How to Check Your Media for Liveness without Oz Front End
Last updated
Last updated
Oz API is a rich Rest API for facial biometry, where you can do liveness checks and face matching. Oz API features are:
Persistence: your media and analysis are stored for future reference unless you explicitly delete it,
Ability to work with videos as well as images,
Asynchronous analyses,
Authentication,
Roles and access management.
The unit of work in Oz API is a folder: you can upload interrelated media to a folder, run analyses on them, and check for the aggregated result.
This step-by-step guide describes how to perform a liveness check on a facial image or video that you already have with Oz backend: create a folder, upload your media to this folder, initiate liveness check and poll for the results.
For better accuracy and user experience, we recommend that you use our Web and/or Native SDK on your front end for face capturing. Please refer to the relevant guides:
Before you begin, make sure you have Oz API credentials. When using SaaS API, you get them from us:
Login: j.doe@yourcompany.com Password: … API: https://sandbox.ohio.ozforensics.com Web Console: https://sandbox.ohio.ozforensics.com |
For the on-premise Oz API, you need to create a user yourself or ask your team that manages the API. See the guide on user creation via Web Console. Consider the proper user role (CLIENT
in most cases or CLIENT ADMIN
, if you are going to make SDK work with the pre-created folders from other API users). In the end, you need to obtain a similar set of credentials as you would get for the SaaS scenario.
You can explore all API methods with Oz Postman collection.
For security reasons, we recommend obtaining the access token instead of using the credentials. Call POST /api/authorize/auth with your login and password in the request body.
Get the access_token from the response and add it to the X-Forensic-Access-Token of all subsequence requests.
This step is not needed for API 5.0.0 and above.
With API 4.0.8 and below, Oz API requires video or archived sequence of images in order to perform liveness check. If you want to analyze a single image, you need to transform it into a ZIP archive. Oz API will treat this archive as a video.
Make sure that you use corresponding video-related tags later on.
To create a folder and upload your media into it, call POST /api/folders/ method, adding the media you need to the body part of the request.
In the payload field, set the appropriate tags:
The successful response will return code 201 and the folder_id
you’ll need later on.
To launch the analysis, call POST /api/folders/{{folder_id}}/analyses/ with the folder_id from the previous step. In the request body, specify the liveness check to be launched.
The results will be available in a short while. The method will return analyse_id that you’ll need at the next step.
Repeat calling GET /api/analyses/{{analyse_id}} with the analyse_id
from the previous step once a second until the state changes from PROCESSING
to something else. For a finished analysis:
get the qualitative result from resolution (SUCCESS
or DECLINED
).
get the quantitative results from results_media[0].results_data.confidence_spoofing
. confidence_spoofing
ranges from 0.0 (real person) to 1.0 (spoofing).
Here is the Postman collection for this guide.
With these steps completed, you are done with Liveness check via Oz API. You will be able to access your media and analysis results in Web UI via browser or programmatically via API.
Oz API methods can be combined with great flexibility. Explore Oz API using the API Developer Guide.