2 Commits

Author	SHA1	Message	Date
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