Repository: NsfwSpy/NsfwSpy.NET
Branch: main
Commit: adce13ada009
Files: 59
Total size: 97.6 KB

Directory structure:
gitextract_qx2j5oyu/

├── .gitignore
├── LICENSE
├── NsfwSpy/
│   ├── INsfwSpy.cs
│   ├── NsfwSpy.cs
│   ├── NsfwSpy.csproj
│   └── Resources/
│       ├── ClassificationFailedException.cs
│       ├── EClassificationType.cs
│       ├── ModelInput.cs
│       ├── ModelOutput.cs
│       ├── NsfwSpyFramesResult.cs
│       ├── NsfwSpyResult.cs
│       ├── NsfwSpyValue.cs
│       └── VideoOptions.cs
├── NsfwSpy.App/
│   ├── Controllers/
│   │   └── NsfwSpyController.cs
│   ├── NsfwSpy.App.csproj
│   ├── Pages/
│   │   ├── Error.cshtml
│   │   ├── Error.cshtml.cs
│   │   └── _ViewImports.cshtml
│   ├── Program.cs
│   ├── Properties/
│   │   └── launchSettings.json
│   ├── README.md
│   ├── appsettings.json
│   └── client-app/
│       ├── .gitignore
│       ├── package.json
│       ├── public/
│       │   ├── index.html
│       │   ├── manifest.json
│       │   └── robots.txt
│       ├── src/
│       │   ├── App.scss
│       │   ├── App.tsx
│       │   ├── aspnetcore-https.ts
│       │   ├── aspnetcore-react.ts
│       │   ├── components/
│       │   │   └── Logo/
│       │   │       ├── Logo.scss
│       │   │       └── Logo.tsx
│       │   ├── functions/
│       │   │   ├── client.ts
│       │   │   ├── getContentType.ts
│       │   │   ├── selectFiles.ts
│       │   │   └── sortBy.ts
│       │   ├── index.scss
│       │   ├── index.tsx
│       │   ├── models/
│       │   │   ├── ImageFile.ts
│       │   │   ├── MediaInfo.ts
│       │   │   ├── NsfwSpyFramesResult.ts
│       │   │   └── NsfwSpyResult.ts
│       │   ├── react-app-env.d.ts
│       │   └── reportWebVitals.ts
│       └── tsconfig.json
├── NsfwSpy.PerformanceTesting/
│   ├── NsfwSpy.PerformanceTesting.csproj
│   ├── PerformanceResult.cs
│   └── Program.cs
├── NsfwSpy.Test/
│   ├── Assets/
│   │   ├── bikini.mkv
│   │   └── bikini.webm
│   ├── NsfwSpy.Test.csproj
│   └── UnitTests.cs
├── NsfwSpy.Train/
│   ├── ImageData.cs
│   ├── NsfwSpy.Train.csproj
│   ├── Program.cs
│   └── tfjs-convert-command.txt
├── NsfwSpy.sln
└── README.md

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================================================
FILE: LICENSE
================================================
MIT License

Copyright (c) 2021 d00ML0rDz

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.


================================================
FILE: NsfwSpy/INsfwSpy.cs
================================================
using System;
using System.Collections.Generic;
using System.Net;
using System.Threading.Tasks;

