mirror of
https://github.com/blakeblackshear/frigate.git
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198 lines
6.8 KiB
Python
198 lines
6.8 KiB
Python
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"""Maintain embeddings in Chroma."""
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import base64
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import io
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import logging
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import threading
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from multiprocessing.synchronize import Event as MpEvent
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from typing import Optional
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import cv2
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import numpy as np
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from peewee import DoesNotExist
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from PIL import Image
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from frigate.comms.events_updater import EventEndSubscriber, EventUpdateSubscriber
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from frigate.comms.inter_process import InterProcessRequestor
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from frigate.config import FrigateConfig
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from frigate.const import UPDATE_EVENT_DESCRIPTION
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from frigate.events.types import EventTypeEnum
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from frigate.genai import get_genai_client
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from frigate.models import Event
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from frigate.util.image import SharedMemoryFrameManager, calculate_region
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from .embeddings import Embeddings, get_metadata
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logger = logging.getLogger(__name__)
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class EmbeddingMaintainer(threading.Thread):
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"""Handle embedding queue and post event updates."""
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def __init__(
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self,
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config: FrigateConfig,
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stop_event: MpEvent,
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) -> None:
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threading.Thread.__init__(self)
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self.name = "embeddings_maintainer"
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self.config = config
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self.embeddings = Embeddings()
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self.event_subscriber = EventUpdateSubscriber()
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self.event_end_subscriber = EventEndSubscriber()
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self.frame_manager = SharedMemoryFrameManager()
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# create communication for updating event descriptions
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self.requestor = InterProcessRequestor()
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self.stop_event = stop_event
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self.tracked_events = {}
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self.genai_client = get_genai_client(config.genai)
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def run(self) -> None:
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"""Maintain a Chroma vector database for semantic search."""
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while not self.stop_event.is_set():
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self._process_updates()
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self._process_finalized()
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self.event_subscriber.stop()
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self.event_end_subscriber.stop()
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self.requestor.stop()
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logger.info("Exiting embeddings maintenance...")
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def _process_updates(self) -> None:
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"""Process event updates"""
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update = self.event_subscriber.check_for_update()
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if update is None:
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return
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source_type, _, camera, data = update
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if not camera or source_type != EventTypeEnum.tracked_object:
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return
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camera_config = self.config.cameras[camera]
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if data["id"] not in self.tracked_events:
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self.tracked_events[data["id"]] = []
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# Create our own thumbnail based on the bounding box and the frame time
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try:
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frame_id = f"{camera}{data['frame_time']}"
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yuv_frame = self.frame_manager.get(frame_id, camera_config.frame_shape_yuv)
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data["thumbnail"] = self._create_thumbnail(yuv_frame, data["box"])
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self.tracked_events[data["id"]].append(data)
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self.frame_manager.close(frame_id)
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except FileNotFoundError:
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pass
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def _process_finalized(self) -> None:
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"""Process the end of an event."""
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while True:
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ended = self.event_end_subscriber.check_for_update()
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if ended == None:
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break
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event_id, camera, updated_db = ended
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camera_config = self.config.cameras[camera]
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if updated_db:
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try:
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event: Event = Event.get(Event.id == event_id)
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except DoesNotExist:
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continue
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# Skip the event if not an object
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if event.data.get("type") != "object":
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continue
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# Extract valid event metadata
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metadata = get_metadata(event)
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thumbnail = base64.b64decode(event.thumbnail)
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# Embed the thumbnail
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self._embed_thumbnail(event_id, thumbnail, metadata)
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if (
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camera_config.genai.enabled
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and self.genai_client is not None
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and event.data.get("description") is None
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):
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# Generate the description. Call happens in a thread since it is network bound.
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threading.Thread(
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target=self._embed_description,
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name=f"_embed_description_{event.id}",
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daemon=True,
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args=(
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event,
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[
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data["thumbnail"]
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for data in self.tracked_events[event_id]
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]
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if len(self.tracked_events.get(event_id, [])) > 0
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else [thumbnail],
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metadata,
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),
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).start()
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# Delete tracked events based on the event_id
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if event_id in self.tracked_events:
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del self.tracked_events[event_id]
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def _create_thumbnail(self, yuv_frame, box, height=500) -> Optional[bytes]:
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"""Return jpg thumbnail of a region of the frame."""
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frame = cv2.cvtColor(yuv_frame, cv2.COLOR_YUV2BGR_I420)
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region = calculate_region(
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frame.shape, box[0], box[1], box[2], box[3], height, multiplier=1.4
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)
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frame = frame[region[1] : region[3], region[0] : region[2]]
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width = int(height * frame.shape[1] / frame.shape[0])
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frame = cv2.resize(frame, dsize=(width, height), interpolation=cv2.INTER_AREA)
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ret, jpg = cv2.imencode(".jpg", frame, [int(cv2.IMWRITE_JPEG_QUALITY), 100])
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if ret:
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return jpg.tobytes()
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return None
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def _embed_thumbnail(self, event_id: str, thumbnail: bytes, metadata: dict) -> None:
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"""Embed the thumbnail for an event."""
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# Encode the thumbnail
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img = np.array(Image.open(io.BytesIO(thumbnail)).convert("RGB"))
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self.embeddings.thumbnail.upsert(
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images=[img],
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metadatas=[metadata],
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ids=[event_id],
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)
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def _embed_description(
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self, event: Event, thumbnails: list[bytes], metadata: dict
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) -> None:
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"""Embed the description for an event."""
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description = self.genai_client.generate_description(thumbnails, metadata)
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if description is None:
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logger.debug("Failed to generate description for %s", event.id)
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return
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# fire and forget description update
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self.requestor.send_data(
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UPDATE_EVENT_DESCRIPTION,
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{"id": event.id, "description": description},
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)
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# Encode the description
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self.embeddings.description.upsert(
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documents=[description],
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metadatas=[metadata],
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ids=[event.id],
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)
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logger.debug(
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"Generated description for %s (%d images): %s",
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event.id,
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len(thumbnails),
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description,
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)
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