From 5cc1a7c54371217ba106f349bdd5205588c425f2 Mon Sep 17 00:00:00 2001 From: Marie Leconte Date: Tue, 23 May 2023 09:39:04 +0200 Subject: [PATCH 1/2] refactor : new API for check_pipeline_section --- pandora/check_json.py | 96 +++++++++++++++++++++-- pandora/state_machine.py | 165 ++++++++++++++++++++------------------- 2 files changed, 173 insertions(+), 88 deletions(-) diff --git a/pandora/check_json.py b/pandora/check_json.py index ec44108..f9ab6b1 100644 --- a/pandora/check_json.py +++ b/pandora/check_json.py @@ -30,6 +30,7 @@ import sys from collections.abc import Mapping from typing import Dict, Union, List, Tuple +import xarray as xr import numpy as np from json_checker import Checker, Or, And @@ -206,6 +207,64 @@ def get_config_input(user_cfg: Dict[str, dict]) -> Dict[str, dict]: return cfg +def get_config_pipeline(user_cfg: Dict[str, dict]) -> Dict[str, dict]: + """ + Get the pipeline configuration + + :param user_cfg: user configuration + :type user_cfg: dict + :return cfg: partial configuration + :rtype cfg: dict + """ + + cfg = {} + + if "pipeline" in user_cfg: + cfg["pipeline"] = user_cfg["pipeline"] + + return cfg + + +def get_metadata( + img: str, disp_min: Union[int, str, None], disp_max: Union[int, str, None], classif: str = None, segm: str = None +) -> xr.Dataset: + """ + Read metadata from image, and return the corresponding xarray.DataSet + + :param img: img_path + :type img: str + :param disp_min: minimal disparity + :type disp_min: int or str or None + :param disp_max: maximal disparity + :type disp_max: int or str or None + :param classif: path to the classif (optional) + :type classif: str + :param segm: path to the segm (optional) + :type segm: str + :return: partial xarray.DataSet (attributes and coordinates) + :rtype: xarray.DataSet + """ + img_ds = rasterio_open(img) + coords = { + "band": list(img_ds.descriptions), + "row": img_ds.height, + "col": img_ds.width, + } + attrs = {"disp_min": disp_min, "disp_max": disp_max} + dataset = xr.Dataset(data_vars={}, coords=coords, attrs=attrs) + + if classif is not None: + classif_ds = rasterio_open(classif) + band_classif = list(classif_ds.descriptions) + dataset.coords["band_classif"] = band_classif + dataset.attrs["classif"] = True + + if segm is not None: + dataset.attrs["segm"] = True + + return dataset + + def memory_consumption_estimation( user_pipeline_cfg: Dict[str, dict], user_input: Union[Dict[str, dict], Tuple[str, int, int]], @@ -247,7 +306,9 @@ def memory_consumption_estimation( else: # First, check if the configuration is valid cfg = {"pipeline": user_pipeline_cfg["pipeline"], "input": user_input["input"]} - checked_cfg = check_pipeline_section(cfg, pandora_machine) + img_left_metadata = get_metadata(cfg["input"]["img_left"], cfg["input"]["disp_min"], cfg["input"]["disp_max"]) + img_right_metadata = get_metadata(cfg["input"]["img_right"], None, None) + checked_cfg = check_pipeline_section(cfg, img_left_metadata, img_right_metadata, pandora_machine) # Obtain pipeline cfg pipeline_cfg = checked_cfg["pipeline"] @@ -271,7 +332,9 @@ def memory_consumption_estimation( return None -def check_pipeline_section(user_cfg: Dict[str, dict], pandora_machine: PandoraMachine) -> Dict[str, dict]: +def check_pipeline_section( + user_cfg: Dict[str, dict], img_left: xr.Dataset, img_right: xr.Dataset, pandora_machine: PandoraMachine +) -> Dict[str, dict]: """ Check if the pipeline is correct by - Checking the sequence of steps according to the machine transitions @@ -279,6 +342,10 @@ def check_pipeline_section(user_cfg: Dict[str, dict], pandora_machine: PandoraMa :param user_cfg: pipeline user configuration :type user_cfg: dict + :param img_left: image left with metadata + :type img_left: xarray.Dataset + :param img_right: image right with metadata + :type img_right: xarray.Dataset :param pandora_machine: instance of PandoraMachine :type pandora_machine: PandoraMachine object :return: cfg: pipeline configuration @@ -286,7 +353,7 @@ def check_pipeline_section(user_cfg: Dict[str, dict], pandora_machine: PandoraMa """ # Check if user configuration pipeline is compatible with transitions/states of pandora machine. cfg = update_conf(default_short_configuration_pipeline, user_cfg) - pandora_machine.check_conf(cfg) + pandora_machine.check_conf(cfg, img_left, img_right) cfg = update_conf(cfg, pandora_machine.pipeline_cfg) @@ -341,9 +408,9 @@ def check_input_section(user_cfg: Dict[str, dict]) -> Dict[str, dict]: check_disparities( cfg["input"]["disp_min_right"], cfg["input"]["disp_max_right"], - cfg["input"]["img_left"], + cfg["input"]["img_right"], ) - + # check bands check_band_names(cfg["input"]["img_left"]) check_band_names(cfg["input"]["img_right"]) @@ -373,8 +440,25 @@ def check_conf(user_cfg: Dict[str, dict], pandora_machine: PandoraMachine) -> di user_cfg_input = get_config_input(user_cfg) cfg_input = check_input_section(user_cfg_input) + # read metadata from left and right images + img_left_metadata = get_metadata( + cfg_input["input"]["img_left"], + cfg_input["input"]["disp_min"], + cfg_input["input"]["disp_max"], + cfg_input["input"]["left_classif"], + cfg_input["input"]["left_segm"], + ) + img_right_metadata = get_metadata( + cfg_input["input"]["img_right"], + cfg_input["input"]["disp_min_right"], + cfg_input["input"]["disp_max_right"], + cfg_input["input"]["right_classif"], + cfg_input["input"]["right_segm"], + ) + # check pipeline - cfg_pipeline = check_pipeline_section(user_cfg, pandora_machine) + user_cfg_pipeline = get_config_pipeline(user_cfg) + cfg_pipeline = check_pipeline_section(user_cfg_pipeline, img_left_metadata, img_right_metadata, pandora_machine) # concatenate updated config cfg = concat_conf([cfg_input, cfg_pipeline]) diff --git a/pandora/state_machine.py b/pandora/state_machine.py index 33fbe32..d1107ea 100644 --- a/pandora/state_machine.py +++ b/pandora/state_machine.py @@ -53,7 +53,7 @@ from pandora import refinement from pandora import matching_cost from pandora import semantic_segmentation -from pandora.img_tools import rasterio_open + # This silences numba's TBB threading layer warning with warnings.catch_warnings(): @@ -681,7 +681,9 @@ def run_exit(self) -> None: self.set_state("begin") def right_disp_map_check_conf( - self, cfg: Dict[str, dict], input_step: str # pylint:disable=unused-argument + self, + cfg: Dict[str, dict], + input_step: str, # pylint:disable=unused-argument ) -> None: """ Check the right_disp_map configuration @@ -696,10 +698,10 @@ def right_disp_map_check_conf( schema = {"method": And(str, lambda input: "none" or "accurate")} checker = Checker(schema) - checker.validate(cfg["pipeline"]["right_disp_map"]) + checker.validate(cfg["right_disp_map"]) # Store the righ disparity map configuration - self.right_disp_map = cfg["pipeline"]["right_disp_map"]["method"] + self.right_disp_map = cfg["right_disp_map"]["method"] def matching_cost_check_conf(self, cfg: Dict[str, dict], input_step: str) -> None: """ @@ -712,22 +714,22 @@ def matching_cost_check_conf(self, cfg: Dict[str, dict], input_step: str) -> Non :return: None """ # Create matching_cost object to check its step configuration - matching_cost_ = matching_cost.AbstractMatchingCost(**cfg["pipeline"][input_step]) # type: ignore + matching_cost_ = matching_cost.AbstractMatchingCost(**cfg[input_step]) # type: ignore # Check the coherence between the band selected for the matching_cost step # and the bands present on left and right image - if not "band" in cfg["pipeline"]["matching_cost"]: + if not "band" in cfg["matching_cost"]: band = None else: - band = cfg["pipeline"]["matching_cost"]["band"] + band = cfg["matching_cost"]["band"] self.check_band_pipeline( - cfg["input"]["img_left"], - cfg["pipeline"]["matching_cost"]["matching_cost_method"], + self.left_img.coords["band"].data, + cfg["matching_cost"]["matching_cost_method"], band, ) self.check_band_pipeline( - cfg["input"]["img_right"], - cfg["pipeline"]["matching_cost"]["matching_cost_method"], + self.right_img.coords["band"].data, + cfg["matching_cost"]["matching_cost_method"], band, ) @@ -743,7 +745,7 @@ def disparity_check_conf(self, cfg: Dict[str, dict], input_step: str) -> None: :type input_step: string :return: None """ - disparity_ = disparity.AbstractDisparity(**cfg["pipeline"][input_step]) # type: ignore + disparity_ = disparity.AbstractDisparity(**cfg[input_step]) # type: ignore self.pipeline_cfg["pipeline"][input_step] = disparity_.cfg def filter_check_conf(self, cfg: Dict[str, dict], input_step: str) -> None: @@ -756,7 +758,7 @@ def filter_check_conf(self, cfg: Dict[str, dict], input_step: str) -> None: :type input_step: string :return: None """ - filter_ = filter.AbstractFilter(**cfg["pipeline"][input_step]) # type: ignore + filter_ = filter.AbstractFilter(**cfg[input_step]) # type: ignore self.pipeline_cfg["pipeline"][input_step] = filter_.cfg def refinement_check_conf(self, cfg: Dict[str, dict], input_step: str) -> None: @@ -769,7 +771,7 @@ def refinement_check_conf(self, cfg: Dict[str, dict], input_step: str) -> None: :type input_step: string :return: None """ - refinement_ = refinement.AbstractRefinement(**cfg["pipeline"][input_step]) # type: ignore + refinement_ = refinement.AbstractRefinement(**cfg[input_step]) # type: ignore self.pipeline_cfg["pipeline"][input_step] = refinement_.cfg def aggregation_check_conf(self, cfg: Dict[str, dict], input_step: str) -> None: @@ -782,7 +784,7 @@ def aggregation_check_conf(self, cfg: Dict[str, dict], input_step: str) -> None: :type input_step: string :return: None """ - aggregation_ = aggregation.AbstractAggregation(**cfg["pipeline"][input_step]) # type: ignore + aggregation_ = aggregation.AbstractAggregation(**cfg[input_step]) # type: ignore self.pipeline_cfg["pipeline"][input_step] = aggregation_.cfg def semantic_segmentation_check_conf(self, cfg: Dict[str, dict], input_step: str) -> None: @@ -795,51 +797,50 @@ def semantic_segmentation_check_conf(self, cfg: Dict[str, dict], input_step: str :type input_step: string :return: None """ - semantic_segmentation_ = semantic_segmentation.AbstractSemanticSegmentation( - **cfg["pipeline"][input_step] - ) # type: ignore + semantic_segmentation_ = semantic_segmentation.AbstractSemanticSegmentation(**cfg[input_step]) # type: ignore self.pipeline_cfg["pipeline"][input_step] = semantic_segmentation_.cfg # If semantic_segmentation is present, check that the necessary bands are present in the inputs self.check_band_pipeline( - cfg["input"]["img_left"], - cfg["pipeline"]["semantic_segmentation"]["segmentation_method"], - cfg["pipeline"]["semantic_segmentation"]["RGB_bands"], + self.left_img.coords["band"].data, + cfg["semantic_segmentation"]["segmentation_method"], + cfg["semantic_segmentation"]["RGB_bands"], ) # If vegetation_band is present in semantic_segmentation, check that the bands are present # in the input left classification - if "vegetation_band" in cfg["pipeline"]["semantic_segmentation"]: - if not "left_classif" in cfg["input"]: + if "vegetation_band" in cfg["semantic_segmentation"]: + if not "classif" in self.left_img.data_vars: logging.error( - "For performing the semantic_segmentation step in the pipeline, left_classif must be present." + "For performing the semantic_segmentation step in the pipeline," + " classif must be present in left image." ) sys.exit(1) self.check_band_pipeline( - cfg["input"]["left_classif"], - cfg["pipeline"]["semantic_segmentation"]["segmentation_method"], - cfg["pipeline"]["semantic_segmentation"]["vegetation_band"]["classes"], + self.left_img.coords["band_classif"].data, + cfg["semantic_segmentation"]["segmentation_method"], + cfg["semantic_segmentation"]["vegetation_band"]["classes"], ) # If semantic_segmentation and right disparity is to be computed, # check that the RGB band are present in the right image if self.right_disp_map == "accurate": self.check_band_pipeline( - cfg["input"]["img_right"], - cfg["pipeline"]["semantic_segmentation"]["segmentation_method"], - cfg["pipeline"]["semantic_segmentation"]["RGB_bands"], + self.right_img.coords["band"].data, + cfg["semantic_segmentation"]["segmentation_method"], + cfg["semantic_segmentation"]["RGB_bands"], ) # If vegetation_band is present