mirror of
https://github.com/azaion/ai-training.git
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Oleksandr Bezdieniezhnykh
142c6c4de8
- 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.
3.6 KiB
3.6 KiB
Component Relationship Diagram
graph TD
subgraph "Core Infrastructure"
core[01 Core<br/>constants, utils]
end
subgraph "Security & Hardware"
sec[02 Security<br/>security, hardware_service]
end
subgraph "API & CDN Client"
api[03 API & CDN<br/>api_client, cdn_manager]
end
subgraph "Data Models"
dto[04 Data Models<br/>dto/annotationClass, dto/imageLabel]
end
subgraph "Data Pipeline"
data[05 Data Pipeline<br/>augmentation, convert-annotations,<br/>dataset-visualiser]
end
subgraph "Training Pipeline"
train[06 Training<br/>train, exports, manual_run]
end
subgraph "Inference Engine"
infer[07 Inference<br/>inference/*, start_inference]
end
subgraph "Annotation Queue Service"
queue[08 Annotation Queue<br/>annotation-queue/*]
end
core --> api
core --> data
core --> train
core --> infer
sec --> api
sec --> train
sec --> infer
api --> train
api --> infer
dto --> data
dto --> train
data -.->|augmented images<br/>on filesystem| train
queue -.->|annotation files<br/>on filesystem| data
style core fill:#e8f5e9
style sec fill:#fff3e0
style api fill:#e3f2fd
style dto fill:#f3e5f5
style data fill:#fce4ec
style train fill:#e0f2f1
style infer fill:#f9fbe7
style queue fill:#efebe9
Component Summary
| # | Component | Modules | Purpose |
|---|---|---|---|
| 01 | Core Infrastructure | constants, utils | Shared paths, config keys, helper classes |
| 02 | Security & Hardware | security, hardware_service | AES encryption, key derivation, hardware fingerprinting |
| 03 | API & CDN Client | api_client, cdn_manager | REST API + S3 CDN communication, split-resource pattern |
| 04 | Data Models | dto/annotationClass, dto/imageLabel | Annotation classes, image+label container |
| 05 | Data Pipeline | augmentation, convert-annotations, dataset-visualiser | Data prep: augmentation, format conversion, visualization |
| 06 | Training Pipeline | train, exports, manual_run | YOLO training, model export, encrypted upload |
| 07 | Inference Engine | inference/dto, onnx_engine, tensorrt_engine, inference, start_inference | Real-time video object detection |
| 08 | Annotation Queue | annotation_queue_dto, annotation_queue_handler | Async annotation event consumer service |
Module Coverage Verification
All 21 source modules are covered by exactly one component:
- 01: constants, utils (2)
- 02: security, hardware_service (2)
- 03: api_client, cdn_manager (2)
- 04: dto/annotationClass, dto/imageLabel (2)
- 05: augmentation, convert-annotations, dataset-visualiser (3)
- 06: train, exports, manual_run (3)
- 07: inference/dto, inference/onnx_engine, inference/tensorrt_engine, inference/inference, start_inference (5)
- 08: annotation-queue/annotation_queue_dto, annotation-queue/annotation_queue_handler (2)
- Total: 21 modules covered
Inter-Component Communication
| From | To | Mechanism |
|---|---|---|
| Annotation Queue → Data Pipeline | Filesystem | Queue writes images/labels → augmentation reads them |
| Data Pipeline → Training | Filesystem | Augmented images in /azaion/data-processed/ → dataset formation |
| Training → API & CDN | API calls | Encrypted model upload (split big/small) |
| Inference → API & CDN | API calls | Encrypted model download (reassemble big/small) |
| API & CDN → Security | Function calls | Encryption/decryption for transit protection |
| API & CDN → Core | Import | Path constants, config file references |