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.

config.yaml

@@ -18,3 +18,15 @@ dirs:
   data_deleted: 'data_deleted'
   images: 'images'
   labels: 'labels'
+
+training:
+  model: 'yolo11m.yaml'
+  epochs: 120
+  batch: 11
+  imgsz: 1280
+  save_period: 1
+  workers: 24
+
+export:
+  onnx_imgsz: 1280
+  onnx_batch: 4