check the refinement configuration + + :param cfg: user_config for refinement + :type cfg: dict + :return: cfg: global configuration + :rtype: cfg: dict + """ + + if "nbr_iteration" not in cfg: + cfg["nbr_iteration"] = self._NBR_ITERATION + + schema = { + "refinement_method": And(str, lambda x: x in ["optical_flow"]), + "nbr_iteration": And(int, lambda nbr_i: nbr_i > 0), + } + + checker = Checker(schema) + checker.validate(cfg) + + return cfg + + def reshape_to_matching_cost_window( + self, img: xr.Dataset, valid_dims: list, drow: np.ndarray = None, dcol: np.ndarray = None + ): + """ + Transform image from (nb_col, nb_row) to (window_size, window_size, nbcol*nbrow) + + :param img: image to reshape + :type img: xr.Dataset + :param valid_dims: size of image without borders + :type valid_dims: list + :param drow: array dim [] containing all the row shift + :type drow: np.ndarray + :param dcol: array dim [] containing all the columns shift + :type dcol: np.ndarray + :return: array containing reshaped image [window_size, window_size, nbcol*nbrow] + :rtype: np.ndarray + """ + + # get numpy array datas for image + img_data = img["im"].data + nb_row, nb_col = img_data.shape + + # valid_dims[0]*valid_dims[1] + one_dim_size = np.prod(valid_dims) + + if drow is None and dcol is None: + patches = np.lib.stride_tricks.sliding_window_view(img_data, [self._window_size, self._window_size]) + patches = patches.reshape((one_dim_size, self._window_size, self._window_size)).transpose((1, 2, 0)) + else: + # initiate values for right reshape computation + offset = max(self.margins.astuple()) + patches = np.ndarray((self._window_size, self._window_size, one_dim_size)) + idx = 0 + + for row in range(offset, nb_row - offset): + for col in range(offset, nb_col - offset): + + shift_col = 0 if np.isnan(dcol[idx]) or dcol[idx] == self._invalid_disp else int(dcol[idx]) + shift_row = 0 if np.isnan(drow[idx]) or drow[idx] == self._invalid_disp else int(drow[idx]) + + # get right pixel with his matching cost window + patch = img_data[ + row - offset + shift_row : row + offset + 1 + shift_row, + col - offset + shift_col : col + offset + 1 + shift_col, + ] + + # stock matching_cost window + if patch.shape == (self._window_size, self._window_size): + patches[:, :, idx] = patch + else: + patches[:, :, idx] = np.ones([self._window_size, self._window_size]) * np.nan + + idx += 1 + + return patches + + def warped_img( + self, + right_reshape: np.ndarray, + delta_row: np.ndarray, + delta_col: np.ndarray, + left_img: xr.Dataset, + index_to_compute: list, + ): + """ + Shifted matching_cost window with computed disparity + + :param right_reshape: image right reshaped with dims (window_size, window_size, nbcol*nb_row) + :type right_reshape: np.ndarray + :param delta_row: rows disparity map + :type delta_row: np.ndarray + :param delta_col: columns disparity map + :type delta_col: np.ndarray + :param left_img: left image dataset + :type left_img: xarray.Dataset + :param index_to_compute: list containing all valid pixel for computing optical flow + :type index_to_compute: list + :return: new array containing shifted matching_cost windows + :rtype: np.ndarray + """ + + if self._step == [1, 1]: + coords_range = index_to_compute + else: + nb_col = left_img.dims["col"] + nb_row = left_img.dims["row"] + step_row, step_col = self._step + + coords_range = [row * nb_col + col + for row in np.arange(0, nb_row, step_row) + for col in np.arange(0, nb_col, step_col) + if row * nb_col + col in index_to_compute] + + x, y = np.meshgrid(range(self._window_size), range(self._window_size)) + + new_img = np.empty_like(right_reshape) + + # resample matching cost right windows + for idx in coords_range: + shifted_img = map_coordinates( + right_reshape[:, :, idx], [y + delta_row[idx], x + delta_col[idx]], order=5, mode="reflect" + ) + + new_img[:, :, idx] = shifted_img + + return new_img + + def lucas_kanade_core_algorithm(self, left_data: np.ndarray, right_data: np.ndarray) -> Tuple[float, float]: + """ + Implement lucas & kanade algorithm core + + :param left_data: matching_cost window for one pixel from left image + :type left_data: np.ndarray + :param right_data: matching_cost window for one pixel from left image + :type right_data: np.ndarray + :return: sub-pixel disparity computed by Lucas & Kanade optical flow + :rtype: Tuple[float, float] + """ + + grad_x = np.gradient(left_data, axis=1) + grad_y = np.gradient(left_data, axis=0) + grad_t = left_data - right_data + + # Create A (grad_matrix) et B (time_matrix) matrix for Lucas Kanade + grad_matrix = np.vstack((grad_x.flatten(), grad_y.flatten())).T + time_matrix = np.reshape(grad_t, len(grad_t) ** 2)[np.newaxis].T + + # v = (A^T.A)^-1.A^T.B + try: + motion = tuple( + np.matmul(np.linalg.inv(np.matmul(grad_matrix.T, grad_matrix)), np.matmul(grad_matrix.T, time_matrix)) + ) + # if matrix is full of NaN or 0 + except np.linalg.LinAlgError: + motion = (self._invalid_disp, self._invalid_disp) + + return motion[1], motion[0] + + def optical_flow( + self, + left_img: np.ndarray, + right_img: np.ndarray, + list_idx_to_compute: list, + ) -> Tuple[np.ndarray, np.ndarray, list]: + """ + Computing optical flow between left and right image + + :param left_img: reshaped left image array + :type left_img: np.ndarray + :param right_img: reshaped right image array + :type right_img: np.ndarray + :param list_idx_to_compute: list of valid pixel + :type list_idx_to_compute: list + :return: computed sub-pixel disparity map + :rtype: Tuple[np.ndarray, np.ndarray, list] + """ + + new_list_to_compute = [] + + final_dec_row = np.zeros(left_img.shape[2]) + final_dec_col = np.zeros(left_img.shape[2]) + + for idx in list_idx_to_compute: + + left_matching_cost = left_img[:, :, idx] + right_matching_cost = right_img[:, :, idx] + + computed_delta_row, computed_delta_col = self.lucas_kanade_core_algorithm( + left_matching_cost, right_matching_cost + ) + + # hypothesis from algorithm: shifts are < 1 + if abs(computed_delta_col) < 1 and abs(computed_delta_row) < 1: + new_list_to_compute.append(idx) + else: + if abs(computed_delta_col) > 1: + computed_delta_col = 0 + if abs(computed_delta_row) > 1: + computed_delta_row = 0 + + final_dec_row[idx] = computed_delta_row + final_dec_col[idx] = computed_delta_col + + return final_dec_row, final_dec_col, new_list_to_compute + + def refinement_method( + self, cost_volumes: xr.Dataset, disp_map: xr.Dataset, img_left: xr.Dataset, img_right: xr.Dataset + ) -> Tuple[np.ndarray, np.ndarray]: + """ + Return the subpixel disparity maps + + :param cost_volumes: cost_volumes 4D row, col, disp_col, disp_row + :type cost_volumes: xarray.Dataset + :param disp_map: pixels disparity maps + :type disp_map: xarray.Dataset + :param img_left: left image dataset + :type img_left: xarray.Dataset + :param img_right: right image dataset + :type img_right: xarray.Dataset + :return: the refined disparity maps + :rtype: Tuple[np.ndarray, np.ndarray] + """ + + # get invalid_disp value + self._invalid_disp = disp_map.attrs["invalid_disp"] + + # get offset + offset = max(self.margins.astuple()) + + # get dimensions + nb_row, nb_col = img_left["im"].data.shape + nb_valid_points_row = nb_row - 2 * offset + nb_valid_points_col = nb_col - 2 * offset + + # get displacement map from disparity state + initial_delta_row = disp_map["row_map"].data + initial_delta_col = disp_map["col_map"].data + + delta_col = initial_delta_col[offset:-offset, offset:-offset].flatten() + delta_row = initial_delta_row[offset:-offset, offset:-offset].flatten() + + # reshape left and right datas + # from (nbcol, nbrow) to (window_size, window_size, nbcol*nbrow) + reshaped_left = self.reshape_to_matching_cost_window(img_left, [nb_valid_points_col, nb_valid_points_row]) + reshaped_right = self.reshape_to_matching_cost_window( + img_right, + [nb_valid_points_col, nb_valid_points_row], + drow=delta_row, + dcol=delta_col, + ) + + idx_to_compute = np.arange(reshaped_left.shape[2]).tolist() + + for _ in range(self._nbr_iteration): + + computed_drow, computed_dcol, idx_to_compute = self.optical_flow( + reshaped_left, reshaped_right, idx_to_compute + ) + + reshaped_right = self.warped_img(reshaped_right, computed_drow, computed_dcol, img_left, idx_to_compute) + + delta_col = delta_col + computed_dcol + delta_row = delta_row + computed_drow + + delta_col = delta_col.reshape([nb_valid_points_col, nb_valid_points_row]) + delta_row = delta_row.reshape([nb_valid_points_col, nb_valid_points_row]) + + # add borders + delta_col = np.pad(delta_col, pad_width=offset, constant_values=self._invalid_disp) + delta_row = np.pad(delta_row, pad_width=offset, constant_values=self._invalid_disp) + + delta_col[delta_col <= img_left.attrs["row_disparity_source"][0]] = self._invalid_disp + delta_col[delta_col >= img_left.attrs["row_disparity_source"][1]] = self._invalid_disp + delta_row[delta_row <= img_left.attrs["col_disparity_source"][0]] = self._invalid_disp + delta_row[delta_row >= img_left.attrs["col_disparity_source"][1]] = self._invalid_disp + + return delta_col, delta_row diff --git a/pandora2d/refinement/refinement.py b/pandora2d/refinement/refinement.py index e86f020..3c4eaba 100644 --- a/pandora2d/refinement/refinement.py +++ b/pandora2d/refinement/refinement.py @@ -2,6 +2,7 @@ # coding: utf8 # # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). +# Copyright (c) 2024 CS GROUP France # # This file is part of PANDORA2D # @@ -50,13 +51,14 @@ class AbstractRefinement: # If we don't make cfg optional, we got this error when we use subprocesses in refinement_method : # AbstractRefinement.