Get Started¶
A typical Miracle-based biometric system is shown on the diagram below:
Miracle consists of the Biometric Data Analysis and Recognition Server (hereinafter referred to as Miracle Server or Server) and, optionally, the video face detector. Besides the latter, you can also install the other additional components. The Miracle Server functioning is provided by interaction of the following components:
| Service | Description |
|---|---|
| findface-facenapi | Python daemon which runs HTTP API. This daemon executes face detection functions, interfaces with MongoDB and findface-nnapi and tarantool@FindFace daemons. |
| tntapi (tarantool@FindFace as a shard) | Daemon which enables interaction with the face descriptors index. |
| findface-nnapi | Daemon extracts a feature vector (based on neural network). Requires the package with models <findface-data>.deb. |
| 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 the Global NTechLab License Server (for the network licensing) or a USB dongle (for the on-premise licensing) and passes a license to licensable components. |
Follow the diagram below to deploy Miracle and get ready for delivering face recognition services to your customers.
The 9 steps to face recognition:
- Choose deployment architecture
- Prepare hardware
- Install prerequisites
- Install Miracle
- Create a token and test the system work
- Configure video face detection
- Increase performance by setting up `nginx load balancing and fast index
- Add advanced features
- Finalize the system with coding