Architecture

Though you mostly interact with FindFace through its web interface, be sure to take a minute to learn the FindFace architecture. This knowledge is essential for the FindFace deployment, integration, maintenance, and troubleshooting.

In this chapter:

Architectural Elements

FindFace consists of the following fundamental architectural elements:

• FindFace core, a cutting-edge AI-based face recognition technology that can be used as a separate product FindFace Enterprise Server.

• FindFace, which is a turnkey application module for FindFace Enterprise Server.

Architecture scheme

FindFace Core

The FindFace core includes the following components:

Component	Ports in use	Description	Vendor
findface-extraction-api	18666	Service that uses neural networks to detect a face in an image and extract a face biometric sample (feature vector). It also performs recognition of face attributes such as gender, age, emotions, beard, glasses, face mask, and others, and silhouette recognition (if configured). CPU- or GPU-acceleration.	NtechLab own deployment
findface-sf-api	18411	Service that implements HTTP API for face detection and face recognition.
findface-tarantool-server	32001, shard ports (default 330xx, 81xx)	Service that provides interaction between the findface-sf-api service and the biometric database (database that stores face biometric samples) powered by Tarantool.
findface-upload	3333	NginX-based web server used as a storage for original images, thumbnails and normalized face images.
findface-facerouter	18820	Service used to define processing directives for detected faces. In FindFace Security, its functions are performed by findface-security (see FindFace Application Module). If necessary, you can still deploy and enable this component for integration purposes (see Custom Plugins).
findface-video-manager	18810, 18811	Service, part of the video face detection module, that is used for managing the video face detection functionality, configuring the video face detector settings and specifying the list of to-be-processed video streams.
findface-video-worker	18999	Service, part of the video face detection module, that recognizes a face in the video and posts its normalized image, full frame and metadata (such as the camera ID and detection time) to the findface-facerouter service for further processing according to given directives. Provides face liveness detection if enabled. CPU- or GPU-acceleration.
findface-ntls	443 (TCP), 3133, 3185	License server which interfaces with the NtechLab Global License Server or a USB dongle to verify the license of your FindFace instance.
Tarantool	Shard ports (default 330xx, 81xx)	Third-party software which implements the biometric database that stores extracted biometric samples (feature vectors) and face identification events. The system data, dossiers, user accounts, and camera settings are stored in PostgreSQL (part of the FindFace application module).	Tarantool
etcd	2379	Third-party software that implements a distributed key-value store for findface-video-manager. Used as a coordination service in the distributed system, providing the video face detector with fault tolerance.	etcd
NginX	80; SSL: 8002, 8003, 443, 80	Third-party software which implements the system web interfaces.	nginx
memcached	11211	Third-party software which implements a distributed memory caching system. Used by findface-extraction-api as a temporary storage for extracted face biometric samples before they are written to the biometric database powered by Tarantool.	memcached

FindFace Application Module

The FindFace application module includes the following components:

Component	Ports in use	Description	Vendor
findface-security	Configurable	Component that serves as a gateway to the FindFace core. Provides interaction between the FindFace Core and the web interface, the system functioning as a whole, HTTP and web socket, biometric monitoring, event notifications, episodes, webhooks, and counters. Includes the following internal services: NTLS checker, Counter manager, Webhooks manager, Persons clusterizator, Event episodes manager, and Video archive queue manager. The last four can be enabled and disabled via the /etc/findface-security/config.py configuration file.	NtechLab own deployment
findface-security-ui	Configurable	Main web interface that is used to interact with FindFace. Allows you to work with face identification events, search for faces, manage cameras, users, dossiers, and watch lists, collect real-time statistics, and many more.
findface-counter	18300	Service used for face deduplication.
findface-liveness-api	18301	Besides the embedded functionality provided by findface-video-worker, face liveness detection can also be harnessed as a standalone service findface-liveness-api. The service takes a specific number of frames from a video fragment and returns the best quality face, and decimal liveness result averaged across the taken frames. The service is also used for authentication based on facial recognition. See Liveness Detection as Standalone Service and Authentication and Session Monitoring.
PostgreSQL	5432	Third-party software which implements the main system database that stores detailed and categorized dossiers on particular persons, as well as data for internal use such as user accounts and camera settings. The face biometric data and face identification events are stored in Tarantool (part of the FindFace core).	PostgreSQL
Pgbouncer	5439	Third-party software, a lightweight connection pooler for PostgreSQL. Optional, used to increase the database performance under high load.	PgBouncer
Redis	6379	Third-party software which implements a message broker inside findface-security.	Redis
Django	5439	Third-party software which implements a web framework for the FindFace web interface.	Django

See also

Components in Depth

Single- and Multi-Host Deployment

You can deploy FindFace on a single host or in a cluster environment. If you opt for the latter, we offer you one of the following deployment schemes:

• Deploy FindFace standalone and distribute additional findface-video-worker components across multiple hosts.

• Distribute the FindFace components across multiple hosts. If necessary, set up load balancing.

See Guide to Typical Cluster Installation for details.

CPU- and GPU-acceleration

The findface-extraction-api and findface-video-worker services can be either CPU- or GPU-based. During installation from the developer-friendly installer, you will have an opportunity to choose the acceleration type you need.

If you opt to install FindFace from the repository package, deploy the findface-extraction-api and findface-video-worker-cpu packages on a CPU-based server, and the findface-extraction-api-gpu and/or findface-video-worker-gpu packages on a GPU-based server.

Important

Refer to System Requirements when choosing hardware configuration.

Important

If the resolution of a camera(s) in use is more than 1280x720px, it is strongly recommended to use the GPU-accelerated package findface-video-worker-gpu.

Note

The liveness detector is much slower on CPU than on GPU.