__new__() missing 1 required positional argument: 'cfg' - def __new__(cls, cfg: dict | None = None): + def __new__(cls, cfg: dict = None, _: list = None, __: int = 5): """ Return the plugin associated with the refinement_method given in the configuration :param cfg: configuration {'refinement_method': value} :type cfg: dictionary """ + if cls is AbstractRefinement: if isinstance(cfg["refinement_method"], str): try: @@ -83,6 +85,13 @@ def __new__(cls, cfg: dict | None = None): return super(AbstractRefinement, cls).__new__(cls) return None + def desc(self) -> None: + """ + Describes the refinement method + :return: None + """ + print(f"{self._refinement_method} refinement measure") + @classmethod def register_subclass(cls, short_name: str): """ @@ -128,14 +137,20 @@ def check_conf(cls, cfg: Dict) -> Dict: return cfg @abstractmethod - def refinement_method(self, cost_volumes: xr.Dataset, pixel_maps: xr.Dataset) -> Tuple[np.ndarray, np.ndarray]: + def refinement_method( + self, cost_volumes: xr.Dataset, disp_map: xr.Dataset, img_left: xr.Dataset, img_right: xr.Dataset + ) -> Tuple[np.ndarray, np.ndarray]: """ Return the subpixel disparity maps :param cost_volumes: cost_volumes 4D row, col, disp_col, disp_row - :type cost_volumes: xarray.dataset - :param pixel_maps: pixels disparity maps - :type pixel_maps: xarray.dataset + :type cost_volumes: xarray.Dataset + :param disp_map: pixels disparity maps + :type disp_map: xarray.Dataset + :param img_left: left image dataset + :type img_left: xarray.Dataset + :param img_right: right image dataset + :type img_right: xarray.Dataset :return: the refined disparity maps :rtype: Tuple[np.ndarray, np.ndarray] """ diff --git a/pandora2d/state_machine.py b/pandora2d/state_machine.py index 50fb2c4..b5b4a18 100644 --- a/pandora2d/state_machine.py +++ b/pandora2d/state_machine.py @@ -58,7 +58,7 @@ class MarginsProperties(TypedDict): margins: Annotated[List[int], '["left, "up", "right", "down"]'] -class Pandora2DMachine(Machine): +class Pandora2DMachine(Machine): # pylint:disable=too-many-instance-attributes """ Pandora2DMachine class to create and use a state machine """ @@ -122,6 +122,10 @@ def __init__( self.cost_volumes: xr.Dataset = xr.Dataset() self.dataset_disp_maps: xr.Dataset = xr.Dataset() + # For communication between matching_cost and refinement steps + self.step: list = None + self.window_size: int = None + # Define available states states_ = ["begin", "assumption", "cost_volumes", "disp_maps"] @@ -284,6 +288,8 @@ def matching_cost_check_conf(self, cfg: Dict[str, dict], input_step: str) -> Non matching_cost_ = matching_cost.MatchingCost(cfg["pipeline"][input_step]) self.pipeline_cfg["pipeline"][input_step] = matching_cost_.cfg + self.step = list(matching_cost_.cfg["step"]) + self.window_size = int(matching_cost_.cfg["window_size"]) self.margins.add_cumulative(input_step, matching_cost_.margins) def disparity_check_conf(self, cfg: Dict[str, dict], input_step: str) -> None: @@ -312,7 +318,9 @@ def refinement_check_conf(self, cfg: Dict[str, dict], input_step: str) -> None: :return: None """ - refinement_ = refinement.AbstractRefinement(cfg["pipeline"][input_step]) # type: ignore[abstract] + refinement_ = refinement.AbstractRefinement( + cfg["pipeline"][input_step], self.step, self.window_size + ) # type: ignore[abstract] self.pipeline_cfg["pipeline"][input_step] = refinement_.cfg self.margins.add_non_cumulative(input_step, refinement_.margins) @@ -392,7 +400,9 @@ def disp_maps_run(self, cfg: Dict[str, dict], input_step: str) -> None: disparity_run = disparity.Disparity(cfg["pipeline"][input_step]) map_col, map_row = disparity_run.compute_disp_maps(self.cost_volumes) - self.dataset_disp_maps = common.dataset_disp_maps(map_row, map_col) + self.dataset_disp_maps = common.dataset_disp_maps( + map_row, map_col, {"invalid_disp": cfg["pipeline"]["disparity"]["invalid_disparity"]} + ) def refinement_run(self, cfg: Dict[str, dict], input_step: str) -> None: """ @@ -406,7 +416,11 @@ def refinement_run(self, cfg: Dict[str, dict], input_step: str) -> None: """ logging.info("Refinement computation...") - refinement_run = refinement.AbstractRefinement(cfg["pipeline"][input_step]) # type: ignore[abstract] + refinement_run = refinement.AbstractRefinement( + cfg["pipeline"][input_step], self.step, self.window_size + ) # type: ignore[abstract] - refine_map_col, refine_map_row = refinement_run.refinement_method(self.cost_volumes, self.dataset_disp_maps) + refine_map_col, refine_map_row = refinement_run.refinement_method( + self.cost_volumes, self.dataset_disp_maps, self.left_img, self.right_img + ) self.dataset_disp_maps = common.dataset_disp_maps(refine_map_row, refine_map_col) From 398a5ac60875c81e62c43178b0441998960ed2ff Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Alice=20de=20Bardonn=C3=A8che-Richard?= Date: Mon, 15 Jan 2024 09:22:08 +0100 Subject: [PATCH 06/14] test: adapt refinement + add optical_flow tests --- tests/test_check_configuration.py | 1 - tests/test_common.py | 114 +++---- .../test_create_datasets_from_input.py | 1 + tests/test_matching_cost.py | 2 + tests/test_pandora2d.py | 1 + tests/test_refinement.py | 311 +++++++++++++----- 6 files changed, 282 insertions(+), 148 deletions(-) diff --git a/tests/test_check_configuration.py b/tests/test_check_configuration.py index 8b42706..60f0bc2 100644 --- a/tests/test_check_configuration.py +++ b/tests/test_check_configuration.py @@ -2,7 +2,6 @@ # coding: utf8 # # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). -# Copyright (c) 2024 CS GROUP France # # This file is part of PANDORA2D # diff --git a/tests/test_common.py b/tests/test_common.py index 56cea77..e6d90d3 100644 --- a/tests/test_common.py +++ b/tests/test_common.py @@ -23,75 +23,65 @@ """ Test common """ + +# pylint: disable=redefined-outer-name import os -import unittest -import xarray as xr import numpy as np +import pytest +import xarray as xr from pandora2d import common -class TestCommon(unittest.TestCase): +@pytest.fixture +def create_test_dataset(): + """ + Create a test dataset + """ + row, col = np.ones((2, 2)), np.ones((2, 2)) + + dataset_y = xr.Dataset( + {"row_map": (["row", "col"], row)}, + coords={"row": np.arange(row.shape[0]), "col": np.arange(row.shape[1])}, + ) + + dataset_x = xr.Dataset( + {"col_map": (["row", "col"], col)}, + coords={"row": np.arange(col.shape[0]), "col": np.arange(col.shape[1])}, + ) + + dataset = dataset_y.merge(dataset_x, join="override", compat="override") + + return dataset + + +def test_save_dataset(create_test_dataset): """ - TestImgTools class allows to test all the methods in the img_tools function + Function for testing the dataset_save function """ - def setUp(self) -> None: - """ - Method called to prepare the test fixture - - """ - self.row = np.ones((2, 2)) - self.col = np.ones((2, 2)) - - def test_save_dataset(self): - """ - Function for testing the dataset_save function - """ - dataset_y = xr.Dataset( - {"row_map": (["row", "col"], self.row)}, - coords={"row": np.arange(self.row.shape[0]), "col": np.arange(self.row.shape[1])}, - ) - - dataset_x = xr.Dataset( - {"col_map": (["row", "col"], self.col)}, - coords={"row": np.arange(self.col.shape[0]), "col": np.arange(self.col.shape[1])}, - ) - - dataset = dataset_y.merge(dataset_x, join="override", compat="override") - - common.save_dataset(dataset, "./tests/res_test/") - assert os.path.exists("./tests/res_test/") - - assert os.path.exists("./tests/res_test/columns_disparity.tif") - assert os.path.exists("./tests/res_test/row_disparity.tif") - - os.remove("./tests/res_test/columns_disparity.tif") - os.remove("./tests/res_test/row_disparity.tif") - os.rmdir("./tests/res_test") - - @staticmethod - def test_dataset_disp_maps(): - """ - Test function for create a dataset - """ - - # create a test dataset for map row - data = np.zeros((2, 2)) - dataset_y = xr.Dataset( - {"row_map": (["row", "col"], data)}, - coords={"row": np.arange(data.shape[0]), "col": np.arange(data.shape[1])}, - ) - # create a test dataset for map col - dataset_x = xr.Dataset( - {"col_map": (["row", "col"], data)}, - coords={"row": np.arange(data.shape[0]), "col": np.arange(data.shape[1])}, - ) - # merge two dataset into one - dataset_test = dataset_y.merge(dataset_x, join="override", compat="override") - - # create dataset with function - dataset_fun = common.dataset_disp_maps(data, data) - - assert dataset_fun.equals(dataset_test) + common.save_dataset(create_test_dataset, "./tests/res_test/") + assert os.path.exists("./tests/res_test/") + + assert os.path.exists("./tests/res_test/columns_disparity.tif") + assert os.path.exists("./tests/res_test/row_disparity.tif") + + os.remove("./tests/res_test/columns_disparity.tif") + os.remove("./tests/res_test/row_disparity.tif") + os.rmdir("./tests/res_test") + + +def test_dataset_disp_maps(create_test_dataset): + """ + Test function for create a dataset + """ + + dataset_test = create_test_dataset + + dataset_test.attrs = {"invalid_disp": -9999} + + # create dataset with function + dataset_fun = common.dataset_disp_maps(np.ones((2, 2)), np.ones((2, 2)), {"invalid_disp": -9999}) + + assert dataset_fun.equals(dataset_test) diff --git a/tests/test_img_tools/test_create_datasets_from_input.py b/tests/test_img_tools/test_create_datasets_from_input.py index 5d3120b..00c92f8 100644 --- a/tests/test_img_tools/test_create_datasets_from_input.py +++ b/tests/test_img_tools/test_create_datasets_from_input.py @@ -1,4 +1,5 @@ # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). +# Copyright (c) 2024 CS GROUP France # # This file is part of PANDORA2D # diff --git a/tests/test_matching_cost.py b/tests/test_matching_cost.py index 70034b6..ae19089 100644 --- a/tests/test_matching_cost.py +++ b/tests/test_matching_cost.py @@ -2,6 +2,7 @@ # coding: utf8 # # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). +# Copyright (c) 2024 CS GROUP France # # This file is part of PANDORA2D # @@ -387,6 +388,7 @@ def test_allocate_cost_volume(self): cost_volumes_test.attrs["no_data_img"] = -9999 cost_volumes_test.attrs["no_data_mask"] = 1 cost_volumes_test.attrs["valid_pixels"] = 0 + cost_volumes_test.attrs["step"] = [1, 1] # data by function compute_cost_volume cfg = {"matching_cost_method": "zncc", "window_size": 3} diff --git a/tests/test_pandora2d.py b/tests/test_pandora2d.py index 4a0ca17..e6fc596 100644 --- a/tests/test_pandora2d.py +++ b/tests/test_pandora2d.py @@ -2,6 +2,7 @@ # coding: utf8 # # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). +# Copyright (c) 2024 CS GROUP France # # This file is part of PANDORA2D # diff --git a/tests/test_refinement.py b/tests/test_refinement.py index e1a886f..ec1e817 100644 --- a/tests/test_refinement.py +++ b/tests/test_refinement.py @@ -2,6 +2,7 @@ # coding: utf8 # # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). +# Copyright (c) 2024 CS GROUP France # # This file is part of PANDORA2D # @@ -24,126 +25,266 @@ Test refinement step """ -import unittest +# pylint: disable=redefined-outer-name, protected-access +# mypy: disable-error-code=attr-defined + + import numpy as np import xarray as xr import pytest +from json_checker.core.exceptions import DictCheckerError + from pandora.margins import Margins from pandora2d import refinement, common -class TestRefinement(unittest.TestCase): +@pytest.fixture() +def cv_dataset(): + """ " """ + + cv = np.zeros((3, 3, 5, 5)) + cv[:, :, 2, 2] = np.ones([3, 3]) + cv[:, :, 2, 3] = np.ones([3, 3]) + cv[:, :, 3, 2] = np.ones([3, 3]) + cv[:, :, 3, 3] = np.ones([3, 3]) + + c_row = [0, 1, 2] + c_col = [0, 1, 2] + + # First pixel in the image that is fully computable (aggregation windows are complete) + row = np.arange(c_row[0], c_row[-1] + 1) + col = np.arange(c_col[0], c_col[-1] + 1) + + disparity_range_col = np.arange(-2, 2 + 1) + disparity_range_row = np.arange(-2, 2 + 1) + + cost_volumes_test = xr.Dataset( + {"cost_volumes": (["row", "col", "disp_col", "disp_row"], cv)}, + coords={"row": row, "col": col, "disp_col": disparity_range_col, "disp_row": disparity_range_row}, + ) + + cost_volumes_test.attrs["measure"] = "zncc" + cost_volumes_test.attrs["window_size"] = 1 + cost_volumes_test.attrs["type_measure"] = "max" + + return cost_volumes_test + + +@pytest.fixture() +def dataset_image(): + """ + Create an image dataset + """ + data = np.arange(30).reshape((6, 5)) + + img = xr.Dataset( + {"im": (["row", "col"], data)}, + coords={"row": np.arange(data.shape[0]), "col": np.arange(data.shape[1])}, + ) + img.attrs = { + "no_data_img": -9999, + "valid_pixels": 0, + "no_data_mask": 1, + "crs": None, + "col_disparity_source": [-2, 2], + "row_disparity_source": [-2, 2], + "invalid_disparity": np.nan, + } + + return img + + +def test_margins(): + """ + test margins of matching cost pipeline + """ + _refinement = refinement.AbstractRefinement({"refinement_method": "interpolation"}) # type: ignore[abstract] + + assert _refinement.margins == Margins(3, 3, 3, 3), "Not a cubic kernel Margins" + + +@pytest.mark.parametrize("refinement_method", ["interpolation", "optical_flow"]) +def test_check_conf_passes(refinement_method): """ - TestRefinement class allows to test the refinement module + Test the check_conf function """ + refinement.AbstractRefinement({"refinement_method": refinement_method}) # type: ignore[abstract] - @staticmethod - def test_check_conf(): - """ - Test the interpolation method - """ - refinement.AbstractRefinement({"refinement_method": "interpolation"}) # type: ignore[abstract] +@pytest.mark.parametrize( + "refinement_config", [{"refinement_method": "wta"}, {"refinement_method": "optical_flow", "nbr_iteration": 0}] +) +def test_check_conf_fails(refinement_config): + """ + Test the refinement check_conf with wrong configuration + """ - with pytest.raises(KeyError): - refinement.AbstractRefinement({"refinement_method": "wta"}) # type: ignore[abstract] + with pytest.raises((KeyError, DictCheckerError)): + refinement.AbstractRefinement(refinement_config) # type: ignore[abstract] - @staticmethod - def test_margins(): - """ - test margins of matching cost pipeline - """ - _refinement = refinement.AbstractRefinement({"refinement_method": "interpolation"}) # type: ignore[abstract] - assert _refinement.margins == Margins(3, 3, 3, 3), "Not a cubic kernel Margins" +def test_refinement_method_subpixel(cv_dataset): + """ + test refinement_method with interpolation + """ - @staticmethod - def test_refinement_method_subpixel(): - """ - test refinement - """ + cost_volumes_test = cv_dataset - cv = np.zeros((3, 3, 5, 5)) - cv[:, :, 2, 2] = np.ones([3, 3]) - cv[:, :, 2, 3] = np.ones([3, 3]) - cv[:, :, 3, 2] = np.ones([3, 3]) - cv[:, :, 3, 3] = np.ones([3, 3]) + data = np.full((3, 3), 0.4833878) - c_row = [0, 1, 2] - c_col = [0, 1, 2] + dataset_disp_map = common.dataset_disp_maps(data, data) - # First pixel in the image that is fully computable (aggregation windows are complete) - row = np.arange(c_row[0], c_row[-1] + 1) - col = np.arange(c_col[0], c_col[-1] + 1) + test = refinement.AbstractRefinement({"refinement_method": "interpolation"}) # type: ignore[abstract] + delta_x, delta_y = test.refinement_method(cost_volumes_test, dataset_disp_map, None, None) - disparity_range_col = np.arange(-2, 2 + 1) - disparity_range_row = np.arange(-2, 2 + 1) + np.testing.assert_allclose(data, delta_y, rtol=1e-06) + np.testing.assert_allclose(data, delta_x, rtol=1e-06) - cost_volumes_test = xr.Dataset( - {"cost_volumes": (["row", "col", "disp_col", "disp_row"], cv)}, - coords={"row": row, "col": col, "disp_col": disparity_range_col, "disp_row": disparity_range_row}, - ) - cost_volumes_test.attrs["measure"] = "zncc" - cost_volumes_test.attrs["window_size"] = 1 - cost_volumes_test.attrs["type_measure"] = "max" +def test_refinement_method_pixel(cv_dataset): + """ + test refinement + """ + + cost_volumes_test = cv_dataset + + new_cv_datas = np.zeros((3, 3, 5, 5)) + new_cv_datas[:, :, 1, 3] = np.ones([3, 3]) - data = np.array( - ([[0.4833878, 0.4833878, 0.4833878], [0.4833878, 0.4833878, 0.4833878], [0.4833878, 0.4833878, 0.4833878]]), - dtype=np.float64, - ) + cost_volumes_test["cost_volumes"].data = new_cv_datas - dataset_disp_map = common.dataset_disp_maps(data, data) + gt_delta_y = np.array( + ([[-1, -1, -1], [-1, -1, -1], [-1, -1, -1]]), + dtype=np.float64, + ) - test = refinement.AbstractRefinement({"refinement_method": "interpolation"}) # type: ignore[abstract] - delta_x, delta_y = test.refinement_method(cost_volumes_test, dataset_disp_map) + gt_delta_x = np.array( + ([[1, 1, 1], [1, 1, 1], [1, 1, 1]]), + dtype=np.float64, + ) - np.testing.assert_allclose(data, delta_y, rtol=1e-06) - np.testing.assert_allclose(data, delta_x, rtol=1e-06) + dataset_disp_map = common.dataset_disp_maps(gt_delta_y, gt_delta_x) - @staticmethod - def test_refinement_method_pixel(): - """ - test refinement - """ + test = refinement.AbstractRefinement({"refinement_method": "interpolation"}) # type: ignore[abstract] + delta_x, delta_y = test.refinement_method(cost_volumes_test, dataset_disp_map, None, None) - cv = np.zeros((3, 3, 5, 5)) - cv[:, :, 1, 3] = np.ones([3, 3]) + np.testing.assert_allclose(gt_delta_y, delta_y, rtol=1e-06) + np.testing.assert_allclose(gt_delta_x, delta_x, rtol=1e-06) - c_row = [0, 1, 2] - c_col = [0, 1, 2] - # First pixel in the image that is fully computable (aggregation windows are complete) - row = np.arange(c_row[0], c_row[-1] + 1) - col = np.arange(c_col[0], c_col[-1] + 1) +def test_optical_flow_margins(): + """ + test get_margins of refinement pipeline + """ + gt = (2, 2, 2, 2) # with 5 has default window size + _refinement = refinement.AbstractRefinement({"refinement_method": "optical_flow"}) # type: ignore[abstract] + + r_margins = _refinement.margins.astuple() + + assert r_margins == gt + + +def test_reshape_to_matching_cost_window_left(dataset_image): + """ + Test reshape_to_matching_cost_window function for a left image + """ + + img = dataset_image + + offset = 1 + nb_row = 6 + nb_col = 5 + + nb_valid_points_row = nb_row - 2 * offset + nb_valid_points_col = nb_col - 2 * offset + + refinement_class = refinement.AbstractRefinement({"refinement_method": "optical_flow"}) # type: ignore[abstract] + refinement_class._window_size = 3 + + # for left image + reshaped_left = refinement_class.reshape_to_matching_cost_window(img, [nb_valid_points_col, nb_valid_points_row]) + + # test four matching_cost + idx_1_1 = [[0, 1, 2], [5, 6, 7], [10, 11, 12]] + idx_2_2 = [[6, 7, 8], [11, 12, 13], [16, 17, 18]] + idx_3_3 = [[12, 13, 14], [17, 18, 19], [22, 23, 24]] + idx_4_1 = [[15, 16, 17], [20, 21, 22], [25, 26, 27]] + + assert np.array_equal(reshaped_left[:, :, 0], idx_1_1) + assert np.array_equal(reshaped_left[:, :, 4], idx_2_2) + assert np.array_equal(reshaped_left[:, :, 8], idx_3_3) + assert np.array_equal(reshaped_left[:, :, 9], idx_4_1) + + +def test_reshape_to_matching_cost_window_right(dataset_image): + """ + Test reshape_to_matching_cost_window function for a right image + """ + + img = dataset_image + + offset = 1 + nb_row = 6 + nb_col = 5 + + nb_valid_points_row = nb_row - 2 * offset + nb_valid_points_col = nb_col - 2 * offset + + refinement_class = refinement.AbstractRefinement({"refinement_method": "optical_flow"}) # type: ignore[abstract] + refinement_class._window_size = 3 + + # Create disparity maps + col_disp_map = [2, 0, 0, 0, 1, 0, 0, 0, 1, -2, 0, 0] + row_disp_map = [2, 0, 0, 0, -1, 0, 0, 0, 0, 1, 0, 0] + + # for right image + reshaped_right = refinement_class.reshape_to_matching_cost_window( + img, [nb_valid_points_col, nb_valid_points_row], row_disp_map, col_disp_map + ) + + # test four matching_cost + idx_1_1 = [[12, 13, 14], [17, 18, 19], [22, 23, 24]] + idx_2_2 = [[2, 3, 4], [7, 8, 9], [12, 13, 14]] + + assert np.array_equal(reshaped_right[:, :, 0], idx_1_1) + assert np.array_equal(reshaped_right[:, :, 4], idx_2_2) + + +def test_warped_image_without_step(): + """ + test warped image + """ + + refinement_class = refinement.AbstractRefinement({"refinement_method": "optical_flow"}) # type: ignore[abstract] - disparity_range_col = np.arange(-2, 2 + 1) - disparity_range_row = np.arange(-2, 2 + 1) + img = np.arange(30).reshape((5, 6)) + mc_1 = np.array( + [[0, 1, 2, 3, 4], [6, 7, 8, 9, 10], [12, 13, 14, 15, 16], [18, 19, 20, 21, 22], [24, 25, 26, 27, 28]] + ) + mc_2 = np.array( + [[1, 2, 3, 4, 5], [7, 8, 9, 10, 11], [13, 14, 15, 16, 17], [19, 20, 21, 22, 23], [25, 26, 27, 28, 29]] + ) - cost_volumes_test = xr.Dataset( - {"cost_volumes": (["row", "col", "disp_col", "disp_row"], cv)}, - coords={"row": row, "col": col, "disp_col": disparity_range_col, "disp_row": disparity_range_row}, - ) + left_img = xr.Dataset( + {"im": (["row", "col"], img)}, coords={"row": np.arange(img.shape[0]), "col": np.arange(img.shape[1])} + ) - cost_volumes_test.attrs["measure"] = "zncc" - cost_volumes_test.attrs["window_size"] = 1 - cost_volumes_test.attrs["type_measure"] = "max" + reshaped_right = np.stack((mc_1, mc_2)).transpose((1, 2, 0)) - gt_delta_y = np.array( - ([[-1, -1, -1], [-1, -1, -1], [-1, -1, -1]]), - dtype=np.float64, - ) + delta_row = 3 * np.ones(2) + delta_col = np.ones(2) - gt_delta_x = np.array( - ([[1, 1, 1], [1, 1, 1], [1, 1, 1]]), - dtype=np.float64, - ) + test_img_shift = refinement_class.warped_img(reshaped_right, delta_row, delta_col, left_img, [0, 1]) - dataset_disp_map = common.dataset_disp_maps(gt_delta_y, gt_delta_x) + gt_mc_1 = np.array( + [[19, 20, 21, 22, 22], [25, 26, 27, 28, 28], [25, 26, 27, 28, 28], [19, 20, 21, 22, 22], [13, 14, 15, 16, 16]] + ) - test = refinement.AbstractRefinement({"refinement_method": "interpolation"}) # type: ignore[abstract] - delta_x, delta_y = test.refinement_method(cost_volumes_test, dataset_disp_map) + gt_mc_2 = np.array( + [[20, 21, 22, 23, 23], [26, 27, 28, 29, 29], [26, 27, 28, 29, 29], [20, 21, 22, 23, 23], [14, 15, 16, 17, 17]] + ) - np.testing.assert_allclose(gt_delta_y, delta_y, rtol=1e-06) - np.testing.assert_allclose(gt_delta_x, delta_x, rtol=1e-06) + # check that the generated image is equal to ground truth + assert np.array_equal(gt_mc_1, test_img_shift[:, :, 0]) + assert np.array_equal(gt_mc_2, test_img_shift[:, :, 1]) From f1d530cbf5ea641f5e1b47c9be86e5dbea78d5e5 Mon Sep 17 00:00:00 2001 From: Quentin Fardet Date: Fri, 26 Jan 2024 16:13:45 +0100 Subject: [PATCH 07/14] refactor: optimization on lucas-kanade function to redude time consumption --- pandora2d/refinement/optical_flow.py | 23 ++++++++++++----------- 1 file changed, 12 insertions(+), 11 deletions(-) diff --git a/pandora2d/refinement/optical_flow.py b/pandora2d/refinement/optical_flow.py index 5a33769..17fe042 100644 --- a/pandora2d/refinement/optical_flow.py +++ b/pandora2d/refinement/optical_flow.py @@ -173,10 +173,12 @@ def warped_img( nb_row = left_img.dims["row"] step_row, step_col = self._step - coords_range = [row * nb_col + col - for row in np.arange(0, nb_row, step_row) - for col in np.arange(0, nb_col, step_col) - if row * nb_col + col in index_to_compute] + coords_range = [ + row * nb_col + col + for row in np.arange(0, nb_row, step_row) + for col in np.arange(0, nb_col, step_col) + if row * nb_col + col in index_to_compute + ] x, y = np.meshgrid(range(self._window_size), range(self._window_size)) @@ -204,19 +206,18 @@ def lucas_kanade_core_algorithm(self, left_data: np.ndarray, right_data: np.ndar :rtype: Tuple[float, float] """ - grad_x = np.gradient(left_data, axis=1) - grad_y = np.gradient(left_data, axis=0) + grad_y, grad_x = np.gradient(left_data) grad_t = left_data - right_data # Create A (grad_matrix) et B (time_matrix) matrix for Lucas Kanade grad_matrix = np.vstack((grad_x.flatten(), grad_y.flatten())).T - time_matrix = np.reshape(grad_t, len(grad_t) ** 2)[np.newaxis].T + time_matrix = grad_t.flatten() + + # Apply least-squares to solve the matrix equation AV= B where A is matrix containing partial derivate of (x,y) + # B the matrix of partial derivate of t and V the motion we want to find - # v = (A^T.A)^-1.A^T.B try: - motion = tuple( - np.matmul(np.linalg.inv(np.matmul(grad_matrix.T, grad_matrix)), np.matmul(grad_matrix.T, time_matrix)) - ) + motion = np.linalg.lstsq(grad_matrix, time_matrix, rcond=None)[0] # if matrix is full of NaN or 0 except np.linalg.LinAlgError: motion = (self._invalid_disp, self._invalid_disp) From b8555636436f6caa6e43fc20812d7a1e7d3464cd Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Alice=20de=20Bardonn=C3=A8che-Richard?= Date: Thu, 25 Jan 2024 17:23:30 +0100 Subject: [PATCH 08/14] minor: align algorithm convention & better step usage --- pandora2d/refinement/optical_flow.py | 96 +++++++++++++--------------- 1 file changed, 44 insertions(+), 52 deletions(-) diff --git a/pandora2d/refinement/optical_flow.py b/pandora2d/refinement/optical_flow.py index 17fe042..131078e 100644 --- a/pandora2d/refinement/optical_flow.py +++ b/pandora2d/refinement/optical_flow.py @@ -86,31 +86,38 @@ def check_conf(self, cfg: Dict) -> Dict: return cfg def reshape_to_matching_cost_window( - self, img: xr.Dataset, valid_dims: list, drow: np.ndarray = None, dcol: np.ndarray = None + self, + img: xr.Dataset, + cost_volumes: xr.Dataset, + disp_row: np.ndarray = None, + disp_col: np.ndarray = None, ): """ Transform image from (nb_col, nb_row) to (window_size, window_size, nbcol*nbrow) :param img: image to reshape :type img: xr.Dataset - :param valid_dims: size of image without borders - :type valid_dims: list - :param drow: array dim [] containing all the row shift - :type drow: np.ndarray - :param dcol: array dim [] containing all the columns shift - :type dcol: np.ndarray + :param cost_volumes: cost_volumes 4D row, col, disp_col, disp_row + :type cost_volumes: xarray.Dataset + :param disp_row: array dim [] containing all the row shift + :type disp_row: np.ndarray + :param disp_col: array dim [] containing all the columns shift + :type disp_col: np.ndarray :return: array containing reshaped image [window_size, window_size, nbcol*nbrow] :rtype: np.ndarray """ # get numpy array datas for image img_data = img["im"].data - nb_row, nb_col = img_data.shape - # valid_dims[0]*valid_dims[1] - one_dim_size = np.prod(valid_dims) + offset = max(self.margins.astuple()) + + computable_col = cost_volumes.col.data[offset:-offset] + computable_row = cost_volumes.row.data[offset:-offset] + + one_dim_size = len(computable_row) * len(computable_col) - if drow is None and dcol is None: + if disp_row is None and disp_col is None: patches = np.lib.stride_tricks.sliding_window_view(img_data, [self._window_size, self._window_size]) patches = patches.reshape((one_dim_size, self._window_size, self._window_size)).transpose((1, 2, 0)) else: @@ -119,11 +126,15 @@ def reshape_to_matching_cost_window( patches = np.ndarray((self._window_size, self._window_size, one_dim_size)) idx = 0 - for row in range(offset, nb_row - offset): - for col in range(offset, nb_col - offset): + for row in computable_row: + for col in computable_col: - shift_col = 0 if np.isnan(dcol[idx]) or dcol[idx] == self._invalid_disp else int(dcol[idx]) - shift_row = 0 if np.isnan(drow[idx]) or drow[idx] == self._invalid_disp else int(drow[idx]) + shift_col = ( + 0 if np.isnan(disp_col[idx]) or disp_col[idx] == self._invalid_disp else int(disp_col[idx]) + ) + shift_row = ( + 0 if np.isnan(disp_row[idx]) or disp_row[idx] == self._invalid_disp else int(disp_row[idx]) + ) # get right pixel with his matching cost window patch = img_data[ @@ -142,12 +153,7 @@ def reshape_to_matching_cost_window( return patches def warped_img( - self, - right_reshape: np.ndarray, - delta_row: np.ndarray, - delta_col: np.ndarray, - left_img: xr.Dataset, - index_to_compute: list, + self, right_reshape: np.ndarray, delta_row: np.ndarray, delta_col: np.ndarray, index_to_compute: list ): """ Shifted matching_cost window with computed disparity @@ -158,36 +164,20 @@ def warped_img( :type delta_row: np.ndarray :param delta_col: columns disparity map :type delta_col: np.ndarray - :param left_img: left image dataset - :type left_img: xarray.Dataset :param index_to_compute: list containing all valid pixel for computing optical flow :type index_to_compute: list :return: new array containing shifted matching_cost windows :rtype: np.ndarray """ - if self._step == [1, 1]: - coords_range = index_to_compute - else: - nb_col = left_img.dims["col"] - nb_row = left_img.dims["row"] - step_row, step_col = self._step - - coords_range = [ - row * nb_col + col - for row in np.arange(0, nb_row, step_row) - for col in np.arange(0, nb_col, step_col) - if row * nb_col + col in index_to_compute - ] - x, y = np.meshgrid(range(self._window_size), range(self._window_size)) new_img = np.empty_like(right_reshape) # resample matching cost right windows - for idx in coords_range: + for idx in index_to_compute: shifted_img = map_coordinates( - right_reshape[:, :, idx], [y + delta_row[idx], x + delta_col[idx]], order=5, mode="reflect" + right_reshape[:, :, idx], [y - delta_row[idx], x - delta_col[idx]], order=5, mode="reflect" ) new_img[:, :, idx] = shifted_img @@ -207,7 +197,7 @@ def lucas_kanade_core_algorithm(self, left_data: np.ndarray, right_data: np.ndar """ grad_y, grad_x = np.gradient(left_data) - grad_t = left_data - right_data + grad_t = right_data - left_data # Create A (grad_matrix) et B (time_matrix) matrix for Lucas Kanade grad_matrix = np.vstack((grad_x.flatten(), grad_y.flatten())).T @@ -295,11 +285,6 @@ def refinement_method( # get offset offset = max(self.margins.astuple()) - # get dimensions - nb_row, nb_col = img_left["im"].data.shape - nb_valid_points_row = nb_row - 2 * offset - nb_valid_points_col = nb_col - 2 * offset - # get displacement map from disparity state initial_delta_row = disp_map["row_map"].data initial_delta_col = disp_map["col_map"].data @@ -309,12 +294,12 @@ def refinement_method( # reshape left and right datas # from (nbcol, nbrow) to (window_size, window_size, nbcol*nbrow) - reshaped_left = self.reshape_to_matching_cost_window(img_left, [nb_valid_points_col, nb_valid_points_row]) + reshaped_left = self.reshape_to_matching_cost_window(img_left, cost_volumes) reshaped_right = self.reshape_to_matching_cost_window( img_right, - [nb_valid_points_col, nb_valid_points_row], - drow=delta_row, - dcol=delta_col, + cost_volumes, + delta_row, + delta_col, ) idx_to_compute = np.arange(reshaped_left.shape[2]).tolist() @@ -325,10 +310,17 @@ def refinement_method( reshaped_left, reshaped_right, idx_to_compute ) - reshaped_right = self.warped_img(reshaped_right, computed_drow, computed_dcol, img_left, idx_to_compute) + reshaped_right = self.warped_img(reshaped_right, computed_drow, computed_dcol, idx_to_compute) + + # Pandora convention is left - d = right + # Lucas&Kanade convention is left + d = right + delta_col = delta_col - computed_dcol + delta_row = delta_row - computed_drow - delta_col = delta_col + computed_dcol - delta_row = delta_row + computed_drow + # get finals disparity map dimensions + nb_row, nb_col = initial_delta_col.shape + nb_valid_points_row = nb_row - 2 * offset + nb_valid_points_col = nb_col - 2 * offset delta_col = delta_col.reshape([nb_valid_points_col, nb_valid_points_row]) delta_row = delta_row.reshape([nb_valid_points_col, nb_valid_points_row]) From ca3cb955d3c58f0369ccbb9f2642d5cc6f6122d0 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Alice=20de=20Bardonn=C3=A8che-Richard?= Date: Fri, 26 Jan 2024 10:02:39 +0100 Subject: [PATCH 09/14] test: fix step issues --- tests/test_refinement.py | 69 +++++++++++++++++++++++----------------- 1 file changed, 40 insertions(+), 29 deletions(-) diff --git a/tests/test_refinement.py b/tests/test_refinement.py index ec1e817..28a01f4 100644 --- a/tests/test_refinement.py +++ b/tests/test_refinement.py @@ -41,7 +41,9 @@ @pytest.fixture() def cv_dataset(): - """ " """ + """ + Create dataset cost volumes + """ cv = np.zeros((3, 3, 5, 5)) cv[:, :, 2, 2] = np.ones([3, 3]) @@ -49,8 +51,8 @@ def cv_dataset(): cv[:, :, 3, 2] = np.ones([3, 3]) cv[:, :, 3, 3] = np.ones([3, 3]) - c_row = [0, 1, 2] - c_col = [0, 1, 2] + c_row = np.arange(cv.shape[0]) + c_col = np.arange(cv.shape[1]) # First pixel in the image that is fully computable (aggregation windows are complete) row = np.arange(c_row[0], c_row[-1] + 1) @@ -192,18 +194,26 @@ def test_reshape_to_matching_cost_window_left(dataset_image): img = dataset_image - offset = 1 - nb_row = 6 - nb_col = 5 - - nb_valid_points_row = nb_row - 2 * offset - nb_valid_points_col = nb_col - 2 * offset - refinement_class = refinement.AbstractRefinement({"refinement_method": "optical_flow"}) # type: ignore[abstract] refinement_class._window_size = 3 + cv = np.zeros((6, 5, 5, 5)) + + disparity_range_col = np.arange(-2, 2 + 1) + disparity_range_row = np.arange(-2, 2 + 1) + + cost_volumes = xr.Dataset( + {"cost_volumes": (["row", "col", "disp_col", "disp_row"], cv)}, + coords={ + "row": np.arange(0, 6), + "col": np.arange(0, 5), + "disp_col": disparity_range_col, + "disp_row": disparity_range_row, + }, + ) + # for left image - reshaped_left = refinement_class.reshape_to_matching_cost_window(img, [nb_valid_points_col, nb_valid_points_row]) + reshaped_left = refinement_class.reshape_to_matching_cost_window(img, cost_volumes) # test four matching_cost idx_1_1 = [[0, 1, 2], [5, 6, 7], [10, 11, 12]] @@ -224,13 +234,6 @@ def test_reshape_to_matching_cost_window_right(dataset_image): img = dataset_image - offset = 1 - nb_row = 6 - nb_col = 5 - - nb_valid_points_row = nb_row - 2 * offset - nb_valid_points_col = nb_col - 2 * offset - refinement_class = refinement.AbstractRefinement({"refinement_method": "optical_flow"}) # type: ignore[abstract] refinement_class._window_size = 3 @@ -238,11 +241,24 @@ def test_reshape_to_matching_cost_window_right(dataset_image): col_disp_map = [2, 0, 0, 0, 1, 0, 0, 0, 1, -2, 0, 0] row_disp_map = [2, 0, 0, 0, -1, 0, 0, 0, 0, 1, 0, 0] - # for right image - reshaped_right = refinement_class.reshape_to_matching_cost_window( - img, [nb_valid_points_col, nb_valid_points_row], row_disp_map, col_disp_map + cv = np.zeros((6, 5, 5, 5)) + + disparity_range_col = np.arange(-2, 2 + 1) + disparity_range_row = np.arange(-2, 2 + 1) + + cost_volumes = xr.Dataset( + {"cost_volumes": (["row", "col", "disp_col", "disp_row"], cv)}, + coords={ + "row": np.arange(0, 6), + "col": np.arange(0, 5), + "disp_col": disparity_range_col, + "disp_row": disparity_range_row, + }, ) + # for right image + reshaped_right = refinement_class.reshape_to_matching_cost_window(img, cost_volumes, row_disp_map, col_disp_map) + # test four matching_cost idx_1_1 = [[12, 13, 14], [17, 18, 19], [22, 23, 24]] idx_2_2 = [[2, 3, 4], [7, 8, 9], [12, 13, 14]] @@ -258,7 +274,6 @@ def test_warped_image_without_step(): refinement_class = refinement.AbstractRefinement({"refinement_method": "optical_flow"}) # type: ignore[abstract] - img = np.arange(30).reshape((5, 6)) mc_1 = np.array( [[0, 1, 2, 3, 4], [6, 7, 8, 9, 10], [12, 13, 14, 15, 16], [18, 19, 20, 21, 22], [24, 25, 26, 27, 28]] ) @@ -266,16 +281,12 @@ def test_warped_image_without_step(): [[1, 2, 3, 4, 5], [7, 8, 9, 10, 11], [13, 14, 15, 16, 17], [19, 20, 21, 22, 23], [25, 26, 27, 28, 29]] ) - left_img = xr.Dataset( - {"im": (["row", "col"], img)}, coords={"row": np.arange(img.shape[0]), "col": np.arange(img.shape[1])} - ) - reshaped_right = np.stack((mc_1, mc_2)).transpose((1, 2, 0)) - delta_row = 3 * np.ones(2) - delta_col = np.ones(2) + delta_row = -3 * np.ones(2) + delta_col = -np.ones(2) - test_img_shift = refinement_class.warped_img(reshaped_right, delta_row, delta_col, left_img, [0, 1]) + test_img_shift = refinement_class.warped_img(reshaped_right, delta_row, delta_col, [0, 1]) gt_mc_1 = np.array( [[19, 20, 21, 22, 22], [25, 26, 27, 28, 28], [25, 26, 27, 28, 28], [19, 20, 21, 22, 22], [13, 14, 15, 16, 16]] From 854c78e913becab98aaf66bfd116fd032eab684d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Alice=20de=20Bardonn=C3=A8che-Richard?= Date: Tue, 16 Jan 2024 14:06:39 +0100 Subject: [PATCH 10/14] notebook: add notebook estimation and optical flow --- notebooks/estimation_step_explained.ipynb | 342 +++++++++++++++++++ notebooks/img/Pandora2D_pipeline.png | Bin 16619 -> 24639 bytes notebooks/introduction_and_basic_usage.ipynb | 29 +- 3 files changed, 359 insertions(+), 12 deletions(-) create mode 100644 notebooks/estimation_step_explained.ipynb diff --git a/notebooks/estimation_step_explained.ipynb b/notebooks/estimation_step_explained.ipynb new file mode 100644 index 0000000..1b05170 --- /dev/null +++ b/notebooks/estimation_step_explained.ipynb @@ -0,0 +1,342 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "db04320a-5fb9-47ca-8dcc-248e00941aa8", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "id": "f15f0456-611e-451f-87e6-dcf58e1ef190", + "metadata": {}, + "source": [ + "# Pandora2D : a coregistration framework" + ] + }, + { + "cell_type": "markdown", + "id": "15158305-7b79-4263-aeaa-16b39235f7e8", + "metadata": {}, + "source": [ + "# Introduction and basic usage" + ] + }, + { + "cell_type": "markdown", + "id": "e8458dd9-7977-4695-bdb5-047c47eec0b0", + "metadata": {}, + "source": [ + "#### Imports and external functions" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ac793218-8f2b-4559-9ef4-bcb6f917a59b", + "metadata": {}, + "outputs": [], + "source": [ + "import io\n", + "from pathlib import Path\n", + "from IPython.display import Image, display\n", + "from pprint import pprint" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dbbf6721-9115-44fb-9525-8e6d81938355", + "metadata": {}, + "outputs": [], + "source": [ + "from snippets.utils import *" + ] + }, + { + "cell_type": "markdown", + "id": "e4e477f5-6a2d-40c6-b747-7cf00791decb", + "metadata": {}, + "source": [ + "## Pandora2D's pipeline\n", + "\n", + "Pandora2D provides the following steps:\n", + "* estimation computation\n", + "* matching cost computation\n", + "* disparity computation (**mandatory if matching_cost**)\n", + "* subpixel disparity refinement" + ] + }, + { + "cell_type": "markdown", + "id": "1be05d02-b1dc-43ec-a09a-d65c8285ea44", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "id": "fdaacb98-cbac-4647-867c-ef110f17a85c", + "metadata": {}, + "source": [ + "## About the estimation step :" + ] + }, + { + "cell_type": "markdown", + "id": "25de08c8-52ab-436f-9bc5-c9b665e672cb", + "metadata": {}, + "source": [ + "1. used alone, it computes a constant a priori offset across the entire image in line and column. \n", + "\n", + "2. When used in a complete pipeline, it enables, **thanks to an interval entered by the user**, the calculation of \"col_disparity\" and \"row_disparity\" parameters in the input configuration dictionnary." + ] + }, + { + "cell_type": "markdown", + "id": "fa43b579-4d68-4c78-8a07-6c6ee05805e5", + "metadata": {}, + "source": [ + "The outputs are : \n", + "- shown in log in verbose mode\n", + "- saved in the configuration