"embedding" Sink

Creates an embedding database in the directory specified by the address property. The database is segregated by channel and includes a dump of the embedding metadata with the associated jpeg-encoded image for every frame.

The embedding database is a nested directory structure. The first directory level is the channel ID, the second directory level is the individual frames. Finally, each frame folder contains the frame itself as a .jpg and an .emb file for each embedding in the frame.

info

When the arcface-identifier element is included in the pipeline, candidate identification .cid files will be generated for each frame.

tip

For a detailed example of how to use this sink, please refer to the Facial Recognition Example.

Examples

REST API

Create Sink:

{
    "type": "embedding",
    "address": "./tmp",
    "filter": []
}

Configuration File

Sample:

sinks:
- type: embedding
  address: ./tmp
  filter: []