in semantic_segmentation, and right disparity is to be computed, # check that the bands are present in the input right classification - if "vegetation_band" in cfg["pipeline"]["semantic_segmentation"]: - if not "right_classif" in cfg["input"]: + if "vegetation_band" in cfg["semantic_segmentation"]: + if not "classif" in self.right_img.data_vars: logging.error( "For performing cross-checking step with semantic_segmentation in the pipeline," - " right classif must be present.", + " classif must be present in right image.", ) sys.exit(1) self.check_band_pipeline( - cfg["input"]["right_classif"], - cfg["pipeline"]["semantic_segmentation"]["segmentation_method"], - cfg["pipeline"]["semantic_segmentation"]["vegetation_band"]["classes"], + self.right_img.coords["band_classif"].data, + cfg["semantic_segmentation"]["segmentation_method"], + cfg["semantic_segmentation"]["vegetation_band"]["classes"], ) def optimization_check_conf(self, cfg: Dict[str, dict], input_step: str) -> None: @@ -852,22 +853,22 @@ def optimization_check_conf(self, cfg: Dict[str, dict], input_step: str) -> None :type input_step: string :return: None """ - optimization_ = optimization.AbstractOptimization(**cfg["pipeline"][input_step]) # type: ignore + optimization_ = optimization.AbstractOptimization(**cfg[input_step]) # type: ignore self.pipeline_cfg["pipeline"][input_step] = optimization_.cfg # If geometric_prior is needed for the optimization step, # check that the necessary inputs and bands are present - if "geometric_prior" in cfg["pipeline"]["optimization"]: - source = cfg["pipeline"]["optimization"]["geometric_prior"]["source"] + if "geometric_prior" in cfg["optimization"]: + source = cfg["optimization"]["geometric_prior"]["source"] if source in ["classif", "segm"]: - if not "left_" + source in cfg["input"]: + if not source in self.left_img.data_vars: logging.error( "For performing the 3SGM optimization step in the pipeline, left %s must be present.", source ) sys.exit(1) # If right disparity is to be computed and 3SGM optimization is present on the pipeline, # then both left and right segmentations/classifications must be present - if self.right_disp_map == "accurate" and "right_" + source not in cfg["input"]: + if self.right_disp_map == "accurate" and not source in self.right_img.data_vars: logging.error( "For performing cross-checking step with 3SGM optimization in the pipeline," " right %s must be present.", @@ -876,19 +877,19 @@ def optimization_check_conf(self, cfg: Dict[str, dict], input_step: str) -> None sys.exit(1) # If sgm optimization is present with geometric_prior classification, check that the # classes bands are present in the input classification - if "classes" in cfg["pipeline"]["optimization"]["geometric_prior"]: + if "classes" in cfg["optimization"]["geometric_prior"]: self.check_band_pipeline( - cfg["input"]["left_classif"], - cfg["pipeline"]["optimization"]["optimization_method"], - cfg["pipeline"]["optimization"]["geometric_prior"]["classes"], + self.left_img.coords["band_classif"].data, + cfg["optimization"]["optimization_method"], + cfg["optimization"]["geometric_prior"]["classes"], ) # If right disparity is to be computed, check that the classes bands are present # in the input right classification if self.right_disp_map == "accurate": self.check_band_pipeline( - cfg["input"]["right_classif"], - cfg["pipeline"]["optimization"]["optimization_method"], - cfg["pipeline"]["optimization"]["geometric_prior"]["classes"], + self.right_img.coords["band_classif"].data, + cfg["optimization"]["optimization_method"], + cfg["optimization"]["geometric_prior"]["classes"], ) def validation_check_conf(self, cfg: Dict[str, dict], input_step: str) -> None: @@ -902,11 +903,11 @@ def validation_check_conf(self, cfg: Dict[str, dict], input_step: str) -> None: :return: None """ - validation_ = validation.AbstractValidation(**cfg["pipeline"][input_step]) # type: ignore + validation_ = validation.AbstractValidation(**cfg[input_step]) # type: ignore self.pipeline_cfg["pipeline"][input_step] = validation_.cfg if "interpolated_disparity" in validation_.cfg: interpolate_ = validation.AbstractInterpolation( # type:ignore # pylint:disable=unused-variable - **cfg["pipeline"][input_step] + **cfg[input_step] ) if validation_.cfg["validation_method"] == "cross_checking" and self.right_disp_map != "accurate": @@ -916,8 +917,8 @@ def validation_check_conf(self, cfg: Dict[str, dict], input_step: str) -> None: # If left disparities are grids of disparity and the right disparities are none, the cross-checking # method cannot be used - if isinstance(cfg["input"]["disp_min"], str) and "validation" in cfg["pipeline"]: - if not "disp_min_right" in cfg["input"]: + if isinstance(self.left_img.attrs["disp_min"], str) and "validation" in cfg: + if not self.right_img.attrs["disp_min"]: logging.error( "The cross-checking step cannot be processed if disp_min, disp_max are paths to the left " "disparity grids and disp_right_min, disp_right_max are none." @@ -934,22 +935,16 @@ def multiscale_check_conf(self, cfg: Dict[str, dict], input_step: str) -> None: :type input_step: string :return: """ - multiscale_ = multiscale.AbstractMultiscale(**cfg["pipeline"][input_step]) # type: ignore + multiscale_ = multiscale.AbstractMultiscale(**cfg[input_step]) # type: ignore self.pipeline_cfg["pipeline"][input_step] = multiscale_.cfg # If multiscale step is present, input disparities cannot be grids - disp_min_right = None - if "disp_min_right" in cfg["input"]: - disp_min_right = cfg["input"] - disp_max_right = None - if "disp_max_right" in cfg["input"]: - disp_max_right = cfg["input"] if ( - isinstance(cfg["input"]["disp_min"], str) - or isinstance(disp_min_right, str) - or (isinstance(cfg["input"]["disp_max"], str)) - or isinstance(disp_max_right, str) - ) and ("multiscale" in cfg["pipeline"]): + isinstance(self.left_img.attrs["disp_min"], str) + or isinstance(self.right_img.attrs["disp_min"], str) + or (isinstance(self.left_img.attrs["disp_max"], str)) + or isinstance(self.right_img.attrs["disp_max"], str) + ) and ("multiscale" in cfg): logging.error("Multiscale processing does not accept input disparity grids.") sys.exit(1) @@ -963,18 +958,25 @@ def cost_volume_confidence_check_conf(self, cfg: Dict[str, dict], input_step: st :type input_step: string :return: None """ - confidence_ = cost_volume_confidence.AbstractCostVolumeConfidence(**cfg["pipeline"][input_step]) # type: ignore + confidence_ = cost_volume_confidence.AbstractCostVolumeConfidence(**cfg[input_step]) # type: ignore self.pipeline_cfg["pipeline"][input_step] = confidence_.cfg - def check_conf(self, cfg: Dict[str, dict]) -> None: + def check_conf(self, cfg: Dict[str, dict], img_left: xr.Dataset, img_right: xr.Dataset) -> None: """ Check configuration and transitions :param cfg: pipeline configuration :type cfg: dict + :param img_left: image left with metadata + :type img_left: xarray.Dataset + :param img_right: image right with metadata + :type img_right: xarray.Dataset :return: """ + self.left_img = img_left + self.right_img = img_right + # Add transitions to the empty machine. self.add_transitions(self._transitions_check) @@ -997,9 +999,9 @@ def check_conf(self, cfg: Dict[str, dict]) -> None: check_input = "check_" + input_step if len(input_step.split(".")) != 1: - self.trigger(check_input.split(".")[0], cfg, input_step) + self.trigger(check_input.split(".")[0], cfg["pipeline"], input_step) else: - self.trigger(check_input, cfg, input_step) + self.trigger(check_input, cfg["pipeline"], input_step) except (MachineError, KeyError, AttributeError): logging.error("A problem occurs during Pandora checking. Be sure of your sequencement") @@ -1043,33 +1045,32 @@ def is_not_last_scale(self, input_step: str, cfg: Dict[str, dict]) -> bool: # p return True @staticmethod - def check_band_pipeline(img: str, step: str, bands: Union[None, str, List[str], Dict]) -> None: + def check_band_pipeline(band_list: np.ndarray, step: str, band_used: Union[None, str, List[str], Dict]) -> None: """ Check coherence band parameter between pipeline step and image dataset - :param img: path