IdentificationVoting

Assign the most common identity out of the last 10 detections for that bounding box.

This module provides a pipeline element whose purpose is to remove some of the identification "noise" inherent in frame-by-frame identification. It achieves this by keeping a sliding windows of the last 10 identities for each bounding box and assigning the most common identity to the bounding box.

This pipeline element relies on the following elements for its metadata:

• tracking
• arcface-identifier

Examples:

REST API:

WIP

Configuration File:

short-from : identification-voting

```yaml
elements:
- name: infer
  args:
    model: yolov5s-face
    mode: a
    score_threshold: 0.3
    iou_threshold: 0.3
- name: demux
- name: face-alignment
- name: infer
  args:
    model: arcface
- name: mux
- name: arcface-identifier
  args:
    database: redis
- name: object-tracking
  args:
    max_age: 100
    history: 1000
    sampling_frequency: 10
- name: identification-voting
sources:
- address: videos/sample.mp4
  type: file
```

IdentificationVoting Objects

class IdentificationVoting(Element)

Assign the most common identity out of the last 10 detections for that bounding box.

Attributes:

• name str - Name of the element.

Examples:

```python
ele = IdentificationVoting()
```

process

def process(meta: PipelineMetadata)

Assign the most common identity out of the last 10 detections for that bounding box.

This is the main function for the element. In this case we are going to create a sliding window of the identities for specific bounding boxes and then vote on the most common identity for each window and assign it to the bounding box.

Arguments:

• meta PipelineMetadata - The metadata of the frame.

Returns:

• meta PipelineMetadata - The processed metadata.

Examples:

```python
ele = IdentificationVoting()
meta = ele.process(meta)
```