Evaluate Trueface: Getting Started
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Evaluate Trueface: Getting Started

This guide outlines the steps for getting started with an evaluation of Trueface's software. Assuming you have already been issued an evaluation token (if not, please contact the team), identify the right solution for your use case, verify your environment meets the minimum hardware requirements, and get started with the appropriate solution guides.

Step 1: Determine which solution is the most appropriate for your use case and deployment.

We currently offer four solutions, each tailored towards a different use case or deployment environment. Below is a quick summary of each solution. If you're still unsure which solution is best for your use case, contact sales or read through the main documentation page which has more information and download links for all solutions.

Trueface SDK

The Trueface SDK is the core of all our products and offers the highest level of performance and most freedom by supporting various configurations and options. The SDK is shipped as a static or dynamic library and offers a C++ API and Python bindings. It supports a variety of targets and architectures, including x86_64 and ARM, as well as CPU and GPU deployments.

The Trueface SDK provides the most flexibility to build your application the way you need as all API functions and modules are accessible, allowing you to build custom pipelines for your use case.

We advise using the SDK where performance is critical (latency and throughput) or when processing large amounts of data. Additionally, the SDK should be the first choice for edge deployments.

Trueface Visionbox

The Trueface Visionbox is a wrapper around the Trueface SDK which packages the SDK in a docker container and exposes the SDK face recognition APIs through REST API endpoints. It is the most flexible of our developer solutions and can interface with any programming language supporting REST APIs (which nearly all do), and it offers additional utility functions for convenience. This solution is great for remote server deployments where latency is not critical.

Ex: A browser client application running onboard an iPad sends images via REST from the onboard camera to a server running a Visionbox instance to run face recognition queries against a database.

Trueface Aware

Trueface Aware is the only no-code solution that comes complete with a user interface. This CCTV-monitoring app allows you to easily connect to IP cameras and create and manage face recognition collections and run queries against video streams.

EBT Solution

This semi-code solution requires one of our supported thermal cameras and is used to automatically screen for elevated body temperature. The solution runs directly onboard the camera at the edge and is capable of also running our LITE face recognition model directly onboard the camera for running identity verification at the edge.

Step 2: Ensure your target hardware meets the minimum and recommended hardware requirements.

Visit the following page and ensure your runtime hardware meets the minimum required hardware specified for the selected solution.

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Minimum & Recommended Hardware Requirements

Step 3: Get started with the appropriate guide below: