Introduction

SmartFace Embedded Toolkit (SFE Toolkit) is a modular, portable and easy-to-integrate SDK, that can be used in any facial recognition use case on various platforms.

Features#

SFE Toolkit supports the following features:

• Face detection
• Face landmarks extraction
• Face mask detection
• Face template extraction
• Face verification
• Face identification
• Face liveness detection
• Iris detection
• Iris template extraction
• Iris verification
• Iris identification

Platform support#

SFE Toolkit supports the following platforms:

• Windows x86_64,
• Linux x86_64,
• Android ARMv7 o and ARM64
• Embedded Linux ARMv7 and ARM64

If you need to support another OS or architecture, please contact your sales representative at Innovatrics.

HW acceleration#

The neural network models used in the libraries can be accelerated using one of the following neural network accelerators:

• Ambarella CVFlow (Ambarella SDK 3.0)
  • CV28
  • CV25
  • CV22
  • CV2
• Rockchip RKNPU (RKNPU 1.6.0)
  • RK1808/RK1806
  • RV1109/RV1126
• Rockchip RKNPU2 (RKNPU 1.5.2)
  • RK3566/RK3568
  • RK3588/RK3588S
  • RV1103/RV1106
  • RK3562
• Hailo-8 AI Accelerator
• NVidia GPUs and NVidia Jetson platforms with NVIDIA CUDA or TensorRT support
• NXP iMX8 (Tensorflow Lite -> VX delegate)

Download and install#

SFE Toolkit packages for various platforms are available to download at the Customer Portal.

Package#

Each of the SFE Toolkit packages consists of:

• root directory includes:
  • this readme file,
  • changelog,
  • EULA,
• doc directory includes documentation in HTML and PDF format,
• lib directory includes shared libraries compiled for one target CPU,
• solver directory includes a set of solvers compiled to be accelerated using a specific neural network accelerator,
• include directory includes header files with documentation of the C API,
• bin directory includes:
  • pre-built example applications demonstrating the usage and integration of the SFE Toolkit libraries,
  • License Manager application compiled for the target CPU,
• assets directory includes images for example applications.

Libraries#

SFE Toolkit consists of the following libraries:

• libsfe_core.so (sfe_core.dll on Windows)
  • solver loading
  • image operations
  • error handling
• libsfe_face.so (sfe_face.dll on Windows)
  • face detection
  • face landmarks detection
  • face mask detection
  • face template extraction
  • 1:1 face template matching
  • 1:N face template identification
  • face liveness detection
  • face and image quality attributes
• libsfe_iris.so (sfe_iris.dll on Windows)
  • iris detection
  • iris template extraction
  • 1:1 iris template matching
  • 1:N iris template identification

API#

SFE Toolkit libraries provide C API. We can also provide a binding with an example application for the following platforms:

• Python for Windows and Linux
• Kotlin for Android
• Swift for iOS
• .NET for Windows and Linux

Licensing#

You will need a valid license file to use the SmartFace Embedded Toolkit.

You can find more information on how to generate and deploy a license on this page

Example application#

To run the pre-built example application run the following commands in the package root directory:

export LD_LIBRARY_PATH=lib
bin/example_face

To display options run:

bin/example_face -h

If you want to build the application, please follow the instructions in example/readme.md

Support#

Please contact sfembedded-integration@innovatrics.com in case of any issues or questions.