namespace NsfwSpyNS
{
    public interface INsfwSpy
    {
        NsfwSpyFramesResult ClassifyGif(byte[] gifImage, VideoOptions videoOptions = null);
        NsfwSpyFramesResult ClassifyGif(string filePath, VideoOptions videoOptions = null);
        NsfwSpyFramesResult ClassifyGif(Uri uri, WebClient webClient = null, VideoOptions videoOptions = null);
        Task<NsfwSpyFramesResult> ClassifyGifAsync(string filePath, VideoOptions videoOptions = null);
        Task<NsfwSpyFramesResult> ClassifyGifAsync(Uri uri, WebClient webClient = null, VideoOptions videoOptions = null);
        NsfwSpyResult ClassifyImage(byte[] imageData);
        NsfwSpyResult ClassifyImage(string filePath);
        NsfwSpyResult ClassifyImage(Uri uri, WebClient webClient = null);
        Task<NsfwSpyResult> ClassifyImageAsync(string filePath);
        Task<NsfwSpyResult> ClassifyImageAsync(Uri uri, WebClient webClient = null);
        List<NsfwSpyValue> ClassifyImages(IEnumerable<string> filesPaths, Action<string, NsfwSpyResult> actionAfterEachClassify = null);
        NsfwSpyFramesResult ClassifyVideo(byte[] video, VideoOptions videoOptions = null);
        NsfwSpyFramesResult ClassifyVideo(string filePath, VideoOptions videoOptions = null);
        NsfwSpyFramesResult ClassifyVideo(Uri uri, WebClient webClient = null, VideoOptions videoOptions = null);
        Task<NsfwSpyFramesResult> ClassifyVideoAsync(string filePath, VideoOptions videoOptions = null);
        Task<NsfwSpyFramesResult> ClassifyVideoAsync(Uri uri, WebClient webClient = null, VideoOptions videoOptions = null);
    }
}

================================================
FILE: NsfwSpy/NsfwSpy.cs
================================================
using HeyRed.Mime;
using ImageMagick;
using Microsoft.ML;
using System;
using System.Collections.Concurrent;
using System.Collections.Generic;
using System.IO;
using System.Linq;
using System.Net;
using System.Threading.Tasks;

namespace NsfwSpyNS
{
    /// <summary>
    /// The NsfwSpy classifier class used to analyse images for explicit content.
    /// </summary>
    public class NsfwSpy : INsfwSpy
    {
        private static ITransformer _model;

        public NsfwSpy()
        {
            if (_model == null)
            {
                var modelPath = Path.Combine(AppContext.BaseDirectory, "NsfwSpyModel.zip");
                var mlContext = new MLContext();
                _model = mlContext.Model.Load(modelPath, out var modelInputSchema);
            }
        }

        /// <summary>
        /// Classify an image from a byte array.
        /// </summary>
        /// <param name="imageData">The image content read as a byte array.</param>
        /// <returns>A NsfwSpyResult that indicates the predicted value and scores for the 5 categories of classification.</returns>
        public NsfwSpyResult ClassifyImage(byte[] imageData)
        {
            var fileType = MimeGuesser.GuessFileType(imageData);
            if (fileType.Extension == "webp")
            {
                using (MagickImage image = new MagickImage(imageData))
                {
                    imageData = image.ToByteArray(MagickFormat.Png);
                }
            }

            var modelInput = new ModelInput(imageData);
            var mlContext = new MLContext();
            var predictionEngine = mlContext.Model.CreatePredictionEngine<ModelInput, ModelOutput>(_model);
            var modelOutput = predictionEngine.Predict(modelInput);
            return new NsfwSpyResult(modelOutput);
        }

        /// <summary>
        /// Classify an image from a file path.
        /// </summary>
        /// <param name="filePath">Path to the image to be classified.</param>
        /// <returns>A NsfwSpyResult that indicates the predicted value and scores for the 5 categories of classification.</returns>
        public NsfwSpyResult ClassifyImage(string filePath)
        {
            var fileBytes = File.ReadAllBytes(filePath);
            var result = ClassifyImage(fileBytes);
            return result;
        }

        /// <summary>
        /// Classify an image from a web url.
        /// </summary>
        /// <param name="uri">Web address of the image to be classified.</param>
        /// <param name="webClient">A custom WebClient to download the image with.</param>
        /// <returns>A NsfwSpyResult that indicates the predicted value and scores for the 5 categories of classification.</returns>
        public NsfwSpyResult ClassifyImage(Uri uri, WebClient webClient = null)
        {
            if (webClient == null) webClient = new WebClient();

            var fileBytes = webClient.DownloadData(uri);
            var result = ClassifyImage(fileBytes);
            return result;
        }

