ArcFaceIdentifier

Search for a face and identification in an embedding database

This module provides a pipeline element to search for a face and identification in the embedding database. This module assumes that the embeddings have been created using the ArcFace model. By default, the embedding database is a Redis database. The embedding database uses an Approximately-Nearest-Neighbor (ANN) algorithm to find the nearest embedding. The embedding database needs to be populated with embeddings beforehand, there is an example under tools/facial_recognition.

Databases (<e-database>) currently supported are:

• Redis (redis)

Examples:

REST API:

WIP

Configuration File:

```yaml
elements:
- name: infer
  args:
    model: yolov5s-face
- name: demux
- name: face-alignment
- name: infer
  args:
    model: arcface
- name: mux
- name: arcface-identifier
  args:
    database: redis
    threshold: 0.3
sources:
- address: videos/sample.mp4
  type: file
```

is_redis_available

def is_redis_available(rs)

Check if the redis database is available

Arguments:

• rs redis.Redis - Redis database

Returns:

• bool - True if the database is available

Examples:

```python
rs = redis.Redis(host=HOST, port=PORT, db=0)
rs_ready = is_redis_available(rs)
```

create_embedding_db

def create_embedding_db(database)

Create an embedding database

Arguments:

• database str - The database to use

Returns:

• storage nearpy.storage.storage.Storage - The embedding database
• lshash nearpy.hashes.RandomBinaryProjections - The LSH algorithm

Raises:

• RuntimeError - If the database is not available, or if it is unable to find the EmbeddingHash configuration

Examples:

```python
embedding_storage, lshash = create_embedding_db("redis")
```

ArcFaceIdentifier Objects

class ArcFaceIdentifier(Element)

Search for an identification in the embedding database and assign it to the detection.

Attributes:

• name str - The name of the element
• database str - The database to use
• threshold float - The threshold to use

Examples:

```python
ele = ArcFaceIdentifier("redis")
```

process

def process(meta: PipelineMetadata)

Process the detections and assign the identification to the detection.

This is the main function for the element. It takes the detection and searches for the identification in the embedding database. If the identification string is found, the detection is assigned the identification. It also includes the three nearest neighbours as candidates.

Arguments:

• meta PipelineMetadata - The metadata to process.

Returns:

• meta PipelineMetadata - The processed metadata.

Examples:

```python
meta = ArcFaceIdentifier().process(meta)
```