mirror of
https://github.com/blakeblackshear/frigate.git
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24ac9f3e5a
* 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
22 lines
542 B
Python
22 lines
542 B
Python
from enum import Enum
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from typing import TypedDict
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from frigate.camera import CameraMetrics
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from frigate.object_detection import ObjectDetectProcess
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class StatsTrackingTypes(TypedDict):
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camera_metrics: dict[str, CameraMetrics]
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detectors: dict[str, ObjectDetectProcess]
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started: int
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latest_frigate_version: str
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last_updated: int
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processes: dict[str, int]
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class ModelStatusTypesEnum(str, Enum):
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not_downloaded = "not_downloaded"
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downloading = "downloading"
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downloaded = "downloaded"
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error = "error"
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