        /// <summary>
        /// Classify an image from a file path asynchronously.
        /// </summary>
        /// <param name="filePath">Path to the image to be classified.</param>
        /// <returns>A NsfwSpyResult that indicates the predicted value and scores for the 5 categories of classification.</returns>
        public async Task<NsfwSpyResult> ClassifyImageAsync(string filePath)
        {
            var fileBytes = await File.ReadAllBytesAsync(filePath);
            var result = ClassifyImage(fileBytes);
            return result;
        }

        /// <summary>
        /// Classify an image from a web url asynchronously.
        /// </summary>
        /// <param name="uri">Web address of the image to be classified.</param>
        /// <param name="webClient">A custom WebClient to download the image with.</param>
        /// <returns>A NsfwSpyResult that indicates the predicted value and scores for the 5 categories of classification.</returns>
        public async Task<NsfwSpyResult> ClassifyImageAsync(Uri uri, WebClient webClient = null)
        {
            if (webClient == null) webClient = new WebClient();

            var fileBytes = await webClient.DownloadDataTaskAsync(uri);
            var result = ClassifyImage(fileBytes);
            return result;
        }

        /// <summary>
        /// Classify multiple images from a list of file paths.
        /// </summary>
        /// <param name="filesPaths">Collection of file paths to be classified.</param>
        /// <param name="actionAfterEachClassify">Action to be invoked after each file is classified.</param>
        /// <returns>A list of results with their associated file paths.</returns>
        public List<NsfwSpyValue> ClassifyImages(IEnumerable<string> filesPaths, Action<string, NsfwSpyResult> actionAfterEachClassify = null)
        {
            var results = new ConcurrentBag<NsfwSpyValue>();
            var sync = new object();

            Parallel.ForEach(filesPaths, filePath =>
            {
                var result = ClassifyImage(filePath);
                var value = new NsfwSpyValue(filePath, result);
                results.Add(value);

                lock (sync)
                {
                    if (actionAfterEachClassify != null)
                        actionAfterEachClassify.Invoke(filePath, result);
                }
            });

            return results.ToList();
        }

        /// <summary>
        /// Classify a .gif file from a byte array.
        /// </summary>
        /// <param name="gifImage">The Gif content read as a byte array.</param>
        /// <param name="videoOptions">VideoOptions to customise how the frames of the file are classified.</param>
        /// <returns>A NsfwSpyFramesResult with results for each frame classified.</returns>
        public NsfwSpyFramesResult ClassifyGif(byte[] gifImage, VideoOptions videoOptions = null)
        {
            if (videoOptions == null)
                videoOptions = new VideoOptions();

            if (videoOptions.ClassifyEveryNthFrame < 1)
                throw new Exception("VideoOptions.ClassifyEveryNthFrame must not be less than 1.");

            var results = new ConcurrentDictionary<int, NsfwSpyResult>();

            using (var collection = new MagickImageCollection(gifImage))
            {
                collection.Coalesce();
                var frameCount = collection.Count;

                Parallel.For(0, frameCount, (i, state) =>
                {
                    if (i % videoOptions.ClassifyEveryNthFrame != 0)
                        return;

                    if (state.ShouldExitCurrentIteration)
                        return;

                    var frame = collection[i];
                    var frameData = frame.ToByteArray();
                    var result = ClassifyImage(frameData);
                    results.GetOrAdd(i, result);

                    // Stop classifying frames if Nsfw frame is found
                    if (result.IsNsfw && videoOptions.EarlyStopOnNsfw)
                        state.Break();
                });
            }

            var resultDictionary = results.OrderBy(r => r.Key).ToDictionary(r => r.Key, r => r.Value);
            var gifResult = new NsfwSpyFramesResult(resultDictionary);
            return gifResult;
        }

