test: add functional test to check disparity margins in cost volumes

tests/functional_tests/matching_cost/test_disparity_margins.py

@@ -0,0 +1,205 @@
+#!/usr/bin/env python
+#
+# Copyright (c) 2024 Centre National d'Etudes Spatiales (CNES).
+#
+# 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.
+#
+
+"""
+Tests disparity margins in matching cost step
+"""
+
+import pytest
+import numpy as np
+import xarray as xr
+
+from pandora2d.img_tools import add_disparity_grid
+from pandora2d.state_machine import Pandora2DMachine
+
+
+class TestDisparityMargins:
+    """
+    Test disparity margins in the cost volume
+    """
+
+    @pytest.fixture()
+    def create_datasets(self):
+        """
+        Creates left and right datasets
+        """
+
+        data = np.full((10, 10), 1)
+        left = xr.Dataset(
+            {"im": (["row", "col"], data)},
+            coords={"row": np.arange(data.shape[0]), "col": np.arange(data.shape[1])},
+        )
+
+        add_disparity_grid(left, [1, 3], [-2, 2])
+
+        left.attrs = {
+            "no_data_img": -9999,
+            "valid_pixels": 0,
+            "no_data_mask": 1,
+            "crs": None,
+            "col_disparity_source": [1, 3],
+            "row_disparity_source": [-2, 2],
+        }
+
+        data = np.full((10, 10), 1)
+        right = xr.Dataset(
+            {"im": (["row", "col"], data)},
+            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,
+            "col_disparity_source": [1, 3],
+            "row_disparity_source": [-2, 2],
+        }
+
+        return left, right
+
+    @pytest.fixture()
+    def config(self, subpix, refinement_config, matching_cost_method):
+        return {
+            # "input": input_config,
+            "pipeline": {
+                "matching_cost": {
+                    "matching_cost_method": matching_cost_method,
+                    "window_size": 1,
+                    "step": [1, 1],
+                    "subpix": subpix,
+                },
+                "disparity": {"disparity_method": "wta", "invalid_disparity": -6},
+                "refinement": refinement_config,
+            }
+        }
+
+    @pytest.mark.parametrize("matching_cost_method", ["sad", "ssd", "zncc"])
+    @pytest.mark.parametrize(
+        ["subpix", "refinement_config", "cv_shape_expected", "disp_col_expected", "disp_row_expected"],
+        [
+            pytest.param(
+                1,
+                {"refinement_method": "dichotomy", "iterations": 1, "filter": "bicubic"},
+                (10, 10, 7, 9),
+                [-1, 0, 1, 2, 3, 4, 5],
+                [-4, -3, -2, -1, 0, 1, 2, 3, 4],
+                id="Subpix=1 and refinement_method=dichotomy",
+            ),
+            pytest.param(
+                1,
+                {
+                    "refinement_method": "interpolation",
+                },
+                (10, 10, 9, 11),
+                [-2, -1, 0, 1, 2, 3, 4, 5, 6],
+                [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5],
+                id="Subpix=1 and refinement_method=interpolation",
+            ),
+            pytest.param(
+                1,
+                {
+                    "refinement_method": "optical_flow",
+                },
+                (10, 10, 3, 5),
+                [1, 2, 3],
+                [-2, -1, 0, 1, 2],
+                id="Subpix=1 and refinement_method=optical_flow",
+            ),
+            pytest.param(
+                2,
+                {"refinement_method": "dichotomy", "iterations": 1, "filter": "bicubic"},
+                (10, 10, 13, 17),
+                [-1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5],
+                [-4, -3.5, -3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4],
+                id="Subpix=2 and refinement_method=dichotomy",
+            ),
+            pytest.param(
+                2,
+                {
+                    "refinement_method": "interpolation",
+                },
+                (10, 10, 17, 21),
+                [-2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6],
+                [-5, -4.5, -4, -3.5, -3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5],
+                id="Subpix=2 and refinement_method=interpolation",
+            ),
+            pytest.param(
+                2,
+                {
+                    "refinement_method": "optical_flow",
+                },
+                (10, 10, 5, 9),
+                [1, 1.5, 2, 2.5, 3],
+                [-2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2],
+                id="Subpix=2 and refinement_method=optical_flow",
+            ),
+            pytest.param(
+                4,
+                {"refinement_method": "dichotomy", "iterations": 1, "filter": "bicubic"},
+                (10, 10, 25, 33),
+                np.arange(-1, 5.25, 0.25),
+                np.arange(-4, 4.25, 0.25),
+                id="Subpix=4 and refinement_method=dichotomy",
+            ),
+            pytest.param(
+                4,
+                {
+                    "refinement_method": "interpolation",
+                },
+                (10, 10, 33, 41),
+                np.arange(-2, 6.25, 0.25),
+                np.arange(-5, 5.25, 0.25),
+                id="Subpix=4 and refinement_method=interpolation",
+            ),
+            pytest.param(
+                4,
+                {
+                    "refinement_method": "optical_flow",
+                },
+                (10, 10, 9, 17),
+                [1, 1.25, 1.5, 1.75, 2, 2.25, 2.5, 2.75, 3],
+                [-2, -1.75, -1.5, -1.25, -1, -0.75, -0.5, -0.25, 0, 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 2],
+                id="Subpix=4 and refinement_method=optical_flow",
+            ),
+        ],
+    )
+    def test_disparity_margins_in_cost_volumes(
+        self, cv_shape_expected, disp_col_expected, disp_row_expected, config, create_datasets
+    ):
+        """
+        Test that the disparity margins are correctly added in the cost volumes
+        according to the refinement margins.
+        """
+
+        pandora2d_machine = Pandora2DMachine()
+
+        img_left, img_right = create_datasets
+
+        pandora2d_machine.check_conf(config)
+        pandora2d_machine.run_prepare(img_left, img_right, config)
+        pandora2d_machine.run("matching_cost", config)
+
+        cost_volumes = pandora2d_machine.cost_volumes["cost_volumes"]
+
+        np.testing.assert_array_equal(cost_volumes.shape, cv_shape_expected)
+        np.testing.assert_array_equal(cost_volumes.disp_col, disp_col_expected)
+        np.testing.assert_array_equal(cost_volumes.disp_row, disp_row_expected)