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/start_inference.md

@@ -0,0 +1,52 @@
+# Module: start_inference
+
+## Purpose
+Entry point for running inference on video files using a TensorRT engine. Downloads the encrypted model from the API/CDN, initializes the engine, and processes video.
+
+## Public Interface
+
+| Function | Signature | Returns | Description |
+|----------|-----------|---------|-------------|
+| `get_engine_filename` | `(device_id=0) -> str \| None` | Engine filename | Generates GPU-specific engine filename (duplicate of TensorRTEngine.get_engine_filename) |
+
+`__main__` block: Creates ApiClient, downloads encrypted TensorRT model (split big/small), initializes TensorRTEngine, runs Inference on a test video.
+
+## Internal Logic
+- **Model download flow**: ApiClient → `load_big_small_resource` → reassembles from local big part + API-downloaded small part → decrypts with model encryption key → raw engine bytes.
+- **Inference setup**: TensorRTEngine initialized from decrypted bytes, Inference configured with confidence_threshold=0.5, iou_threshold=0.3.
+- **Video source**: Hardcoded to `tests/ForAI_test.mp4`.
+- **get_engine_filename()**: Duplicates `TensorRTEngine.get_engine_filename()` — generates `azaion.cc_{major}.{minor}_sm_{sm_count}.engine` based on CUDA device compute capability and SM count.
+
+## Dependencies
+- `constants` — config file paths
+- `api_client` — ApiClient, ApiCredentials for model download
+- `cdn_manager` — CDNManager, CDNCredentials (imported but CDN managed by api_client)
+- `inference/inference` — Inference pipeline
+- `inference/tensorrt_engine` — TensorRTEngine
+- `security` — model encryption key
+- `utils` — Dotdict
+- `pycuda.driver` (external) — CUDA device queries
+- `yaml` (external)
+
+## Consumers
+None (entry point).
+
+## Data Models
+None.
+
+## Configuration
+- Confidence threshold: 0.5
+- IoU threshold: 0.3
+- Video path: `tests/ForAI_test.mp4` (hardcoded)
+
+## External Integrations
+- Azaion API + CDN for model download
+- TensorRT GPU inference
+- OpenCV video capture and display
+
+## Security
+- Model is downloaded encrypted (split big/small) and decrypted locally
+- Uses hardware-bound and model encryption keys
+
+## Tests
+None.