        /// <summary>
        /// Classify a .gif file from a path.
        /// </summary>
        /// <param name="filePath">Path to the .gif to be classified.</param>
        /// <param name="videoOptions">VideoOptions to customise how the frames of the file are classified.</param>
        /// <returns>A NsfwSpyFramesResult with results for each frame classified.</returns>
        public NsfwSpyFramesResult ClassifyGif(string filePath, VideoOptions videoOptions = null)
        {
            var gifImage = File.ReadAllBytes(filePath);
            var results = ClassifyGif(gifImage, videoOptions);
            return results;
        }

        /// <summary>
        /// Classify a .gif file  from a web url.
        /// </summary>
        /// <param name="uri">Web address of the Gif to be classified.</param>
        /// <param name="webClient">A custom WebClient to download the Gif with.</param>
        /// <param name="videoOptions">VideoOptions to customise how the frames of the file are classified.</param>
        /// <returns>A NsfwSpyFramesResult with results for each frame classified.</returns>
        public NsfwSpyFramesResult ClassifyGif(Uri uri, WebClient webClient = null, VideoOptions videoOptions = null)
        {
            if (webClient == null) webClient = new WebClient();

            var gifImage = webClient.DownloadData(uri);
            var results = ClassifyGif(gifImage, videoOptions);
            return results;
        }

        /// <summary>
        /// Classify a .gif file from a path asynchronously.
        /// </summary>
        /// <param name="filePath">Path to the .gif to be classified.</param>
        /// <param name="videoOptions">VideoOptions to customise how the frames of the file are classified.</param>
        /// <returns>A NsfwSpyFramesResult with results for each frame classified.</returns>
        public async Task<NsfwSpyFramesResult> ClassifyGifAsync(string filePath, VideoOptions videoOptions = null)
        {
            var gifImage = await File.ReadAllBytesAsync(filePath);
            var results = ClassifyGif(gifImage, videoOptions);
            return results;
        }

        /// <summary>
        /// Classify a .gif file  from a web url asynchronously.
        /// </summary>
        /// <param name="uri">Web address of the Gif to be classified.</param>
        /// <param name="webClient">A custom WebClient to download the Gif with.</param>
        /// <param name="videoOptions">VideoOptions to customise how the frames of the file are classified.</param>
        /// <returns>A NsfwSpyFramesResult with results for each frame classified.</returns>
        public async Task<NsfwSpyFramesResult> ClassifyGifAsync(Uri uri, WebClient webClient = null, VideoOptions videoOptions = null)
        {
            if (webClient == null) webClient = new WebClient();

            var gifImage = await webClient.DownloadDataTaskAsync(uri);
            var results = ClassifyGif(gifImage, videoOptions);
            return results;
        }

        /// <summary>
        /// Classify a video file from a byte array.
        /// </summary>
        /// <param name="video">The video content read as a byte array.</param>
        /// <param name="videoOptions">VideoOptions to customise how the frames of the file are classified.</param>
        /// <returns>A NsfwSpyFramesResult with results for each frame classified.</returns>
        public NsfwSpyFramesResult ClassifyVideo(byte[] video, VideoOptions videoOptions = null)
        {
            if (videoOptions == null)
                videoOptions = new VideoOptions();

            if (videoOptions.ClassifyEveryNthFrame < 1)
                throw new Exception("VideoOptions.ClassifyEveryNthFrame must not be less than 1.");

            var results = new ConcurrentDictionary<int, NsfwSpyResult>();

            using (var collection = new MagickImageCollection(video, MagickFormat.Mp4))
            {
                collection.Coalesce();
                var frameCount = collection.Count;

