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.

_docs/02_document/modules/utils.md

@@ -0,0 +1,36 @@
+# Module: utils
+
+## Purpose
+Provides a dictionary subclass that supports dot-notation attribute access.
+
+## Public Interface
+
+| Name | Type | Signature |
+|------|------|-----------|
+| `Dotdict` | class (extends `dict`) | `Dotdict(dict)` |
+
+`Dotdict` overrides `__getattr__`, `__setattr__`, `__delattr__` to delegate to `dict.get`, `dict.__setitem__`, `dict.__delitem__` respectively.
+
+## Internal Logic
+Single-class module. Allows `config.url` instead of `config["url"]` for YAML-loaded dicts.
+
+## Dependencies
+None (stdlib `dict` only).
+
+## Consumers
+exports, train, start_inference
+
+## Data Models
+None.
+
+## Configuration
+None.
+
+## External Integrations
+None.
+
+## Security
+None.
+
+## Tests
+None.