Merge branch '948-new-margins-process' into 'master'

Resolve "Pandora: update de la récupération des marges"

Closes #948

See merge request 3d/cars-park/cars!796

cars/applications/dense_matching/census_mccnn_sgm.py

@@ -33,11 +33,14 @@
 # Third party imports
 import affine
 import numpy as np
+import pandora
 import rasterio
 import xarray as xr
 from affine import Affine
 from json_checker import And, Checker, Or
+from pandora.check_configuration import check_pipeline_section
 from pandora.img_tools import add_global_disparity
+from pandora.state_machine import PandoraMachine
 from scipy.ndimage import generic_filter
 
 import cars.applications.dense_matching.dense_matching_constants as dm_cst
@@ -225,6 +228,27 @@ def check_conf(self, conf):
         self.loader = pandora_loader
         self.corr_config = collections.OrderedDict(pandora_loader.get_conf())
 
+        # Instantiate margins from pandora check conf
+        # create the dataset
+        fake_dataset = xr.Dataset(
+            data_vars={},
+            coords={
+                "band_im": [(None)],
+                "row": np.arange(10),
+                "col": np.arange(10),
+            },
+            attrs={"disparity_source": [-1, 1]},
+        )
+        # Import plugins before checking configuration
+        pandora.import_plugin()
+        pandora_machine = PandoraMachine()
+        corr_config_pipeline = {"pipeline": dict(self.corr_config["pipeline"])}
+
+        _ = check_pipeline_section(
+            corr_config_pipeline, fake_dataset, fake_dataset, pandora_machine
+        )
+        self.margins = pandora_machine.margins.global_margins
+
         overloaded_conf["loader_conf"] = self.corr_config
 
         application_schema = {
@@ -299,7 +323,7 @@ def get_margins_fun(self, grid_left, disp_range_grid):
         matching method, to use during resampling
 
         :param grid_left: left epipolar grid
-        :param disp_min_grid: minimum and maximum disparity grid
+        :param disp_range_grid: minimum and maximum disparity grid
         :return: function that generates margin for given roi
 
         """
@@ -408,8 +432,8 @@ def margins_wrapper(row_min, row_max, col_min, col_max):
             disp_max = int(math.ceil(disp_max))
 
             # Compute margins for the correlator
-            # TODO use loader correlators
-            margins = dm_tools.get_margins(disp_min, disp_max, self.corr_config)
+            margins = dm_tools.get_margins(self.margins, disp_min, disp_max)
+
             return margins
 
         return margins_wrapper

cars/applications/dense_matching/dense_matching.py

@@ -106,14 +106,13 @@ def get_optimal_tile_size(self, disp_range_grid, max_ram_per_worker):
         """
 
     @abstractmethod
-    def get_margins_fun(self, grid_left, disp_min_grid, disp_max_grid):
+    def get_margins_fun(self, grid_left, disp_range_grid):
         """
         Get Margins function  that generates margins needed by
         matching method, to use during resampling
 
         :param grid_left: left epipolar grid
-        :param disp_min_grid: minimum disparity grid
-        :param disp_max_grid: maximum disparity grid
+        :param disp_range_grid: minimum and maximum disparity grid
         :return: function that generates margin for given roi
 
         """

cars/applications/dense_matching/dense_matching_tools.py

@@ -30,7 +30,6 @@
 
 import numpy as np
 import pandora
-import pandora.marge
 import xarray as xr
 
 # Third party imports
@@ -55,19 +54,54 @@
 from cars.core import constants_disparity as cst_disp
 
 
-def get_margins(disp_min, disp_max, corr_cfg):
+def get_margins(margin, disp_min, disp_max):
     """
     Get margins for the dense matching steps
 
+    :param margin: margins object
+    :type margin: Margins
     :param disp_min: Minimum disparity
     :type disp_min: int
     :param disp_max: Maximum disparity
     :type disp_max: int
-    :param corr_cfg: Correlator configuration
-    :type corr_cfg: dict
     :return: margins of the matching algorithm used
     """
-    return pandora.marge.get_margins(disp_min, disp_max, corr_cfg["pipeline"])
+
+    corner = ["left", "up", "right", "down"]
+    col = np.arange(len(corner))
+
+    left_margins = [
+        margin.left + disp_max,
+        margin.up,
+        margin.right - disp_min,
+        margin.down,
+    ]
+    right_margins = [
+        margin.left - disp_min,
+        margin.up,
+        margin.right + disp_max,
+        margin.down,
+    ]
+    same_margins = [
+        max(left, right)
+        for left, right in zip(left_margins, right_margins, strict=True)
+    ]
+
+    margins = xr.Dataset(
+        {
+            "left_margin": (
+                ["col"],
+                same_margins,
+            )
+        },
+        coords={"col": col},
+    )
+    margins["right_margin"] = xr.DataArray(same_margins, dims=["col"])
+
+    margins.attrs["disp_min"] = disp_min
+    margins.attrs["disp_max"] = disp_max
+
+    return margins
 
 
 def get_masks_from_pandora(

cars/pipelines/default/default_pipeline.py

@@ -1639,7 +1639,8 @@ def sensor_to_depth_maps(self):  # noqa: C901
             # Get margins used in dense matching,
             dense_matching_margins_fun = (
                 self.dense_matching_app.get_margins_fun(
-                    self.pairs[pair_key]["corrected_grid_left"], disp_range_grid
+                    self.pairs[pair_key]["corrected_grid_left"],
+                    disp_range_grid,
                 )
             )
 

tests/applications/dense_matching/test_dense_matching_config.py

@@ -146,7 +146,17 @@ def test_check_conf_with_error(
         "min_elevation_offset": 20,
         "max_elevation_offset": max_offset,  # should be > min
         "generate_confidence_intervals": confidence_intervals,
-        "loader_conf": {"pipeline": {"disparity": {}}},
+        "loader_conf": {
+            "input": {},
+            "pipeline": {
+                "matching_cost": {
+                    "matching_cost_method": "census",
+                    "window_size": 5,
+                    "subpix": 1,
+                },
+                "disparity": {"disparity_method": "wta"},
+            },
+        },
     }
     with pytest.raises(expected_error):
         _ = CensusMccnnSgm(conf)

tests/pipelines/test_wrappers.py

@@ -29,6 +29,7 @@
 # Third party imports
 import pytest
 from pandora.img_tools import get_metadata
+from pandora.margins import Margins
 
 # CARS imports
 import cars.applications.dense_matching.dense_matching_tools as dense_match
@@ -111,8 +112,11 @@ def test_epipolar_pipeline(
     global_disp_min = -19
     global_disp_max = 15
 
+    # cumulative margins between sgm (40) and matching_cost (ws/2)
+    margins = Margins(42, 42, 42, 42)
+
     initial_margins = dense_match.get_margins(
-        global_disp_min, global_disp_max, corr_cfg
+        margins, global_disp_min, global_disp_max
     )
     pandora_margins = initial_margins["left_margin"].values