* Add margin to detected faces for embeddings
* Standardize pixel values for face input
* Use SVC to classify faces
* Clear classifier when new face is added
* Formatting
* Add dependency
* Update version
* Face recognition backend (#14495)
* Add basic config and face recognition table
* Reconfigure updates processing to handle face
* Crop frame to face box
* Implement face embedding calculation
* Get matching face embeddings
* Add support face recognition based on existing faces
* Use arcface face embeddings instead of generic embeddings model
* Add apis for managing faces
* Implement face uploading API
* Build out more APIs
* Add min area config
* Handle larger images
* Add more debug logs
* fix calculation
* Reduce timeout
* Small tweaks
* Use webp images
* Use facenet model
* Improve face recognition (#14537)
* Increase requirements for face to be set
* Manage faces properly
* Add basic docs
* Simplify
* Separate out face recognition frome semantic search
* Update docs
* Formatting
* Fix access (#14540)
* Face detection (#14544)
* Add support for face detection
* Add support for detecting faces during registration
* Set body size to be larger
* Undo
* Update version
* Face recognition backend (#14495)
* Add basic config and face recognition table
* Reconfigure updates processing to handle face
* Crop frame to face box
* Implement face embedding calculation
* Get matching face embeddings
* Add support face recognition based on existing faces
* Use arcface face embeddings instead of generic embeddings model
* Add apis for managing faces
* Implement face uploading API
* Build out more APIs
* Add min area config
* Handle larger images
* Add more debug logs
* fix calculation
* Reduce timeout
* Small tweaks
* Use webp images
* Use facenet model
* Improve face recognition (#14537)
* Increase requirements for face to be set
* Manage faces properly
* Add basic docs
* Simplify
* Separate out face recognition frome semantic search
* Update docs
* Formatting
* Fix access (#14540)
* Face detection (#14544)
* Add support for face detection
* Add support for detecting faces during registration
* Set body size to be larger
* Undo
* initial foundation for alpr with paddleocr
* initial foundation for alpr with paddleocr
* initial foundation for alpr with paddleocr
* config
* config
* lpr maintainer
* clean up
* clean up
* fix processing
* don't process for stationary cars
* fix order
* fixes
* check for known plates
* improved length and character by character confidence
* model fixes and small tweaks
* docs
* placeholder for non frigate+ model lp detection
---------
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* Add basic config and face recognition table
* Reconfigure updates processing to handle face
* Crop frame to face box
* Implement face embedding calculation
* Get matching face embeddings
* Add support face recognition based on existing faces
* Use arcface face embeddings instead of generic embeddings model
* Add apis for managing faces
* Implement face uploading API
* Build out more APIs
* Add min area config
* Handle larger images
* Add more debug logs
* fix calculation
* Reduce timeout
* Small tweaks
* Use webp images
* Use facenet model
* Add config option to select fp16 or quantized jina vision model
* requires_fp16 for text and large models only
* fix model type check
* fix cpu
* pass model size
* add generic onnx model class and use jina ai clip models for all embeddings
* fix merge confligt
* add generic onnx model class and use jina ai clip models for all embeddings
* fix merge confligt
* preferred providers
* fix paths
* disable download progress bar
* remove logging of path
* drop and recreate tables on reindex
* use cache paths
* fix model name
* use trust remote code per transformers docs
* ensure tokenizer and feature extractor are correctly loaded
* revert
* manually download and cache feature extractor config
* remove unneeded
* remove old clip and minilm code
* docs update
* swap sqlite_vec for chroma in requirements
* load sqlite_vec in embeddings manager
* remove chroma and revamp Embeddings class for sqlite_vec
* manual minilm onnx inference
* remove chroma in clip model
* migrate api from chroma to sqlite_vec
* migrate event cleanup from chroma to sqlite_vec
* migrate embedding maintainer from chroma to sqlite_vec
* genai description for sqlite_vec
* load sqlite_vec in main thread db
* extend the SqliteQueueDatabase class and use peewee db.execute_sql
* search with Event type for similarity
* fix similarity search
* install and add comment about transformers
* fix normalization
* add id filter
* clean up
* clean up
* fully remove chroma and add transformers env var
* readd uvicorn for fastapi
* readd tokenizer parallelism env var
* remove chroma from docs
* remove chroma from UI
* try removing custom pysqlite3 build
* hard code limit
* optimize queries
* revert explore query
* fix query
* keep building pysqlite3
* single pass fetch and process
* remove unnecessary re-embed
* update deps
* move SqliteVecQueueDatabase to db directory
* make search thumbnail take up full size of results box
* improve typing
* improve model downloading and add status screen
* daemon downloading thread
* catch case when semantic search is disabled
* fix typing
* build sqlite_vec from source
* resolve conflict
* file permissions
* try build deps
* remove sources
* sources
* fix thread start
* include git in build
* reorder embeddings after detectors are started
* build with sqlite amalgamation
* non-platform specific
* use wget instead of curl
* remove unzip -d
* remove sqlite_vec from requirements and load the compiled version
* fix build
* avoid race in db connection
* add scale_factor and bias to description zscore normalization
* Set caching options for hardware providers
* Always use CPU for searching
* Use new install strategy to remove onnxruntime and then install post wheels
* Initial re-implementation of semantic search
* put docker-compose back and make reindex match docs
* remove debug code and fix import
* fix docs
* manually build pysqlite3 as binaries are only available for x86-64
* update comment in build_pysqlite3.sh
* only embed objects
* better error handling when genai fails
* ask ollama to pull requested model at startup
* update ollama docs
* address some PR review comments
* fix lint
* use IPC to write description, update docs for reindex
* remove gemini-pro-vision from docs as it will be unavailable soon
* fix OpenAI doc available models
* fix api error in gemini and metadata for embeddings
