Architecture¶
Though you mostly interact with FindFace Security through its web interface, be sure to take a minute to learn the FindFace Security architecture. This knowledge is essential for the FindFace Security deployment, integration, maintenance, and troubleshooting.
In this chapter:
Architectural Elements¶
FindFace Security 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 Security, which is a turnkey application module for FindFace Enterprise Server.
FindFace Core¶
The FindFace core includes the following components:
| Component | Description | Vendor |
|---|---|---|
| findface-extraction-api | 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 | Service that implements HTTP API for face detection and face recognition. | |
| findface-tarantool-server | 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 | NginX-based web server used as a storage for original images, thumbnails and normalized face images. | |
| findface-facerouter | Service used to define processing directives for detected faces. In FindFace
Security, its functions are performed by findface-security
(see FindFace Security Application Module). If necessary, you can still deploy and
enable this component for integration purposes (see Plugins). |
|
| findface-video-manager | 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 | 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. CPU- or GPU-acceleration. |
|
| findface-ntls | License server which interfaces with the NtechLab Global License Server or a USB dongle to verify the license of your FindFace Security instance. | |
| Tarantool | 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 Security application module). | Tarantool |
| etcd | 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 | Third-party software which implements the system web interfaces. | nginx |
| memcached | 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 Security Application Module¶
The FindFace Security application module includes the following components:
| Component | Description | Vendor |
|---|---|---|
| findface-security | 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, Webhooks manager, Persons
clusterizator, Event episodes manager, and Counter manager. The last four can be
disabled via the findface-security configuration file. |
NtechLab own deployment |
| ffsecurity-ui | Main web interface that is used to interact with FindFace Security. 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 | Service used for face deduplication. | |
| PostgreSQL | 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 | Third-party software, a lightweight connection pooler for PostgreSQL. Optional, used to increase the database performance under high load. | PgBouncer |
| Redis | Third-party software which implements a message broker inside findface-security. |
Redis |
| Django | Third-party software which implements a web framework for the FindFace Security web interface. | Django |
See also
Single- and Multi-Host Deployment¶
You can deploy FindFace Security 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 Security standalone and distribute additional
findface-video-workercomponents across multiple hosts. - Distribute the FindFace Security 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 Security 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.