Merge pull request #20 from kovalp/use-pure-ab-3d-mot-2

Use pure ab 3d mot 2

Author: kovalp

.bumpversion.toml

@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "1.0.0"
+current_version = "2.0.0"
 parse = "(?P<major>\\d+)\\.(?P<minor>\\d+)\\.(?P<patch>\\d+)"
 serialize = ["{major}.{minor}.{patch}"]
 search = "{current_version}"

CHANGELOG.md

@@ -1,3 +1,7 @@
+# 2.0.0
+
+  - Use the AssociationQuality class from the package `association-quality-clavia`.
+
 # 1.0.0
 
   - Added the module `association_quality` with an implementation of the classifier.

README.md

@@ -5,7 +5,7 @@ The purpose of the package is to enable calculation of the detection+tracking qu
 metrics for 3D tracking with KITTI data set.
 
 Apart from the refactored evaluation part of the AB3DMOT, a binary classifier 
-of the association outcomes is included. See `association_quality` submodule.
+of the association outcomes is included. The corresponding CLI needs to be implemented still.
 
 ## Installation
 

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "eval-ab-3d-mot"
-version = "1.0.0"
+version = "2.0.0"
 description = "Evaluation for the Pure AB-3D-MOT."
 readme = "README.md"
 authors = [
@@ -15,7 +15,7 @@ requires-python = ">=3.8"
 dependencies = [
     "binary-classification-ratios>=0.3.0",
     "munkres>=1.1.4",
-    "pure-ab-3d-mot>=1.0.0",
+    "pure-ab-3d-mot>=2.0.0",
     "pytest-mock>=3.14.1",
     "rich>=14.2.0",
     "rich-argparse>=1.7.1",
@@ -40,7 +40,7 @@ package = true
 
 [dependency-groups]
 dev = [
-    "bump-my-version>=1.2.4; python_version < '3.14'",
+    "bump-my-version>=1.2.4",
     "pytest>=8.3.5",
     "pytest-cov>=5.0.0",
     "ruff>=0.14.0",

src/eval_ab_3d_mot/__init__.py

@@ -1,3 +1,3 @@
 """."""
 
-__version__ = '1.0.0'
+__version__ = '2.0.0'

src/eval_ab_3d_mot/association_quality.py

@@ -4,11 +4,11 @@
 
 import numpy as np
 
-from pure_ab_3d_mot.clavia_conventions import ANN_IDS
-from pure_ab_3d_mot.str_const import DETS, INFO
+from association_quality_clavia import AssociationQuality
+from binary_classification_ratios import BinaryClassificationRatios
+from pure_ab_3d_mot.str_const import ANN_IDS, DETS, INFO
 from pure_ab_3d_mot.tracker import Ab3DMot
 
-from eval_ab_3d_mot.association_quality import AssociationQuality
 from eval_ab_3d_mot.cli.common.opt_param import fill_r_cnn_opt_param
 from eval_ab_3d_mot.kitti_category import KittiCategory
 
@@ -34,7 +34,8 @@ def test_run_1_757(files_dir: Path) -> None:
             is_det_supplied = track.ann_id in ids_r
             classifier.classify(track.ann_id, track.upd_id, is_det_supplied)
 
-    ratios = classifier.get_classification_ratios()
+    confusion_mat = classifier.get_confusion_matrix()
+    ratios = BinaryClassificationRatios(**confusion_mat)
     print(ratios.get_summary())
     ratios.assert_min(0.78366, 1.000, 0.7789)
     assert len(tracker.trackers) == 13