Biometry (Face Matching)

The Biometry algorithm is intended to compare two or more photos and detect the level of similarity of the spotted faces. As a source media, the algorithm takes photos, videos, and documents (with photos).

Requirements

1. You're authorized.

2. You have already created a folder and added your media marked by correct tags into this folder.

Processing steps

1. Initiate the analysis for the folder: POST /api/folders/{{folder_id}}/analyses/

If you want to use a webhook for response, add it to the payload at this step, as described here.

{
  "analyses": [{
    "type": "biometry",
    "source_media": ["1111aaaa-11aa-11aa-11aa-111111aaaaaa"], // // optional; omit to include all media from the folder
  }]
}

You'll needanalyse_id or folder_id from response.

2. If you use a webhook, just wait for it to return the information needed. Otherwise, initiate polling:

• GET /api/analyses/{{analyse_id}} – for the analyse_id you have from the previous step.

• GET /api/folders/{{folder_id}} – for all analyses performed on media in the folder with the folder_id you have from the previous step.

Repeat until the resolution_status and resolution fields change status to any other except PROCESSING, and treat this as a result.

Check the response for the min_confidence value. It is a quantitative result of matching the people on the media uploaded.

[
  {
    // you may have multiple analyses in the list
    // pick the one you need by analyse_id or type
    "analyse_id": "1111aaaa-11aa-11aa-11aa-111111aaaaaa",
    "type": "BIOMETRY",
    "results_media": [
      {
        // if you have multiple media in one analysis, match score with media by source_video_id/source_shots_set_id 
        "source_video_id": "1111aaaa-11aa-11aa-11aa-111111aaaaab", // for shots_set media, the key would be source_shots_set_id 
        "results_data": 
        {
          "max_confidence": 0.997926354, 
          "min_confidence": 0.997926354 // quantitative score for this media
        }
      ...
    ]
    "resolution_status": "SUCCESS", // qualitative resolution (based on all media)
    ...
  }
  ...
]