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Author	SHA1	Message	Date
dtoro	7558aeb5e6	fix: sync DB sessions in Celery, letterbox YuNet, dedupe detections - Rewrite all vision tasks to use sync psycopg2 sessions instead of asyncpg — fixes 'another operation in progress' and event loop errors when Celery forks workers sharing the async connection pool - Letterbox-pad images to exactly 640x640 for YuNet face detector (was crashing on non-square thumbnails) - Deduplicate object detections per label per photo — keep highest confidence only to avoid photo_tags PK violation on multiple detections of the same class - Add all queues (-Q default,high,low,vision) to worker command Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>	2026-04-10 10:28:17 +02:00
dtoro	2a6661f779	fix: model weights setup — export scripts, ORT compat, bootstrap - Add export_models.py for OpenCLIP ViT-B/32 and YOLOv8n ONNX export - Fix ArgMax(13) ORT ARM64 incompatibility by passing eot_indices as a separate ONNX input (computed outside the graph in embed.py) - Use legacy TorchScript exporter (dynamo=False) for IR version 9 compat - Upgrade onnxruntime to 1.18.1 - Rewrite bootstrap_models.py with clear separation of auto-downloadable models (YuNet, SFace) vs manually-exported ones (OpenCLIP, YOLOv8n) - Wire bootstrap into worker CMD (runs before Celery) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>	2026-04-10 09:41:25 +02:00
dtoro	9282a5c734	feat: add vision pipeline scaffolding with ONNX backend Introduce the app/services/vision/ module with ABC interfaces, ONNX Runtime backend, model registry, and per-task implementations: - OpenCLIP ViT-B/32 embedder (image + text, 512-d) - RapidOCR engine (PP-OCRv4 via ONNX, no PaddlePaddle) - YOLOv8n object detector (raw ONNX, no ultralytics runtime) - YuNet + SFace face processor (Apache 2.0, opencv_zoo, 128-d) - DBSCAN face clustering helper Add VisionSettings to config (mulita.yml + Pydantic), bootstrap_models.py for first-boot weight downloads, models_data Docker volume, and ROCm backend stub for future GPU acceleration. No Celery tasks wired yet — models load but nothing invokes them. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>	2026-04-10 09:00:06 +02:00

Author

SHA1

Message

Date

dtoro

7558aeb5e6

fix: sync DB sessions in Celery, letterbox YuNet, dedupe detections

- Rewrite all vision tasks to use sync psycopg2 sessions instead of
  asyncpg — fixes 'another operation in progress' and event loop errors
  when Celery forks workers sharing the async connection pool
- Letterbox-pad images to exactly 640x640 for YuNet face detector
  (was crashing on non-square thumbnails)
- Deduplicate object detections per label per photo — keep highest
  confidence only to avoid photo_tags PK violation on multiple
  detections of the same class
- Add all queues (-Q default,high,low,vision) to worker command

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

2026-04-10 10:28:17 +02:00

dtoro

2a6661f779

fix: model weights setup — export scripts, ORT compat, bootstrap

- Add export_models.py for OpenCLIP ViT-B/32 and YOLOv8n ONNX export
- Fix ArgMax(13) ORT ARM64 incompatibility by passing eot_indices as a
  separate ONNX input (computed outside the graph in embed.py)
- Use legacy TorchScript exporter (dynamo=False) for IR version 9 compat
- Upgrade onnxruntime to 1.18.1
- Rewrite bootstrap_models.py with clear separation of auto-downloadable
  models (YuNet, SFace) vs manually-exported ones (OpenCLIP, YOLOv8n)
- Wire bootstrap into worker CMD (runs before Celery)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

2026-04-10 09:41:25 +02:00

dtoro

9282a5c734

feat: add vision pipeline scaffolding with ONNX backend

Introduce the app/services/vision/ module with ABC interfaces, ONNX
Runtime backend, model registry, and per-task implementations:
- OpenCLIP ViT-B/32 embedder (image + text, 512-d)
- RapidOCR engine (PP-OCRv4 via ONNX, no PaddlePaddle)
- YOLOv8n object detector (raw ONNX, no ultralytics runtime)
- YuNet + SFace face processor (Apache 2.0, opencv_zoo, 128-d)
- DBSCAN face clustering helper

Add VisionSettings to config (mulita.yml + Pydantic), bootstrap_models.py
for first-boot weight downloads, models_data Docker volume, and ROCm
backend stub for future GPU acceleration.

No Celery tasks wired yet — models load but nothing invokes them.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

2026-04-10 09:00:06 +02:00

3 Commits