Refactor constants management to use Pydantic BaseModel for configuration

- Replaced module-level path variables in constants.py with a structured Pydantic Config class.
- Updated all relevant modules (train.py, augmentation.py, exports.py, dataset-visualiser.py, manual_run.py) to access paths through the new config structure.
- Fixed bugs related to image processing and model saving.
- Enhanced test infrastructure to accommodate the new configuration approach.

This refactor improves code maintainability and clarity by centralizing configuration management.

tests/performance/test_augmentation_perf.py

@@ -20,15 +20,7 @@ if "matplotlib" not in sys.modules:
 
 
 def _patch_augmentation_paths(monkeypatch, base: Path):
-    import augmentation as aug
-    import constants as c
-
     apply_constants_patch(monkeypatch, base)
-    monkeypatch.setattr(aug, "data_images_dir", c.data_images_dir)
-    monkeypatch.setattr(aug, "data_labels_dir", c.data_labels_dir)
-    monkeypatch.setattr(aug, "processed_images_dir", c.processed_images_dir)
-    monkeypatch.setattr(aug, "processed_labels_dir", c.processed_labels_dir)
-    monkeypatch.setattr(aug, "processed_dir", c.processed_dir)
 
 
 def _augment_annotation_with_total(monkeypatch):
@@ -58,8 +50,8 @@ def test_pt_aug_01_throughput_ten_images_sixty_seconds(
     import constants as c
     from augmentation import Augmentator
 
-    img_dir = Path(c.data_images_dir)
-    lbl_dir = Path(c.data_labels_dir)
+    img_dir = Path(c.config.data_images_dir)
+    lbl_dir = Path(c.config.data_labels_dir)
     img_dir.mkdir(parents=True, exist_ok=True)
     lbl_dir.mkdir(parents=True, exist_ok=True)
     src_img, src_lbl = sample_images_labels(10)
@@ -83,9 +75,9 @@ def test_pt_aug_02_parallel_at_least_one_point_five_x_faster(
     import constants as c
     from augmentation import Augmentator
 
-    img_dir = Path(c.data_images_dir)
-    lbl_dir = Path(c.data_labels_dir)
-    proc_dir = Path(c.processed_dir)
+    img_dir = Path(c.config.data_images_dir)
+    lbl_dir = Path(c.config.data_labels_dir)
+    proc_dir = Path(c.config.processed_dir)
     img_dir.mkdir(parents=True, exist_ok=True)
     lbl_dir.mkdir(parents=True, exist_ok=True)
     src_img, src_lbl = sample_images_labels(10)
@@ -93,8 +85,8 @@ def test_pt_aug_02_parallel_at_least_one_point_five_x_faster(
         shutil.copy2(p, img_dir / p.name)
     for p in src_lbl.glob("*.txt"):
         shutil.copy2(p, lbl_dir / p.name)
-    Path(c.processed_images_dir).mkdir(parents=True, exist_ok=True)
-    Path(c.processed_labels_dir).mkdir(parents=True, exist_ok=True)
+    Path(c.config.processed_images_dir).mkdir(parents=True, exist_ok=True)
+    Path(c.config.processed_labels_dir).mkdir(parents=True, exist_ok=True)
     names = sorted(p.name for p in img_dir.glob("*.jpg"))
 
     class _E:
@@ -113,8 +105,8 @@ def test_pt_aug_02_parallel_at_least_one_point_five_x_faster(
     seq_elapsed = time.perf_counter() - t0
 
     shutil.rmtree(proc_dir)
-    Path(c.processed_images_dir).mkdir(parents=True, exist_ok=True)
-    Path(c.processed_labels_dir).mkdir(parents=True, exist_ok=True)
+    Path(c.config.processed_images_dir).mkdir(parents=True, exist_ok=True)
+    Path(c.config.processed_labels_dir).mkdir(parents=True, exist_ok=True)
 
     aug_par = Augmentator()
     aug_par.total_images_to_process = len(entries)

tests/performance/test_dataset_perf.py

@@ -56,8 +56,8 @@ def _prepare_form_dataset(
     constants_patch(tmp_path)
     import train
 
-    proc_img = Path(c_mod.processed_images_dir)
-    proc_lbl = Path(c_mod.processed_labels_dir)
+    proc_img = Path(c_mod.config.processed_images_dir)
+    proc_lbl = Path(c_mod.config.processed_labels_dir)
     proc_img.mkdir(parents=True, exist_ok=True)
     proc_lbl.mkdir(parents=True, exist_ok=True)
 
@@ -70,14 +70,8 @@ def _prepare_form_dataset(
         if stem in corrupt_stems:
             dst.write_text("0 1.5 0.5 0.1 0.1\n", encoding="utf-8")
 
-    today_ds = osp.join(c_mod.datasets_dir, train.today_folder)
-    monkeypatch.setattr(train, "today_dataset", today_ds)
-    monkeypatch.setattr(train, "processed_images_dir", c_mod.processed_images_dir)
-    monkeypatch.setattr(train, "processed_labels_dir", c_mod.processed_labels_dir)
-    monkeypatch.setattr(train, "corrupted_images_dir", c_mod.corrupted_images_dir)
-    monkeypatch.setattr(train, "corrupted_labels_dir", c_mod.corrupted_labels_dir)
-    monkeypatch.setattr(train, "datasets_dir", c_mod.datasets_dir)
-    return train
+    today_ds = osp.join(c_mod.config.datasets_dir, train.today_folder)
+    return train, today_ds
 
 
 @pytest.mark.performance
@@ -88,7 +82,7 @@ def test_pt_dsf_01_dataset_formation_under_thirty_seconds(
     fixture_images_dir,
     fixture_labels_dir,
 ):
-    train = _prepare_form_dataset(
+    train, today_ds = _prepare_form_dataset(
         monkeypatch,
         tmp_path,
         constants_patch,