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/augmentation.md

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+# Module: augmentation
+
+## Purpose
+Image augmentation pipeline that takes raw annotated images and produces multiple augmented variants for training data expansion. Runs continuously in a loop.
+
+## Public Interface
+
+### Augmentator
+| Method | Signature | Returns | Description |
+|--------|-----------|---------|-------------|
+| `__init__` | `()` | — | Initializes augmentation transforms and counters |
+| `augment_annotations` | `(from_scratch: bool = False)` | — | Processes all unprocessed images from `data/images` → `data-processed/images` |
+| `augment_annotation` | `(image_file)` | — | Processes a single image file: reads image + labels, augments, saves results |
+| `augment_inner` | `(img_ann: ImageLabel) -> list[ImageLabel]` | List of augmented images | Generates 1 original + 7 augmented variants |
+| `correct_bboxes` | `(labels) -> list` | Corrected labels | Clips bounding boxes to image boundaries, removes tiny boxes |
+| `read_labels` | `(labels_path) -> list[list]` | Parsed YOLO labels | Reads YOLO-format label file into list of [x, y, w, h, class_id] |
+
+## Internal Logic
+- **Augmentation pipeline** (albumentations Compose):
+  1. HorizontalFlip (p=0.6)
+  2. RandomBrightnessContrast (p=0.4)
+  3. Affine: scale 0.8–1.2, rotate ±35°, shear ±10° (p=0.8)
+  4. MotionBlur (p=0.1)
+  5. HueSaturationValue (p=0.4)
+- Each image produces **8 outputs**: 1 original copy + 7 augmented variants
+- Naming: `{stem}_{1..7}.jpg` for augmented, original keeps its name
+- **Bbox correction**: clips bounding boxes that extend outside image borders, removes boxes smaller than `correct_min_bbox_size` (0.01 of image dimension)
+- **Incremental processing**: skips images already present in `processed_images_dir`
+- **Concurrent**: uses `ThreadPoolExecutor` for parallel processing
+- **Continuous mode**: `__main__` runs augmentation in an infinite loop with 5-minute sleep between rounds
+
+## Dependencies
+- `constants` — directory paths (data_images_dir, data_labels_dir, processed_*)
+- `dto/imageLabel` — ImageLabel container class
+- `albumentations` (external) — augmentation transforms
+- `cv2` (external) — image read/write
+- `numpy` (external) — image array handling
+- `concurrent.futures`, `os`, `shutil`, `time`, `datetime`, `pathlib` (stdlib)
+
+## Consumers
+manual_run
+
+## Data Models
+Uses `ImageLabel` from `dto/imageLabel`.
+
+## Configuration
+Hardcoded augmentation parameters (probabilities, ranges). Directory paths from `constants`.
+
+## External Integrations
+Filesystem I/O: reads from `/azaion/data/`, writes to `/azaion/data-processed/`.
+
+## Security
+None.
+
+## Tests
+None.