using System.IO;
using System.Windows.Media;
using System.Windows.Media.Imaging;
using Xunit;
using ytLive.Models;
using ytLive.Services;
using ytLive.Services.BackgroundEffects;

namespace ytLive.Tests;

/// <summary>TASK 51 slice 1 — the background-effects engine.</summary>
public class BackgroundEffectEngineTests
{
    private sealed class FakeSegmenter : IPersonSegmenter
    {
        private readonly SegmentationMask? _mask;
        public int Calls;
        public FakeSegmenter(SegmentationMask? mask) => _mask = mask;
        public SegmentationMask? Segment(VideoFrame frame)
        {
            Calls++;
            return _mask;
        }
    }

    /// <summary>The integration test for this unit: a webcam frame run through the
    /// processor with Remove comes back with the person kept and the background
    /// transparent, colors untouched, flagged non-opaque so the compositor blends it.
    /// None is a true passthrough (same instance, segmenter never called).</summary>
    [Fact]
    public void Remove_keeps_the_person_and_makes_the_background_transparent()
    {
        const int w = 64, h = 32;
        var pixels = new byte[w * h * 4];
        for (var i = 0; i < pixels.Length; i += 4)
        {
            pixels[i] = 10; pixels[i + 1] = 20; pixels[i + 2] = 30; pixels[i + 3] = 255;
        }
        var frame = new VideoFrame(w, h, pixels) { IsOpaque = true };

        // 4×2 mask: left half person, right half background.
        var mask = new SegmentationMask(4, 2, new[] { 1f, 1f, 0f, 0f, 1f, 1f, 0f, 0f });
        var segmenter = new FakeSegmenter(mask);
        var processor = new BackgroundEffectProcessor(segmenter);

        Assert.Same(frame, processor.Apply(frame, BackgroundEffect.None));
        Assert.Equal(0, segmenter.Calls);

        var result = processor.Apply(frame, BackgroundEffect.Remove);

        Assert.NotSame(frame, result);
        Assert.False(result.IsOpaque);
        Assert.Equal(w, result.Width);
        Assert.Equal(h, result.Height);
        for (var y = 0; y < h; y++)
        {
            Assert.Equal(255, Alpha(result, 4, y));      // well inside the person half
            Assert.Equal(0, Alpha(result, w - 5, y));    // well inside the background half
        }
        for (var i = 0; i < pixels.Length; i += 4)
        {
            Assert.Equal(pixels[i], result.BgraPixels[i]);
            Assert.Equal(pixels[i + 1], result.BgraPixels[i + 1]);
            Assert.Equal(pixels[i + 2], result.BgraPixels[i + 2]);
        }
        Assert.Equal(255, frame.BgraPixels[(w - 5) * 4 + 3]); // source frame never mutated
    }

    /// <summary>Model contract: the BUNDLED (embedded) ONNX model, driven through the C#
    /// preprocessing, reproduces Google's own MediaPipe runtime on a fixed fixture.
    /// The expected mask was produced by tools/selfie-seg/ running the original .tflite in
    /// MediaPipe (fixture: MediaPipe's public test image mozart_square.jpg, a public-domain
    /// painting, cropped to 256×144). Guards the embedding, the input layout (RGB, NHWC,
    /// /255) and the conversion itself.</summary>
    [Fact]
    public void Bundled_model_matches_the_MediaPipe_reference_mask()
    {
        var frame = LoadBgra(Fixture("selfie-fixture-256x144.png"));
        var expected = LoadBgra(Fixture("selfie-fixture-expected-mask.png"));

        using var segmenter = new OnnxPersonSegmenter();
        var mask = segmenter.Segment(frame);

        Assert.NotNull(mask);
        Assert.Equal(OnnxPersonSegmenter.ModelWidth, mask!.Width);
        Assert.Equal(OnnxPersonSegmenter.ModelHeight, mask.Height);

        var agree = 0;
        var person = 0;
        for (var i = 0; i < mask.Width * mask.Height; i++)
        {
            var expectPerson = expected.BgraPixels[i * 4] > 127;
            var gotPerson = mask.Values[i] > 0.5f;
            if (expectPerson == gotPerson) agree++;
            if (gotPerson) person++;
        }
        var total = mask.Width * mask.Height;
        Assert.True(agree >= total * 0.995, $"binary agreement {100.0 * agree / total:0.00}% < 99.5%");
        Assert.InRange(100.0 * person / total, 45, 60); // reference: 52.5% person
    }

    private static int Alpha(VideoFrame f, int x, int y) => f.BgraPixels[(y * f.Width + x) * 4 + 3];

    private static string Fixture(string name) => Path.Combine(AppContext.BaseDirectory, "Fixtures", name);

    private static VideoFrame LoadBgra(string path)
    {
        using var stream = File.OpenRead(path);
        var decoded = BitmapDecoder.Create(stream, BitmapCreateOptions.PreservePixelFormat, BitmapCacheOption.OnLoad).Frames[0];
        var bgra = new FormatConvertedBitmap(decoded, PixelFormats.Bgra32, null, 0);
        var pixels = new byte[bgra.PixelWidth * bgra.PixelHeight * 4];
        bgra.CopyPixels(pixels, bgra.PixelWidth * 4, 0);
        return new VideoFrame(bgra.PixelWidth, bgra.PixelHeight, pixels);
    }
}