                Parallel.For(0, frameCount, (i, state) =>
                {
                    if (i % videoOptions.ClassifyEveryNthFrame != 0)
                        return;

                    if (state.ShouldExitCurrentIteration)
                        return;

                    var frame = collection[i];
                    frame.Format = MagickFormat.Jpg;

                    var result = ClassifyImage(frame.ToByteArray());
                    results.GetOrAdd(i, result);

                    // Stop classifying frames if Nsfw frame is found
                    if (result.IsNsfw && videoOptions.EarlyStopOnNsfw)
                        state.Break();
                });
            }

            var resultDictionary = results.OrderBy(r => r.Key).ToDictionary(r => r.Key, r => r.Value);
            var gifResult = new NsfwSpyFramesResult(resultDictionary);
            return gifResult;
        }

        /// <summary>
        /// Classify a .gif file from a path.
        /// </summary>
        /// <param name="filePath">Path to the video to be classified.</param>
        /// <param name="videoOptions">VideoOptions to customise how the frames of the file are classified.</param>
        /// <returns>A NsfwSpyFramesResult with results for each frame classified.</returns>
        public NsfwSpyFramesResult ClassifyVideo(string filePath, VideoOptions videoOptions = null)
        {
            var video = File.ReadAllBytes(filePath);
            var results = ClassifyVideo(video, videoOptions);
            return results;
        }

        /// <summary>
        /// Classify a .gif file  from a web url.
        /// </summary>
        /// <param name="uri">Web address of the video to be classified.</param>
        /// <param name="webClient">A custom WebClient to download the video with.</param>
        /// <param name="videoOptions">VideoOptions to customise how the frames of the file are classified.</param>
        /// <returns>A NsfwSpyFramesResult with results for each frame classified.</returns>
        public NsfwSpyFramesResult ClassifyVideo(Uri uri, WebClient webClient = null, VideoOptions videoOptions = null)
        {
            if (webClient == null) webClient = new WebClient();

            var video = webClient.DownloadData(uri);
            var results = ClassifyVideo(video, videoOptions);
            return results;
        }

        /// <summary>
        /// Classify a .gif file from a path asynchronously.
        /// </summary>
        /// <param name="filePath">Path to the video to be classified.</param>
        /// <param name="videoOptions">VideoOptions to customise how the frames of the file are classified.</param>
        /// <returns>A NsfwSpyFramesResult with results for each frame classified.</returns>
        public async Task<NsfwSpyFramesResult> ClassifyVideoAsync(string filePath, VideoOptions videoOptions = null)
        {
            var video = await File.ReadAllBytesAsync(filePath);
            var results = ClassifyVideo(video, videoOptions);
            return results;
        }

        /// <summary>
        /// Classify a .gif file  from a web url asynchronously.
        /// </summary>
        /// <param name="uri">Web address of the video to be classified.</param>
        /// <param name="webClient">A custom WebClient to download the video with.</param>
        /// <param name="videoOptions">VideoOptions to customise how the frames of the file are classified.</param>
        /// <returns>A NsfwSpyFramesResult with results for each frame classified.</returns>
        public async Task<NsfwSpyFramesResult> ClassifyVideoAsync(Uri uri, WebClient webClient = null, VideoOptions videoOptions = null)
        {
            if (webClient == null) webClient = new WebClient();

            var video = await webClient.DownloadDataTaskAsync(uri);
            var results = ClassifyVideo(video, videoOptions);
            return results;
        }
    }
}


================================================
FILE: NsfwSpy/NsfwSpy.csproj
================================================
<Project Sdk="Microsoft.NET.Sdk">

