Getting Started

1. Recognition presets

Exist several recognition presets that suitable for different use cases:

• Realtime - realtime preset, fast, suitable for real-time video processing
• Balanced - balance between processing speed and faces match accuracy
• Accurate - slow, but most accurate, suitable for systems where face match accuracy is more important

Recognition preset can be configured at service initialization with Settings.RecognitionPreset property.

2. Basic sample of using SDK

Initialization and Configuration

• The first step is to create a Settings object and then set the License field.

Note

To obtain a license please email to support@idscan.net.

• The second step is to create a FaceService object by passing in to constructor the Settings object created in the previous step.

• Now you are ready to make use of the library.

Warning

IFaceService implements the IDisposable interface. So the SDK must be initialized only once at startup and disposed at the end.

Basic Sample

using System;
using System.IO;
using System.Linq;                
using System.Threading;
using System.Threading.Tasks;
using IDScanNet.Faces.SDK;

namespace Sample
{
    class Program
    {
        public static async Task Main(string[] args)
        {                   
            Console.WriteLine("Hello World!");
            
            // path to license file
            var licenseFilePath = Path.Combine(AppContext.BaseDirectory,"idscannet.facesdk.license");
                        
            var settings = new Settings
            {                
                License = File.ReadAllBytes(licenseFilePath),
                RecognitionPreset = RecognitionPreset.Realtime                              
            };
                  
            // create and initialize face service
            using var service = new FaceService(settings);

            var image1 = File.ReadAllBytes("image1.jpg");
            var image2 = File.ReadAllBytes("image2.jpg");
            
            // detect face from given image1
            using var faceSample1 = await service.DetectSingleAsync(image1);
            
            // detect face from given image2
            using var faceSample2 = await service.DetectSingleAsync(image2);

            // compute face templates
            using var template1 = await service.ComputeTemplateAsync(faceSample1);
            using var template2 = await service.ComputeTemplateAsync(faceSample2);

            // compare two templates
            var matchResult = await service.MatchAsync(template1, template2);
            
            Console.WriteLine($"Match result: {matchResult.Score*100f} %");
        }
    }
}

A sample project can be found on Github (https://github.com/IDScanNet/IDScanNet.Faces.SDK.Samples)