container/ubuntu/Dockerfile

@@ -45,7 +45,7 @@ RUN apt-get update && apt-get install -y \
         python3-dev \
     && apt-get clean
 
-RUN pip install pytest aqtinstall
+RUN pip install pytest numpy aqtinstall
 
 # Install Qt 5.15
 RUN aqt install-qt linux desktop 5.15.2

tests/regression_test/tests/test_calib.py

+#
+# PeTrack - Software for tracking pedestrians movement in videos
+# Copyright (C) 2022 Forschungszentrum Jülich GmbH, IAS-7
+#
+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation, either version 3 of the License, or
+# (at your option) any later version.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with this program.  If not, see <https://www.gnu.org/licenses/>.
+#
+
+from pytest import approx
+import subprocess
+import xml.etree.ElementTree as ET
+import numpy as np
+
+# NOTE: Does not test all options; ie. QuadAspectRatio, Fix Center, Ext. Model, ...
+
+
+def read_intrinsics(tree: ET.ElementTree) -> np.ndarray:
+    node = tree.find("./CONTROL/CALIBRATION/INTRINSIC_PARAMETERS")
+    if node is None:
+        raise RuntimeError("Invalid pet-File! No Calibration node")
+
+    cx = float(node.get("CX", "nan"))
+    cy = float(node.get("CY", "nan"))
+    fx = float(node.get("FX", "nan"))
+    fy = float(node.get("FY", "nan"))
+    k4 = float(node.get("K4", "nan"))
+    k5 = float(node.get("K5", "nan"))
+    k6 = float(node.get("K6", "nan"))
+    r2 = float(node.get("R2", "nan"))
+    r4 = float(node.get("R4", "nan"))
+    r6 = float(node.get("R6", "nan"))
+    s1 = float(node.get("S1", "nan"))
+    s2 = float(node.get("S2", "nan"))
+    s3 = float(node.get("S3", "nan"))
+    s4 = float(node.get("S4", "nan"))
+    tang_dist = float(node.get("TANG_DIST", "nan"))
+    taux = float(node.get("TAUX", "nan"))
+    tauy = float(node.get("TAUY", "nan"))
+    tx = float(node.get("TX", "nan"))
+    ty = float(node.get("TY", "nan"))
+
+    # currently not used
+    # error leads to nan-value (Issue #364) being saved in demo
+    reprojection_error = float(node.get("ReprError", "nan"))
+    return np.array(
+        [
+            cx,
+            cy,
+            fx,
+            fy,
+            k4,
+            k5,
+            k6,
+            r2,
+            r4,
+            r6,
+            s1,
+            s2,
+            s3,
+            s4,
+            tang_dist,
+            taux,
+            tauy,
+            tx,
+            ty,
+            #reprojection_error,
+        ]
+    )
+
+
+def compare_intrinsic_calib(test_pet: ET.ElementTree, truth_pet: ET.ElementTree):
+    test_calib_params = read_intrinsics(test_pet)
+    truth_calib_params = read_intrinsics(truth_pet)
+
+    # high margin, but calibration itself should be tested by OpenCV itself
+    # this is just to see that we did calibrate
+    assert test_calib_params == approx(truth_calib_params, abs=0.1)
+
+
+def test_autoCalib(pytestconfig):
+    petrack_path = pytestconfig.getoption("path")
+    project = "../../../demo/00_files/00_empty.pet"
+    real_intrinsic = "../../../demo/01_calibration/01_intrinsic.pet"
+    intrinsic_dir = "../../../demo/00_files/calibration/intrinsic"
+    output = "../data/calibTest.pet"
+
+    # run autocalib on demo project
+    subprocess.run(
+        [
+            petrack_path,
+            "-project",
+            project,
+            "-autoIntrinsic",
+            intrinsic_dir,
+            "-autosave",
+            output,
+            "-platform",
+            "offscreen",
+        ],
+        check=True,
+    )
+
+    test_pet = ET.parse(output)
+    truth_pet = ET.parse(real_intrinsic)
+
+    compare_intrinsic_calib(test_pet, truth_pet)