file\n", + "- stored in dataset image" + ] + }, + { + "cell_type": "markdown", + "id": "00469662-a597-4976-88df-1cd6b9c30b77", + "metadata": {}, + "source": [ + "# Pandora2D execution options with state machine" + ] + }, + { + "cell_type": "markdown", + "id": "548a5fd1-4c3b-4dc7-bba3-83114f84396b", + "metadata": {}, + "source": [ + "#### Imports of pandora2d" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4fabcfd6-e078-491c-86e9-407ff5eca137", + "metadata": {}, + "outputs": [], + "source": [ + "# Load pandora2d imports\n", + "import pandora2d\n", + "from pandora2d.state_machine import Pandora2DMachine\n", + "from pandora2d.check_configuration import check_conf\n", + "from pandora2d.img_tools import create_datasets_from_inputs" + ] + }, + { + "cell_type": "markdown", + "id": "21cc33a4-0264-443c-97c8-ad32b80d9c65", + "metadata": {}, + "source": [ + "#### Load and visualize input data " + ] + }, + { + "cell_type": "markdown", + "id": "6d44265d-decd-4157-817f-40bd1a3df0a5", + "metadata": {}, + "source": [ + "Provide image path" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8df92f0f-298e-4f1d-b5a2-f7bbf0622646", + "metadata": {}, + "outputs": [], + "source": [ + "# Paths to left and right images\n", + "img_left_path = \"data/left.tif\"\n", + "img_right_path = \"data/right.tif\"" + ] + }, + { + "cell_type": "markdown", + "id": "bfb900c7-9356-48be-9a3a-74e1ddb5b27e", + "metadata": {}, + "source": [ + "#### No need for disparity Range in the estimation process." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "22aed1c4-a53a-43bd-bbd3-10eb64b59e63", + "metadata": {}, + "outputs": [], + "source": [ + "user_cfg = {\n", + " \"input\": {\n", + " \"left\": {\n", + " \"img\": img_left_path, \n", + " \"nodata\": np.nan\n", + " },\n", + " \"right\": {\n", + " \"img\": img_right_path, \n", + " \"nodata\": np.nan\n", + " },\n", + " },\n", + " \"pipeline\": { \n", + " \"estimation\": {\n", + " \"estimation_method\": \"phase_cross_correlation\",\n", + " \"range_row\": 5, \n", + " \"range_col\": 5,\n", + " \"sample_factor\": 100\n", + " },\n", + " }\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2931b134-aaee-4086-a6b4-88cec3bc39f3", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "img_left, img_right = create_datasets_from_inputs(input_config=user_cfg[\"input\"], estimation_cfg=user_cfg[\"pipeline\"].get(\"estimation\"))" + ] + }, + { + "cell_type": "markdown", + "id": "4def9934-12f8-42cd-a05b-bc845a1a1620", + "metadata": {}, + "source": [ + "#### Instantiate the machine" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "47546952-4125-43b9-aaa1-71fe48cac2d8", + "metadata": {}, + "outputs": [], + "source": [ + "pandora2d_machine = Pandora2DMachine()" + ] + }, + { + "cell_type": "markdown", + "id": "d69483f3-7a28-4530-b286-ec40c64ecfb2", + "metadata": {}, + "source": [ + "#### Check the configuration and sequence of steps" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c085399b-eb82-4614-8135-3bf4bbcbf583", + "metadata": {}, + "outputs": [], + "source": [ + "checked_cfg = check_conf(user_cfg, pandora2d_machine)" + ] + }, + { + "cell_type": "markdown", + "id": "4cb3efad-3e1c-4c38-b0e1-2405d7431f3f", + "metadata": {}, + "source": [ + "#### Trigger all the steps of the machine at ones" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "efc291e7-03ef-4fa4-9aed-7eee6f12639a", + "metadata": {}, + "outputs": [], + "source": [ + "dataset, estimation_results = pandora2d.run(\n", + " pandora2d_machine,\n", + " img_left,\n", + " img_right,\n", + " checked_cfg\n", + " )" + ] + }, + { + "cell_type": "markdown", + "id": "c043bc01-12c8-4caf-b65d-1d46bcca90fb", + "metadata": {}, + "source": [ + "## The results are added to a configuration dictionnary " + ] + }, + { + "cell_type": "markdown", + "id": "3c4e99b3-5d7d-4bc2-8530-d0a70fd8c6be", + "metadata": {}, + "source": [ + "##### Disparities ranges are set" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ce0f5e8b-a4c5-4f52-955a-c8bffa49782c", + "metadata": {}, + "outputs": [], + "source": [ + "print(\"Disparity range for columns : \", estimation_results[\"input\"][\"col_disparity\"])\n", + "print(\"Disparity range for rows : \", estimation_results[\"input\"][\"row_disparity\"])" + ] + }, + { + "cell_type": "markdown", + "id": "a70b11c1-85bd-450d-86fa-11079a3a7355", + "metadata": {}, + "source": [ + "##### And many informations are stored in estimation dictionnary configuration" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5bef0454-425e-43ff-af66-b3d8cd90b31c", + "metadata": {}, + "outputs": [], + "source": [ + "estimation_results[\"pipeline\"][\"estimation\"]" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "pandora2D-dev", + "language": "python", + "name": "pandora2d-dev" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/img/Pandora2D_pipeline.png b/notebooks/img/Pandora2D_pipeline.png index c4b43ba05ab5c288c81d8f7a9303a96e237440b9..f396452e440a2a404efdb3cf92cde85b6cd81a02 100644 GIT binary patch literal 24639 zcmeHv1z1(vwlE+nAf3|ENT+m{D5a!yv&l_tx 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pandora2d/estimation/phase_cross_correlation.py | 1 - pandora2d/img_tools.py | 1 - pandora2d/refinement/__init__.py | 2 -- pandora2d/refinement/interpolation.py | 1 - pandora2d/refinement/optical_flow.py | 1 - pandora2d/refinement/refinement.py | 1 - pandora2d/state_machine.py | 1 - tests/test_common.py | 1 + tests/test_estimation.py | 2 -- tests/test_refinement.py | 1 - 14 files changed, 1 insertion(+), 16 deletions(-) diff --git a/pandora2d/check_configuration.py b/pandora2d/check_configuration.py index c0b320c..24e65b9 100644 --- a/pandora2d/check_configuration.py +++ b/pandora2d/check_configuration.py @@ -1,5 +1,4 @@ #!/usr/bin/env python -# coding: utf8 # # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). # Copyright (c) 2024 CS GROUP France diff --git a/pandora2d/common.py b/pandora2d/common.py index f8a6427..e8a206c 100644 --- a/pandora2d/common.py +++ b/pandora2d/common.py @@ -1,5 +1,4 @@ #!/usr/bin/env python -# coding: utf8 # # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). # Copyright (c) 2024 CS GROUP France diff --git a/pandora2d/estimation/__init__.py b/pandora2d/estimation/__init__.py index 8313cef..8846ad9 100644 --- a/pandora2d/estimation/__init__.py +++ b/pandora2d/estimation/__init__.py @@ -1,5 +1,3 @@ -#!/usr/bin/env python -# coding: utf8 # # Copyright (c) 2024 CS GROUP France # diff --git a/pandora2d/estimation/estimation.py b/pandora2d/estimation/estimation.py index 97c9ad1..d7a933d 100644 --- a/pandora2d/estimation/estimation.py +++ b/pandora2d/estimation/estimation.py @@ -1,5 +1,4 @@ #!/usr/bin/env python -# coding: utf8 # # Copyright (c) 2024 CS GROUP France # diff --git a/pandora2d/estimation/phase_cross_correlation.py b/pandora2d/estimation/phase_cross_correlation.py index 576e737..b9a3750 100644 --- a/pandora2d/estimation/phase_cross_correlation.py +++ b/pandora2d/estimation/phase_cross_correlation.py @@ -1,5 +1,4 @@ #!/usr/bin/env python -# coding: utf8 # # Copyright (c) 2024 CS GROUP France # diff --git a/pandora2d/img_tools.py b/pandora2d/img_tools.py index b8cdb88..8b41e3b 100644 --- a/pandora2d/img_tools.py +++ b/pandora2d/img_tools.py @@ -1,5 +1,4 @@ #!/usr/bin/env python -# coding: utf8 # # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). # Copyright (c) 2024 CS GROUP France diff --git a/pandora2d/refinement/__init__.py b/pandora2d/refinement/__init__.py index 5c53fd6..1f58be2 100644 --- a/pandora2d/refinement/__init__.py +++ b/pandora2d/refinement/__init__.py @@ -1,5 +1,3 @@ -#!/usr/bin/env python -# coding: utf8 # # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). # Copyright (c) 2024 CS GROUP France diff --git a/pandora2d/refinement/interpolation.py b/pandora2d/refinement/interpolation.py index 6867a80..cdd0f07 100644 --- a/pandora2d/refinement/interpolation.py +++ b/pandora2d/refinement/interpolation.py @@ -1,5 +1,4 @@ #!/usr/bin/env python -# coding: utf8 # # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). # Copyright (c) 2024 CS GROUP France diff --git a/pandora2d/refinement/optical_flow.py b/pandora2d/refinement/optical_flow.py index 131078e..b0e45d5 100644 --- a/pandora2d/refinement/optical_flow.py +++ b/pandora2d/refinement/optical_flow.py @@ -1,5 +1,4 @@ #!/usr/bin/env python -# coding: utf8 # # Copyright (c) 2024 CS GROUP France # diff --git a/pandora2d/refinement/refinement.py b/pandora2d/refinement/refinement.py index 3c4eaba..18f6bfd 100644 --- a/pandora2d/refinement/refinement.py +++ b/pandora2d/refinement/refinement.py @@ -1,5 +1,4 @@ #!/usr/bin/env python -# coding: utf8 # # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). # Copyright (c) 2024 CS GROUP France diff --git a/pandora2d/state_machine.py b/pandora2d/state_machine.py index b5b4a18..e3797c7 100644 --- a/pandora2d/state_machine.py +++ b/pandora2d/state_machine.py @@ -1,5 +1,4 @@ #!/usr/bin/env python -# coding: utf8 # # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). # Copyright (c) 2024 CS GROUP France diff --git a/tests/test_common.py b/tests/test_common.py index e6d90d3..17b7783 100644 --- a/tests/test_common.py +++ b/tests/test_common.py @@ -2,6 +2,7 @@ # coding: utf8 # # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). +# Copyright (c) 2024 CS GROUP France # # This file is part of PANDORA2D # diff --git a/tests/test_estimation.py b/tests/test_estimation.py index 42f79dc..aac15f7 100644 --- a/tests/test_estimation.py +++ b/tests/test_estimation.py @@ -1,7 +1,5 @@ #!/usr/bin/env python -# coding: utf8 # -# Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). # Copyright (c) 2024 CS GROUP France # # This file is part of PANDORA2D diff --git a/tests/test_refinement.py b/tests/test_refinement.py index 28a01f4..78d5ce6 100644 --- a/tests/test_refinement.py +++ b/tests/test_refinement.py @@ -1,5 +1,4 @@ #!