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// build features and labels
var features = NetUtil.Var(new int[] { 7 }, DataType.Float);
var labels = NetUtil.Var(new int[] { 1 }, DataType.Float);

// the rest of the code goes here...

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// file paths
private const string inputFilePath = "./pillow.jpg";

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// export the modified image
Dlib.SaveJpeg(img, "output.jpg");

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// create a color palette for plotting
var palette = new RgbPixel[]
{
    new RgbPixel(0xe6, 0x19, 0x4b),
    new RgbPixel(0xf5, 0x82, 0x31),
    new RgbPixel(0xff, 0xe1, 0x19),
    new RgbPixel(0xbc, 0xf6, 0x0c),
    new RgbPixel(0x3c, 0xb4, 0x4b),
    new RgbPixel(0x46, 0xf0, 0xf0),
    new RgbPixel(0x43, 0x63, 0xd8),

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// use the chinese whispers algorithm to find all face clusters
Dlib.ChineseWhispers(edges, 100, out var clusters, out var labels);
Console.WriteLine($"   Found {clusters} unique person(s) in the image");

// the rest of the code goes here...

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// compare each face with all other faces
var edges = new List<SamplePair>();
for (uint i = 0; i < descriptors.Count; ++i)
    for (var j = i; j < descriptors.Count; ++j)

        // record every pair of two similar faces
        // faces are similar if they are less than 0.6 apart in the 128D embedding space
        if (Dlib.Length(descriptors[i] - descriptors[j]) < 0.6)
            edges.Add(new SamplePair(i, j));

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// compare each face with all other faces
var edges = new List<SamplePair>();
for (uint i = 0; i < descriptors.Count; ++i)
    for (var j = i; j < descriptors.Count; ++j)

        // record every pair of two similar faces
        // faces are similar if they are less than 0.6 apart in the 128D embedding space
        if (Dlib.Length(descriptors[i] - descriptors[j]) < 0.6)
            edges.Add(new SamplePair(i, j));

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// put each fae in a 128D embedding space
// similar faces will be placed close together
Console.WriteLine("Recognizing faces...");
var descriptors = dnn.Operator(chips);

// the rest of the code goes here...

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// detect all faces
var chips = new List<Matrix<RgbPixel>>();
var faces = new List<Rectangle>();
Console.WriteLine("Detecting faces...");
foreach (var face in detector.Operator(img))
{
    // detect landmarks
    var shape = predictor.Detect(img, face);

    // extract normalized and rotated 150x150 face chip

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using System.Collections.Generic;
using System;
using DlibDotNet;

namespace FaceClustering
{
    /// <summary>
    /// The program class.
    /// </summary>
    class Program