dtoro
fbeefb24a0
- detect_objects, classify_content, recluster_faces now look up the photo's user_id and set it on created Tag rows — fixes tags being invisible to the owning user due to NULL user_id - Initial admin setup creates source root at the mount root (/photos) instead of a subdirectory, since the admin owns the entire library - Revert to OpenCLIP ViT-B/32 (512-d) as default embedder — SigLIP requires transformers version alignment not yet available in the Docker image. SigLIP2 code remains for future enablement. - Add transformers to requirements for future SigLIP support Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
25 lines
951 B
Python
25 lines
951 B
Python
"""
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Embedding model — stores CLIP/SigLIP image embeddings via pgvector.
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Composite PK (photo_id, model) allows re-embedding with newer models
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without clobbering old vectors.
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Vector dimension is 768 to support SigLIP2 ViT-B/16 (the default).
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OpenCLIP ViT-B/32 (512-d) embeddings are zero-padded on insert so
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both models coexist in the same column. The padding is invisible to
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cosine similarity (zeros don't affect the angle).
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"""
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from sqlalchemy import Column, String, ForeignKey, DateTime, func
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from pgvector.sqlalchemy import Vector
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from app.database import Base
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class Embedding(Base):
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__tablename__ = 'embeddings'
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photo_id = Column(String, ForeignKey('photos.id', ondelete='CASCADE'), primary_key=True)
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model = Column(String(64), primary_key=True) # e.g. 'siglip2_vitb16'
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vector = Column(Vector(512)) # OpenCLIP ViT-B/32 → 512-d
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created_at = Column(DateTime(timezone=True), server_default=func.now())
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