/usr/bin/env python -# coding: utf8 # # Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES). # Copyright (c) 2024 CS GROUP France From 68d827adbe3cbc55187d6455658e7078ebdd596a Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Alice=20de=20Bardonn=C3=A8che-Richard?= Date: Wed, 17 Jan 2024 11:16:54 +0100 Subject: [PATCH 12/14] doc: add optical flow and phase cross correlation documentation --- docs/source/Images/Pandora2D_pipeline.png | Bin 15517 -> 17385 bytes docs/source/Images/estimation_schema.png | Bin 0 -> 145414 bytes docs/source/Images/img_pipeline/dp_step.png | Bin 3542 -> 4355 bytes .../Images/img_pipeline/estimation_step.png | Bin 0 -> 4226 bytes docs/source/Images/img_pipeline/mc_step.png | Bin 4393 -> 4673 bytes docs/source/Images/img_pipeline/refi_step.png | Bin 1712 -> 4059 bytes docs/source/Images/optical_flow_schema.png | Bin 0 -> 255283 bytes docs/source/Images/range_schema.png | Bin 0 -> 300415 bytes docs/source/exploring_the_field.rst | 9 ++ .../exploring_the_field/initial_disparity.rst | 38 ++++++ .../refining_disparity.rst | 12 ++ docs/source/index.rst | 2 + docs/source/userguide/as_an_api.rst | 16 +-- docs/source/userguide/input.rst | 4 +- docs/source/userguide/output.rst | 2 +- docs/source/userguide/overview.rst | 14 ++- docs/source/userguide/sequencing.rst | 8 +- docs/source/userguide/step_by_step.rst | 2 +- .../userguide/step_by_step/estimation.rst | 97 ++++++++++++++ .../userguide/step_by_step/refinement.rst | 118 +++++++++++++++--- .../estimation/phase_cross_correlation.py | 2 +- 21 files changed, 282 insertions(+), 42 deletions(-) create mode 100644 docs/source/Images/estimation_schema.png create mode 100644 docs/source/Images/img_pipeline/estimation_step.png create mode 100644 docs/source/Images/optical_flow_schema.png create mode 100644 docs/source/Images/range_schema.png create mode 100644 docs/source/exploring_the_field.rst create mode 100644 docs/source/exploring_the_field/initial_disparity.rst create mode 100644 docs/source/exploring_the_field/refining_disparity.rst create mode 100644 docs/source/userguide/step_by_step/estimation.rst diff --git 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b/docs/source/userguide/sequencing.rst index a3d4f64..79141fc 100644 --- a/docs/source/userguide/sequencing.rst +++ b/docs/source/userguide/sequencing.rst @@ -7,10 +7,12 @@ transition defined by the Pandora2D Machine (`transitions `__ + + +Configuration and parameters +---------------------------- +.. warning:: + + You don't need to set disparities in input section if you set the estimation step + +.. list-table:: Parameters + :header-rows: 1 + + + * - Name + - Description + - Type + - Default value + - Available value + - Required + * - *estimation_method* + - estimation measure + - string + - + - "phase_cross_correlation" + - Yes + * - *range_col* + - Exploration around the initial disparity for columns + - int + - 5 + - >0, odd number + - No + * - *range_row* + - Exploration around the initial disparity for rows + - int + - 5 + - >0, odd number + - No + * - *sample_factor* + - | Upsampling factor. + | Images will be registered to within 1 / upsample_factor of a pixel + - int + - 1 + - >= 1 + - No + + +**Example** + +.. sourcecode:: text + + { + "input" : + { + ... + }, + "pipeline" : + { + "estimation": + { + "estimation_method": "phase_cross_correlation", + "range_col": 5, + "range_row": 5, + "sample_factor": 20 + } + ... + } + } + + +Outputs: +-------- + +- Showed in log in verbose mode +- Written in the output configuration file +- Stored in the inputs_dataset \ No newline at end of file diff --git a/docs/source/userguide/step_by_step/refinement.rst b/docs/source/userguide/step_by_step/refinement.rst index e388c7c..72d4f63 100644 --- a/docs/source/userguide/step_by_step/refinement.rst +++ b/docs/source/userguide/step_by_step/refinement.rst @@ -2,25 +2,100 @@ Refinement of the disparity maps ================================ - -Theoretical basics ------------------- The purpose of this step is to refine the disparity identified in the previous step. -The available refinement methods are: - * **Interpolation**: +Interpolation method +-------------------- + +It consists on 3 different steps: + + * First, the cost_volumes is reshaped to obtain the 2D (disp_row, disp_col) costs map for each pixel, so we will obtain (row * col) 2D cost maps. + * The cost map of each pixel is interpolated using scipy to obtain a continuous function. + * Then, the interpolated functions are minimized using scipy to obtain the refined disparities. + +Optical_flow method +------------------- + +Inspired by [Lucas & Kanade]_.'s algorithm + + * We first need to suppose that pixel's shifting are subpixel between left and right images. + * Second, we need to suppose brightness constancy between left and right images. (2) + * Now, we can write : + + .. math:: + + I(x, y, t) &= I(x + dx, y + dy, t + dt) \\ + I(x, y, t) &= I(x, y, t) + \frac{\partial I}{\partial x}\partial x + \frac{\partial I}{\partial y}\partial y +\frac{\partial I}{\partial t}\partial t + + with hypothesis (2) : + + .. math:: + + \frac{\partial I}{\partial x} dx + \frac{\partial I}{\partial y} dy + \frac{\partial I}{\partial t}dt = 0 + + after dividing by :math:`dt`: + + .. math:: + + \frac{\partial I}{\partial x} \frac{dx}{dt} + \frac{\partial I}{\partial y} \frac{dy}{dt} = - \frac{\partial I}{\partial t} + + * We can resolve v thanks to least squares method : + + .. math:: + + v = (A^T A)^{-1}A^T B + + * Lucas & Kanade works on a pixel and his neighbourhood so : + + .. math:: + + A = + \left(\begin{array}{cc} + I_x(q1) & I_y(q1)\\ + I_x(q2) & I_y(q2) \\ + . & . \\ + . & . \\ + . & . \\ + I_x(qn) & I_y(qn) + \end{array}\right) + + v = + \left(\begin{array}{cc} + V_x\\ + V_y + \end{array}\right) + + + B = + \left(\begin{array}{cc} + -I_t(q1) \\ + -I_t(q2) \\ + . \\ + . \\ + . \\ + -I_t(qn) + \end{array}\right) + +The following diagram presents the different steps implemented in Pandora2d to enable +the refinement of the disparity map with optical flow. + +.. [Lucas & Kanade] An iterative image registration technique with an application to stereo vision. + Proceedings of Imaging Understanding Workshop, pages 121--130. + +.. figure:: ../../Images/optical_flow_schema.png + :width: 1000px + :height: 200px + +Dichotomy method +---------------- + +It’s an iterative process that will, at each iteration: + * compute the half way positions between each best candidate in the cost volume and its nearest neighbours. + * compute the similarity coefficients at those positions using the given filter method. + * find the new best candidate from those computed coefficients. - It consists on 3 different steps: - * First, the cost_volumes is reshaped to obtain the 2D (disp_row, disp_col) costs map for each pixel, so we will obtain (row * col) 2D cost maps. - * The cost map of each pixel is interpolated using scipy to obtain a continuous function. - * Then, the interpolated functions are minimized using scipy to obtain the refined disparities. - * **Dichotomy**: - It’s an iterative process that will, at each iteration: - * compute the half way positions between each best candidate in the cost volume and its nearest neighbours. - * compute the similarity coefficients at those positions using the given filter method. - * find the new best candidate from those computed coefficients. Configuration and parameters ---------------------------- @@ -34,20 +109,23 @@ Configuration and parameters - Default value - Available value - Required - * - *refinemement_method* + * - *refinement_method* - Refinement method - string - - | "interpolation", | "dichotomy", + | "optical_flow" - Yes * - *iterations* - - Number of iterations + - Number of iterations (not available for interpolation) - integer - - - - | 1 to 9 + - 4 for **optical_flow** method + - | **Dichotomy** + | 1 to 9 | *if above, will be bound to 9* - | **Only available if "dichotomy" method** + | **Optical flow** + | >0 - Yes * - *filter* - Name of the filter to use @@ -74,7 +152,7 @@ Configuration and parameters // ... "refinement": { - "refinement_method": "interpolation" + "refinement_method": "optical_flow" }, // ... } diff --git a/pandora2d/estimation/phase_cross_correlation.py b/pandora2d/estimation/phase_cross_correlation.py index b9a3750..903a2d0 100644 --- a/pandora2d/estimation/phase_cross_correlation.py +++ b/pandora2d/estimation/phase_cross_correlation.py @@ -107,7 +107,7 @@ def compute_estimation(self, img_left: xr.Dataset, img_right: xr.Dataset) -> Tup :return: row disparity: list col disparity: list Calculated shifts: np.ndarray - Extra information about estimation: dict + Extra information about estimation: dict :rtype: list, list, np.ndarray, dict """ From cb187bdf8be42f5fa50665e11af695ac44fcf579 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Alice=20de=20Bardonn=C3=A8che-Richard?