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41 lines
1.1 KiB
41 lines
1.1 KiB
using Microsoft.ML.OnnxRuntime.Tensors;
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using SixLabors.ImageSharp;
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using ZeroLevel.NN.Models;
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namespace ZeroLevel.NN
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{
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public sealed class FaceNet
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: SSDNN, IEncoder
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{
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private const int INPUT_WIDTH = 160;
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private const int INPUT_HEIGHT = 160;
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public FaceNet(string modelPath)
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: base(modelPath)
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{
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}
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public int InputW => INPUT_WIDTH;
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public int InputH => INPUT_HEIGHT;
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public float[] Predict(Image image)
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{
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var input = MakeInput(image,
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new ImagePreprocessorOptions(INPUT_WIDTH, INPUT_HEIGHT, PredictorChannelType.ChannelFirst)
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.ApplyCorrection((c,px) => (px / 127.5f) - 1f)
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.ApplyAxeInversion());
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return Predict(input);
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}
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public float[] Predict(Tensor<float> input)
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{
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float[] embedding = null;
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Extract(new Dictionary<string, Tensor<float>> { { "input.1", input } }, d =>
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{
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embedding = d.First().Value.ToArray();
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});
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Norm(embedding);
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return embedding;
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}
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}
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}
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