  <PropertyGroup>
    <TargetFramework>netcoreapp2.0</TargetFramework>
    <Authors>NsfwSpy</Authors>
    <Company>NsfwSpy</Company>
    <PackageTags>nsfw nude nudity porn pornography explicit image detect detection classification classifier machinglearning ml.net</PackageTags>
    <Description>NsfwSpy is an image and video classifier used to identify explicit/pornographic content using machine learning.</Description>
    <RepositoryUrl>https://github.com/NsfwSpy/NsfwSpy.NET</RepositoryUrl>
    <PackageProjectUrl>https://github.com/NsfwSpy/NsfwSpy.NET</PackageProjectUrl>
    <PackageIcon>NsfwSpy-Icon.png</PackageIcon>
    <PackageIconUrl />
    <PackageLicenseExpression></PackageLicenseExpression>
    <PackageRequireLicenseAcceptance>false</PackageRequireLicenseAcceptance>
    <PackageLicenseFile>LICENSE</PackageLicenseFile>
    <Version>3.5.0</Version>
  </PropertyGroup>

  <ItemGroup>
    <PackageReference Include="Magick.NET-Q16-AnyCPU" Version="11.1.2" />
    <PackageReference Include="Microsoft.ML" Version="1.6.0" />
    <PackageReference Include="Microsoft.ML.Vision" Version="1.6.0" />
    <PackageReference Include="Mime" Version="3.4.0" />
    <PackageReference Include="SciSharp.TensorFlow.Redist-Linux-GPU" Version="2.3.1" />
    <PackageReference Include="SciSharp.TensorFlow.Redist-Windows-GPU" Version="2.3.1" />
  </ItemGroup>

  <ItemGroup>
    <None Include="..\LICENSE">
      <Pack>True</Pack>
      <PackagePath></PackagePath>
    </None>
    <None Include="NsfwSpy-Icon.png">
      <Pack>True</Pack>
      <PackagePath></PackagePath>
    </None>
    <None Include="NsfwSpy-Icon.png">
      <Pack>True</Pack>
      <PackagePath></PackagePath>
    </None>
  </ItemGroup>

  <ItemGroup>
    <None Update="NsfwSpyModel.zip">
      <Pack>true</Pack>
      <CopyToOutputDirectory>Always</CopyToOutputDirectory>
      <PackageCopyToOutput>true</PackageCopyToOutput>
    </None>
  </ItemGroup>

</Project>


================================================
FILE: NsfwSpy/Resources/ClassificationFailedException.cs
================================================
using System;
using System.Collections.Generic;
using System.Text;

namespace NsfwSpyNS
{
    public class ClassificationFailedException : Exception
    {
        public ClassificationFailedException(string message)
            : base(message)
        {
        }
    }
}


================================================
FILE: NsfwSpy/Resources/EClassificationType.cs
================================================
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;

namespace NsfwSpyNS
{
    internal enum EClassificationType
    {
        Hentai = 0,
        Neutral = 1,
        Pornography = 2,
        Sexy = 3
    }
}


================================================
FILE: NsfwSpy/Resources/ModelInput.cs
================================================
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;

namespace NsfwSpyNS
{
    class ModelInput
    {
        public ModelInput(byte[] image)
        {
            Image = image;
        }

        public byte[] Image { get; set; }
    }
}


================================================
FILE: NsfwSpy/Resources/ModelOutput.cs
================================================
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;

namespace NsfwSpyNS
{
    class ModelOutput
    {
        public string PredictedLabel { get; set; }
        public float[] Score { get; set; }
    }
}


================================================
FILE: NsfwSpy/Resources/NsfwSpyFramesResult.cs
================================================
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;

namespace NsfwSpyNS
{
    /// <summary>
    /// The result from classifying a Gif file.
    /// </summary>
    public class NsfwSpyFramesResult
    {
        /// <summary>
        /// The NsfwSpyResults for each of the frames classified with the key being the frame index.
        /// </summary>
        public Dictionary<int, NsfwSpyResult> Frames { get; set; }

        /// <summary>
        /// The amount of frames classified.
        /// </summary>
        public int FrameCount => Frames.Count;

        /// <summary>
        /// True if any of the frames have been classified as NSFW.
        /// </summary>
        public bool IsNsfw => Frames.Any(f => f.Value.IsNsfw);

        public NsfwSpyFramesResult(Dictionary<int, NsfwSpyResult> frames)
        {
            Frames = frames;
        }
    }
}


