Get Started

Here you can see a typical biometric system based on FindFace Enterprise Server SDK:


FindFace Enterprise Server SDK consists of the Biometric Data Analysis and Recognition Server (FindFace Server or Server hereinafter) and, optionally, the video face detector and other additional components.

The FindFace Server functioning is provided by interaction of the following components:

Component Description
findface-facenapi Python daemon which runs HTTP API and provides the system functioning. It interfaces with MongoDB and extraction-api and tarantool@FindFace daemons.
tntapi (tarantool@FindFace as a shard) Daemon which enables interaction with the face descriptors index (Tarantool database).
findface-extraction-api Daemon which detects a face and extracts a feature vector (based on neural networks). Requires the packages with models <findface-data>.deb. Can also provide advanced functions.
MongoDB Database which stores faces metadata, galleries details, settings, etc.
findface-upload Nginx web server used to receive images using WebDAV.
NTLS Local license server which interfaces with NtechLab Global License Server (for network licensing) or a USB dongle (for on-premise licensing) and passes a license to licensable components.

Follow the 9 steps below to start delivering face recognition services to your customers:

  1. Choose deployment architecture
  2. Prepare hardware
  3. Install prerequisites
  4. Install FindFace Server
  5. Create a token and test the system work
  6. Configure video face detection
  7. Increase performance by setting up fast index
  8. Add advanced features
  9. Finalize the system with coding