= Date: Fri, 9 Feb 2024 14:40:25 +0100 Subject: [PATCH 13/14] minor: adapt to dichotomy implementation --- .../userguide/step_by_step/refinement.rst | 5 ++- notebooks/introduction_and_basic_usage.ipynb | 6 +-- pandora2d/refinement/dichotomy.py | 15 +++++-- pandora2d/refinement/optical_flow.py | 42 +++++++++---------- pandora2d/refinement/refinement.py | 6 ++- tests/test_dichotomy.py | 2 +- tests/test_refinement.py | 2 +- 7 files changed, 46 insertions(+), 32 deletions(-) diff --git a/docs/source/userguide/step_by_step/refinement.rst b/docs/source/userguide/step_by_step/refinement.rst index 72d4f63..4dc1c3e 100644 --- a/docs/source/userguide/step_by_step/refinement.rst +++ b/docs/source/userguide/step_by_step/refinement.rst @@ -126,7 +126,10 @@ Configuration and parameters | *if above, will be bound to 9* | **Optical flow** | >0 - - Yes + - | **Dichotomy** + | Yes + | **Optical flow** + | No * - *filter* - Name of the filter to use - str diff --git a/notebooks/introduction_and_basic_usage.ipynb b/notebooks/introduction_and_basic_usage.ipynb index 33c0083..aa8636f 100644 --- a/notebooks/introduction_and_basic_usage.ipynb +++ b/notebooks/introduction_and_basic_usage.ipynb @@ -347,7 +347,7 @@ " },\n", " \"refinement\" : {\n", " \"refinement_method\" : \"optical_flow\",\n", - " \"nbr_iteration\": 4\n", + " \"iterations\": 4\n", " }\n", " }\n", "}" @@ -547,7 +547,7 @@ " },\n", " \"refinement\":{\n", " \"refinement_method\" : \"optical_flow\",\n", - " \"nbr_iteration\": 4\n", + " \"iterations\": 4\n", " }\n", " }\n", "}" @@ -775,7 +775,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.16" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/pandora2d/refinement/dichotomy.py b/pandora2d/refinement/dichotomy.py index 3e972f2..685bb95 100644 --- a/pandora2d/refinement/dichotomy.py +++ b/pandora2d/refinement/dichotomy.py @@ -1,4 +1,5 @@ # Copyright (c) 2024 Centre National d'Etudes Spatiales (CNES). +# Copyright (c) 2024 CS GROUP France # # This file is part of PANDORA2D # @@ -66,14 +67,20 @@ def check_conf(cls, cfg: Dict) -> Dict: def margins(self): return Margins(2, 2, 2, 2) - def refinement_method(self, cost_volumes: xr.Dataset, pixel_maps: xr.Dataset) -> None: + def refinement_method( + self, cost_volumes: xr.Dataset, disp_map: xr.Dataset, img_left: xr.Dataset, img_right: xr.Dataset + ) -> None: """ Return the subpixel disparity maps :param cost_volumes: cost_volumes 4D row, col, disp_col, disp_row - :type cost_volumes: xarray.dataset - :param pixel_maps: pixels disparity maps - :type pixel_maps: xarray.dataset + :type cost_volumes: xarray.Dataset + :param disp_map: pixel disparity maps + :type disp_map: xarray.Dataset + param img_left: left image dataset + :type img_left: xarray.Dataset + :param img_right: right image dataset + :type img_right: xarray.Dataset :return: the refined disparity maps :rtype: Tuple[np.ndarray, np.ndarray] """ diff --git a/pandora2d/refinement/optical_flow.py b/pandora2d/refinement/optical_flow.py index b0e45d5..3555512 100644 --- a/pandora2d/refinement/optical_flow.py +++ b/pandora2d/refinement/optical_flow.py @@ -25,7 +25,7 @@ import numpy as np import xarray as xr -from json_checker import And, Checker +from json_checker import And from scipy.ndimage import map_coordinates from pandora.margins import Margins @@ -38,30 +38,32 @@ class OpticalFlow(refinement.AbstractRefinement): OpticalFLow class allows to perform the subpixel cost refinement step """ - _nbr_iteration = None + _iterations = None _invalid_disp = None - _NBR_ITERATION = 4 + _ITERATIONS = 4 + + schema = {"refinement_method": And(str, lambda x: x in ["optical_flow"]), "iterations": And(int, lambda it: it > 0)} def __init__(self, cfg: dict = None, step: list = None, window_size: int = 5) -> None: """ :param cfg: optional configuration, {} :type cfg: dict + :param step: list containing row and col step + :type step: list + :param window_size: window size + :type window_size: int :return: None """ + super().__init__(cfg) - self.cfg = self.check_conf(cfg) - self._nbr_iteration = self.cfg["nbr_iteration"] + self._iterations = self.cfg["iterations"] self._refinement_method = self.cfg["refinement_method"] self._window_size = window_size self._step = [1, 1] if step is None else step - @property - def margins(self): - values = (self._window_size // 2 * ele for _ in range(2) for ele in self._step) - return Margins(*values) - - def check_conf(self, cfg: Dict) -> Dict: + @classmethod + def check_conf(cls, cfg: Dict) -> Dict: """ Check the refinement configuration @@ -71,19 +73,17 @@ def check_conf(self, cfg: Dict) -> Dict: :rtype: cfg: dict """ - if "nbr_iteration" not in cfg: - cfg["nbr_iteration"] = self._NBR_ITERATION + cfg["iterations"] = cfg.get("iterations", cls._ITERATIONS) - schema = { - "refinement_method": And(str, lambda x: x in ["optical_flow"]), - "nbr_iteration": And(int, lambda nbr_i: nbr_i > 0), - } - - checker = Checker(schema) - checker.validate(cfg) + cfg = super().check_conf(cfg) return cfg + @property + def margins(self): + values = (self._window_size // 2 * ele for _ in range(2) for ele in self._step) + return Margins(*values) + def reshape_to_matching_cost_window( self, img: xr.Dataset, @@ -303,7 +303,7 @@ def refinement_method( idx_to_compute = np.arange(reshaped_left.shape[2]).tolist() - for _ in range(self._nbr_iteration): + for _ in range(self._iterations): computed_drow, computed_dcol, idx_to_compute = self.optical_flow( reshaped_left, reshaped_right, idx_to_compute diff --git a/pandora2d/refinement/refinement.py b/pandora2d/refinement/refinement.py index 18f6bfd..876a74a 100644 --- a/pandora2d/refinement/refinement.py +++ b/pandora2d/refinement/refinement.py @@ -112,10 +112,14 @@ def decorator(subclass): return decorator - def __init__(self, cfg: Dict) -> None: + def __init__(self, cfg: Dict, _: list = None, __: int = 5) -> None: """ :param cfg: optional configuration, {} :type cfg: dict + :param step: list containing row and col step + :type step: list + :param window_size: window size + :type window_size: int :return: None """ self.cfg = self.check_conf(cfg) diff --git a/tests/test_dichotomy.py b/tests/test_dichotomy.py index ba68da0..70ca24d 100644 --- a/tests/test_dichotomy.py +++ b/tests/test_dichotomy.py @@ -120,7 +120,7 @@ def test_refinement_method(config, caplog, mocker: MockerFixture): dichotomy_instance = refinement.dichotomy.Dichotomy(config) # We can pass anything as it is not yet implemented - dichotomy_instance.refinement_method(mocker.ANY, mocker.ANY) + dichotomy_instance.refinement_method(mocker.ANY, mocker.ANY, mocker.ANY, mocker.ANY) assert "refinement_method of Dichotomy not yet implemented" in caplog.messages diff --git a/tests/test_refinement.py b/tests/test_refinement.py index 78d5ce6..8d6fc68 100644 --- a/tests/test_refinement.py +++ b/tests/test_refinement.py @@ -114,7 +114,7 @@ def test_check_conf_passes(refinement_method): @pytest.mark.parametrize( - "refinement_config", [{"refinement_method": "wta"}, {"refinement_method": "optical_flow", "nbr_iteration": 0}] + "refinement_config", [{"refinement_method": "wta"}, {"refinement_method": "optical_flow", "iterations": 0}] ) def test_check_conf_fails(refinement_config): """ From cac35bd01ec0d7b4777712e677de5c7c8a7b2d63 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Alice=20de=20Bardonn=C3=A8che-Richard?= Date: Tue, 13 Feb 2024 16:47:05 +0100 Subject: [PATCH 14/14] minor: add warning about optical flow --- docs/source/exploring_the_field/refining_disparity.rst | 3 +++ docs/source/userguide/step_by_step/refinement.rst | 2 ++ pandora2d/common.py | 2 +- pandora2d/refinement/dichotomy.py | 2 +- pandora2d/state_machine.py | 4 ++++ 5 files changed, 11 insertions(+), 2 deletions(-) diff --git a/docs/source/exploring_the_field/refining_disparity.rst b/docs/source/exploring_the_field/refining_disparity.rst index 6452d51..5408c02 100644 --- a/docs/source/exploring_the_field/refining_disparity.rst +++ b/docs/source/exploring_the_field/refining_disparity.rst @@ -10,3 +10,6 @@ Two methods are available in pandora2d: - Interpolation - Optical flow. + +.. warning:: + The optical flow method is still in an experimental phase. diff --git a/docs/source/userguide/step_by_step/refinement.rst b/docs/source/userguide/step_by_step/refinement.rst index 4dc1c3e..6f321e6 100644 --- a/docs/source/userguide/step_by_step/refinement.rst +++ b/docs/source/userguide/step_by_step/refinement.rst @@ -15,6 +15,8 @@ It consists on 3 different steps: Optical_flow method ------------------- +.. warning:: + The optical flow method is still in an experimental phase. Inspired by [Lucas & Kanade]_.'s algorithm diff --git a/pandora2d/common.py b/pandora2d/common.py index e8a206c..f2a9a77 100644 --- a/pandora2d/common.py +++ b/pandora2d/common.py @@ -61,7 +61,7 @@ def dataset_disp_maps(delta_row: np.ndarray, delta_col: np.ndarray, attributes: :type delta_row: np.ndarray :param delta_col: disparity map for col :type delta_col: np.ndarray - :param attributes: disparity map for col + :param attributes: attributes containing invalid disparity values :type attributes: dict :return: dataset: Dataset with the disparity maps with the data variables : diff --git a/pandora2d/refinement/dichotomy.py b/pandora2d/refinement/dichotomy.py index 685bb95..b36e044 100644 --- a/pandora2d/refinement/dichotomy.py +++ b/pandora2d/refinement/dichotomy.py @@ -77,7 +77,7 @@ def refinement_method( :type cost_volumes: xarray.Dataset :param disp_map: pixel disparity maps :type disp_map: xarray.Dataset - param img_left: left image dataset + :param img_left: left image dataset :type img_left: xarray.Dataset :param img_right: right image dataset :type img_right: xarray.Dataset diff --git a/pandora2d/state_machine.py b/pandora2d/state_machine.py index e3797c7..e4d80c4 100644 --- a/pandora2d/state_machine.py +++ b/pandora2d/state_machine.py @@ -415,6 +415,10 @@ def refinement_run(self, cfg: Dict[str, dict], input_step: str) -> None: """ logging.info("Refinement computation...") + + if cfg["pipeline"][input_step]["refinement_method"] == "optical_flow": + logging.warning("The optical flow method is still in an experimental phase.") + refinement_run = refinement.AbstractRefinement( cfg["pipeline"][input_step], self.step, self.window_size ) # type: ignore[abstract]

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