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/tests/resource-limit-tests.md

@@ -0,0 +1,31 @@
+# Resource Limit Test Scenarios
+
+## RL-AUG-01: Augmentation output count bounded
+- **Input**: 1 image
+- **Action**: Run `augment_inner()`
+- **Expected**: Returns exactly 8 outputs (never more, even with retries)
+- **Traces**: AC: 8× augmentation ratio (1 original + 7 augmented)
+
+## RL-DSF-01: Dataset split ratios sum to 100%
+- **Input**: Any number of images
+- **Action**: Check `train_set + valid_set + test_set`
+- **Expected**: Equals 100
+- **Traces**: AC: 70/20/10 split
+
+## RL-DSF-02: No data duplication across splits
+- **Input**: 100 images
+- **Action**: Run `form_dataset()`, collect all filenames across train/valid/test
+- **Expected**: No filename appears in more than one split
+- **Traces**: AC: Dataset integrity
+
+## RL-ENC-01: Encrypted output size bounded
+- **Input**: N bytes plaintext
+- **Action**: Encrypt
+- **Expected**: Ciphertext size ≤ N + 32 bytes (16 IV + up to 16 padding)
+- **Traces**: Restriction: AES-256-CBC overhead
+
+## RL-CLS-01: Total class count is exactly 80
+- **Input**: `classes.json`
+- **Action**: Generate class list for YAML
+- **Expected**: Exactly 80 entries (17 named × 3 weather + 29 placeholders = 80)
+- **Traces**: AC: 80 total class slots