to the image - :type img: str + :param band_list: band names of image + :type band_list: numpy.ndarray with bands :param step: pipeline step :type step: str - :param bands: band names - :type bands: None, str, List[str] or Dict + :param band_used: band names for pipeline step + :type band_used: None, str, List[str] or Dict :return: None """ - # open images - img_ds = rasterio_open(img) + # If no bands are given, then the input image shall be monoband - if not bands: - if img_ds.count != 1: + if not band_used: + if len(band_list) != 1: logging.error("Missing band instantiate on %s step : input image is multiband", step) sys.exit(1) # check that the image have the band names - elif isinstance(bands, dict): - for _, band in bands.items(): - if not band in list(img_ds.descriptions): + elif isinstance(band_used, dict): + for _, band in band_used.items(): + if not band in band_list: logging.error("Wrong band instantiate on %s step: %s not in input image", step, band) sys.exit(1) else: - for band in bands: - if not band in list(img_ds.descriptions): + for band in band_used: + if not band in band_list: logging.error("Wrong band instantiate %s step: %s not in input image", step, band) sys.exit(1) From eb89f939355bbfe165f06a093f7d40f1df0f1aa4 Mon Sep 17 00:00:00 2001 From: Marie Leconte Date: Tue, 30 May 2023 10:24:20 +0200 Subject: [PATCH 2/2] test: update test with new check_pipeline_section api --- .../advanced_examples/api_check_conf.ipynb | 490 ++++++++++++++++++ notebooks/data/left_rgb.tif | Bin 0 -> 2027662 bytes notebooks/data/right_rgb.tif | Bin 0 -> 2027662 bytes notebooks/introduction_and_basic_usage.ipynb | 12 +- .../statistical_and_visual_analysis.ipynb | 29 +- notebooks/usage_with_multiscale.ipynb | 16 +- tests/pandora/right_classif.tif | Bin 0 -> 2027826 bytes tests/test_config.py | 62 ++- tests/test_notebooks.py | 26 + 9 files changed, 610 insertions(+), 25 deletions(-) create mode 100644 notebooks/advanced_examples/api_check_conf.ipynb create mode 100644 notebooks/data/left_rgb.tif create mode 100644 notebooks/data/right_rgb.tif create mode 100644 tests/pandora/right_classif.tif diff --git a/notebooks/advanced_examples/api_check_conf.ipynb b/notebooks/advanced_examples/api_check_conf.ipynb new file mode 100644 index 0000000..2064dc5 --- /dev/null +++ b/notebooks/advanced_examples/api_check_conf.ipynb @@ -0,0 +1,490 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "3311ab29", + "metadata": {}, + "source": [ + "# API check conf pandora" + ] + }, + { + "cell_type": "markdown", + "id": "82d86b5f", + "metadata": {}, + "source": [ + "*This notebook is used to test the new* «check_pipeline_section» *function*." + ] + }, + { + "cell_type": "markdown", + "id": "888eb507", + "metadata": {}, + "source": [ + " ## 1. \"Pandora\" version : user config with input + pipeline" + ] + }, + { + "cell_type": "markdown", + "id": "704eeb13", + "metadata": {}, + "source": [ + "### Import" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "80b6fcf6", + "metadata": {}, + "outputs": [], + "source": [ + "from pandora import import_plugin\n", + "from pandora.check_json import (\n", + " check_conf,\n", + " get_config_input,\n", + " check_input_section,\n", + " get_config_pipeline,\n", + " get_metadata,\n", + " check_pipeline_section,\n", + " concat_conf\n", + ")\n", + "from pandora.state_machine import PandoraMachine\n", + "from pandora.img_tools import rasterio_open\n", + "\n", + "import xarray as xr\n", + "import pprint\n", + "\n", + "pp = pprint.PrettyPrinter(indent=4)" + ] + }, + { + "cell_type": "markdown", + "id": "d3118f7e", + "metadata": {}, + "source": [ + "### Define user config" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d0171881", + "metadata": {}, + "outputs": [], + "source": [ + "user_cfg = {\n", + " \"input\":\n", + " {\n", + " \"img_left\":\"../data/left_rgb.tif\",\n", + " \"img_right\":\"../data/right_rgb.tif\",\n", + " \"disp_min\": -60,\n", + " \"disp_max\": 0\n", + " },\n", + " \"pipeline\":\n", + " {\n", + " \"right_disp_map\": { \"method\": \"accurate\"},\n", + " \"matching_cost\": {\"matching_cost_method\": \"zncc\", \"band\": \"r\"},\n", + " \"optimization\": {\"optimization_method\": \"sgm\"},\n", + " \"disparity\": {\"disparity_method\": \"wta\"},\n", + " \"filter\": {\"filter_method\": \"median\"},\n", + " \"refinement\": {\"refinement_method\": \"quadratic\"},\n", + " \"validation\": {\"validation_method\": \"cross_checking\"}\n", + " }\n", + "}" + ] + }, + { + "cell_type": "markdown", + "id": "7e26b840", + "metadata": {}, + "source": [ + "### Import pandora plugins (sgm)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "079918b4", + "metadata": {}, + "outputs": [], + "source": [ + "import_plugin()" + ] + }, + { + "cell_type": "markdown", + "id": "9eebd7d7", + "metadata": {}, + "source": [ + "### Instantiate a pandora machine" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d3c70c47", + "metadata": {}, + "outputs": [], + "source": [ + "pandora_machine = PandoraMachine()" + ] + }, + { + "cell_type": "markdown", + "id": "0001b8da", + "metadata": {}, + "source": [ + "### Run check config" + ] + }, + { + "cell_type": "markdown", + "id": "63ce3c7c", + "metadata": {}, + "source": [ + "**Check input**" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b8750c5f", + "metadata": {}, + "outputs": [], + "source": [ + "user_cfg_input = get_config_input(user_cfg)\n", + "cfg_input = check_input_section(user_cfg_input)\n", + "pp.pprint(cfg_input)" + ] + }, + { + "cell_type": "markdown", + "id": "dacacc1e", + "metadata": {}, + "source": [ + "**Check pipeline**" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "61d09c86", + "metadata": {}, + "outputs": [], + "source": [ + "user_cfg_pipeline = get_config_pipeline(user_cfg)\n", + "metadata_left = get_metadata(\n", + " cfg_input[\"input\"][\"img_left\"],\n", + " cfg_input[\"input\"][\"disp_min\"],\n", + " cfg_input[\"input\"][\"disp_max\"]\n", + ")\n", + "metadata_right = get_metadata(\n", + " cfg_input[\"input\"][\"img_right\"], \n", + " cfg_input[\"input\"][\"disp_min_right\"],\n", + " cfg_input[\"input\"][\"disp_max_right\"])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bb3d83c6", + "metadata": {}, + "outputs": [], + "source": [ + "cfg_pipeline = check_pipeline_section(user_cfg_pipeline, metadata_left, metadata_right, pandora_machine)\n", + "pp.pprint(cfg_pipeline)" + ] + }, + { + "cell_type": "markdown", + "id": "a6416b8f", + "metadata": {}, + "source": [ + "**update config**" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a81a62a0", + "metadata": {}, + "outputs": [], + "source": [ + "cfg_update = concat_conf([cfg_input, cfg_pipeline])\n", + "pp.pprint(cfg_update)" + ] + }, + { + "cell_type": "markdown", + "id": "7e77eb90", + "metadata": {}, + "source": [ + "## 2. \"CARS\" version : user config with only pipeline and xr.Dataset list" + ] + }, + { + "cell_type": "markdown", + "id": "23029f28", + "metadata": {}, + "source": [ + "### Define user config" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "66f11d4c", + "metadata": {}, + "outputs": [], + "source": [ + "user_cfg_pipeline = {\n", + " \"pipeline\":\n", + " {\n", + " \"right_disp_map\": { \"method\": \"accurate\"},\n", + " \"matching_cost\": {\"matching_cost_method\": \"zncc\", \"band\": \"r\"},\n", + " \"optimization\": {\"optimization_method\": \"sgm\"},\n", + " \"disparity\": {\"disparity_method\": \"wta\"},\n", + " \"filter\": {\"filter_method\": \"median\"},\n", + " \"refinement\": {\"refinement_method\": \"quadratic\"},\n", + " \"validation\": {\"validation_method\": \"cross_checking\"}\n", + " }\n", + "}" + ] + }, + { + "cell_type": "markdown", + "id": "6b19a881", + "metadata": {}, + "source": [ + "### Instantiate a pandora machine" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8f3b6a65", + "metadata": {}, + "outputs": [], + "source": [ + "pandora_machine = PandoraMachine()" + ] + }, + { + "cell_type": "markdown", + "id": "850adb0b", + "metadata": {}, + "source": [ + "### image paths with disparities" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a3ca7451", + "metadata": {}, + "outputs": [], + "source": [ + "disp_min = -60\n", + "disp_max = 0\n", + "img_left_path = \"../data/left_rgb.tif\"\n", + "img_right_path = \"../data/right_rgb.tif\"" + ] + }, + { + "cell_type": "markdown", + "id": "ec4a597e", + "metadata": {}, + "source": [ + "### Run check config : only pipeline" + ] + }, + { + "cell_type": "markdown", + "id": "c1b98b96", + "metadata": {}, + "source": [ + "**Check pipeline**" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a61637f0", + "metadata": {}, + "outputs": [], + "source": [ + "metadata_left = get_metadata(img_left_path, disp_min, disp_max)\n", + "metadata_right = get_metadata(img_right_path, None, None)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "148a2316", + "metadata": {}, + "outputs": [], + "source": [ + "cfg_pipeline = check_pipeline_section(user_cfg_pipeline, metadata_left, metadata_right, pandora_machine)\n", + "pp.pprint(cfg_pipeline)" + ] + }, + { + "cell_type": "markdown", + "id": "2744ee64", + "metadata": {}, + "source": [ + "## 3. \"Pandora\" version : user config with all options" + ] + }, + { + "cell_type": "markdown", + "id": "3552e955", + "metadata": {}, + "source": [ + "### Instantiate a pandora machine" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "26ee255d", + "metadata": {}, + "outputs": [], + "source": [ + "pandora_machine = PandoraMachine()" + ] + }, + { + "cell_type": "markdown", + "id": "2e78cef7", + "metadata": {}, + "source": [ + "### User cfg" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2eb03d52", + "metadata": {}, + "outputs": [], + "source": [ + "user_cfg = {\n", + " \"input\":\n", + " {\n", + " \"img_left\": \"../../tests/pandora/left_rgb.tif\",\n", + " \"img_right\": \"../../tests/pandora/right_rgb.tif\",\n", + " \"disp_min\": -60,\n", + " \"disp_max\": 0,\n", + " \"left_classif\": \"../../tests/pandora/left_classif.tif\",\n", + " \"right_classif\": \"../../tests/pandora/right_classif.tif\"\n", + " },\n", + " \"pipeline\":\n", + " {\n", + " \"right_disp_map\": { \"method\": \"accurate\"},\n", + " \"matching_cost\": {\"matching_cost_method\": \"zncc\", \"band\": \"r\"},\n", + " \"aggregation\": {\"aggregation_method\": \"cbca\"},\n", + " \"optimization\": {\"optimization_method\": \"sgm\"},\n", + " \"disparity\": {\"disparity_method\": \"wta\"},\n", + " \"filter\": {\"filter_method\": \"median\"},\n", + " \"refinement\": {\"refinement_method\": \"quadratic\"},\n", + " \"validation\": {\"validation_method\": \"cross_checking\"},\n", + " \"multiscale\": {\"multiscale_method\": \"fixed_zoom_pyramid\", \"num_scales\": 3}\n", + " }\n", + "}" + ] + }, + { + "cell_type": "markdown", + "id": "1a52bc97", + "metadata": {}, + "source": [ + "### Run check config " + ] + }, + { + "cell_type": "markdown", + "id": "4499ac47", + "metadata": {}, + "source": [ + "**Check input**" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ff804336", + "metadata": {}, + "outputs": [], + "source": [ + "user_cfg_input = get_config_input(user_cfg)\n", + "cfg_input = check_input_section(user_cfg_input)\n", + "pp.pprint(cfg_input)" + ] + }, + { + "cell_type": "markdown", + "id": "ba4d40be", + "metadata": {}, + "source": [ + "**Check pipeline**" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "61cbb844", + "metadata": {}, + "outputs": [], + "source": [ + "user_cfg_pipeline = get_config_pipeline(user_cfg)\n", + "metadata_left = get_metadata(\n", + " cfg_input[\"input\"][\"img_left\"],\n", + " cfg_input[\"input\"][\"disp_min\"],\n", + " cfg_input[\"input\"][\"disp_max\"],\n", + " cfg_input[\"input\"][\"left_classif\"]\n", + " \n", + ")\n", + "metadata_right = get_metadata(\n", + " cfg_input[\"input\"][\"img_right\"],\n", + " cfg_input[\"input\"][\"disp_min_right\"],\n", + " cfg_input[\"input\"][\"disp_max_right\"],\n", + " cfg_input[\"input\"][\"right_classif\"]\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bd4eb726", + "metadata": {}, + "outputs": [], + "source": [ + "cfg_pipeline = check_pipeline_section(user_cfg_pipeline, metadata_left, metadata_right, pandora_machine)\n", + 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