added voxel down sample and trace test

tests/test_data.py

@@ -31,6 +31,6 @@
         "R": 12,
         "nb_neighbors": 5,
         "std_ratio": 2.0,
-        "voxel_size": 0.25,
+        "voxel_size": 1.0,
     }
 )

tests/test_voxel_down.py

@@ -0,0 +1,135 @@
+# Copyright (c) 2023, Sofia Vivdich and Anastasiia Kornilova
+#
+# 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.
+
+import numpy as np
+import open3d as o3d
+import pytest
+
+from services.preprocessing.voxel_down import VoxelDownProcessor
+
+from tests.test_data import config
+
+
+@pytest.mark.parametrize(
+    "src_points, "
+    "src_points2instances, "
+    "expected_points, "
+    "expected_points2instances, "
+    "expected_trace",
+    [
+        (
+            np.array(
+                [
+                    [0.1, 0.1, 0.1],
+                    [0.11, 0.11, 0.11],
+                    [0.111, 0.111, 0.111],
+                    [-10000, -20000, -30000],
+                    [1000, 2000, 3000],
+                    [1000.1, 2000.2, 3000.3],
+                ]
+            ),
+            np.array(
+                [
+                    [1, 2, 3, 4, 5, 6],
+                    [1, 2, 3, 4, 0, 0],
+                    [1, 2, 3, 4, 5, 6],
+                    [18, 17, 56, 78, 90, 23],
+                    [1, 2, 3, 0, 0, 6],
+                    [1, 2, 3, 0, 0, 6],
+                ]
+            ),
+            np.array(
+                [
+                    [0.107, 0.107, 0.107],
+                    [-10000, -20000, -30000],
+                    [1000.05, 2000.1, 3000.15],
+                ]
+            ),
+            np.array(
+                [
+                    [1, 2, 3, 4, 5, 6],
+                    [18, 17, 56, 78, 90, 23],
+                    [1, 2, 3, 0, 0, 6],
+                ]
+            ),
+            [
+                o3d.utility.IntVector([0, 1, 2]),
+                o3d.utility.IntVector([3]),
+                o3d.utility.IntVector([4, 5]),
+            ],
+        )
+    ],
+)
+def test_voxel_down_sample(
+    src_points, src_points2instances, expected_points, expected_points2instances, expected_trace
+):
+    pcd = o3d.geometry.PointCloud()
+    pcd.points = o3d.utility.Vector3dVector(src_points)
+
+    actual_pcd, actual_points2instances, actual_trace = VoxelDownProcessor().process(
+        config, pcd, src_points2instances
+    )
+
+    assert check_result_points(actual_pcd, expected_points) == len(expected_points)
+    assert check_result_points2instances(actual_points2instances, expected_points2instances) == expected_points2instances.shape[0]
+    assert check_result_trace(actual_trace, expected_trace) == len(expected_trace)
+
+
+def check_result_points(actual_pcd, expected_points):
+    actual_points = np.asarray(actual_pcd.points)
+
+    number_of_matched_positions = 0
+    for point1 in actual_points:
+        for point2 in expected_points:
+            if (point1 == point2).all():
+                number_of_matched_positions += 1
+                break
+
+    return number_of_matched_positions
+
+
+def check_result_points2instances(actual_points2instances, expected_points2instances):
+    matched_rows_in_expected = []
+
+    number_of_matched_rows = 0
+    for row1 in actual_points2instances:
+        for id, row2 in enumerate(expected_points2instances):
+            if id not in matched_rows_in_expected:
+                if (row1 == row2).all():
+                    number_of_matched_rows += 1
+                    matched_rows_in_expected.append(id)
+                    break
+
+    return number_of_matched_rows
+
+
+def check_result_trace(actual_trace, expected_trace):
+    matched_rows_in_expected = []
+
+    number_of_matched_rows = 0
+    for row1 in actual_trace:
+        int_vector1 = np.asarray(row1)
+
+        for id, row2 in enumerate(expected_trace):
+            int_vector2 = np.asarray(row2)
+            if len(int_vector1) != len(int_vector2):
+                continue
+
+            if id not in matched_rows_in_expected:
+                if (int_vector1 == int_vector2).all():
+                    number_of_matched_rows += 1
+                    matched_rows_in_expected.append(id)
+                    break
+
+    return number_of_matched_rows