================================================
FILE: NsfwSpy/Resources/NsfwSpyResult.cs
================================================
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;

namespace NsfwSpyNS
{
    /// <summary>
    /// The result from classifying an image.
    /// </summary>
    public class NsfwSpyResult
    {
        /// <summary>
        /// The hentai probability score between 0 and 1.
        /// </summary>
        public float Hentai { get; }

        /// <summary>
        /// The neutral probability score between 0 and 1.
        /// </summary>
        public float Neutral { get; }

        /// <summary>
        /// The pornography probability score between 0 and 1.
        /// </summary>
        public float Pornography { get; }

        /// <summary>
        /// The sexy probability score between 0 and 1.
        /// </summary>
        public float Sexy { get; }

        /// <summary>
        /// The most likely predicted value.
        /// </summary>
        public string PredictedLabel { get; }

        /// <summary>
        /// Whether the image is likely to be explicit. True if the sum of pornography, hentai and sexy is equal to or above 0.5.
        /// </summary>
        public bool IsNsfw => Neutral < 0.5;

        public NsfwSpyResult()
        {

        }

        internal NsfwSpyResult(ModelOutput modelOutput)
        {
            Hentai = modelOutput.Score[(int)EClassificationType.Hentai];
            Neutral = modelOutput.Score[(int)EClassificationType.Neutral];
            Pornography = modelOutput.Score[(int)EClassificationType.Pornography];
            Sexy = modelOutput.Score[(int)EClassificationType.Sexy];
            PredictedLabel = modelOutput.PredictedLabel;

            if (Hentai + Neutral + Pornography + Sexy == 0)
            {
                throw new ClassificationFailedException("Classification of the file failed. Make sure the file is a valid image format (jpg, png, gif etc) and has been loaded correctly.");
            }
        }

        /// <summary>
        /// Get the 5 classification types as a dictionary ordered by their score.
        /// </summary>
        /// <returns>Dictionary of the prediction scores.</returns>
        public Dictionary<string, float> ToDictionary()
        {
            var dictionary = new Dictionary<string, float>
            {
                { "Hentai", Hentai },
                { "Neutral", Neutral },
                { "Pornography", Pornography },
                { "Sexy", Sexy }
            };

            return dictionary.OrderByDescending(p => p.Value).ToDictionary(x => x.Key, x => x.Value); ;
        }
    }
}


================================================
FILE: NsfwSpy/Resources/NsfwSpyValue.cs
================================================
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;

namespace NsfwSpyNS
{
    public class NsfwSpyValue
    {
        public string FilePath { get; }
        public NsfwSpyResult Result { get; }

        public NsfwSpyValue(string filePath, NsfwSpyResult result)
        {
            FilePath = filePath;
            Result = result;
        }
    }
}


================================================
FILE: NsfwSpy/Resources/VideoOptions.cs
================================================
using System;
using System.Collections.Generic;
using System.Text;

namespace NsfwSpyNS
{
    /// <summary>
    /// Customise how the frames of a video file are classified.
    /// </summary>
    public class VideoOptions
    {
        /// <summary>
        /// Stop classifying frames if a NSFW frame is found.
        /// </summary>
        public bool EarlyStopOnNsfw { get; set; } = false;

        /// <summary>
        /// Improve performance by only classifying one in every Nth frames e.g. 1 = classify all frames, 2 = classify 1 in 2 frames.
        /// </summary>
        public int ClassifyEveryNthFrame { get; set; } = 1;
    }
}


================================================
FILE: NsfwSpy.App/Controllers/NsfwSpyController.cs
================================================
using HeyRed.Mime;
using Microsoft.AspNetCore.Mvc;
using System.Web;

namespace NsfwSpyNS.App.Controllers
{
    [ApiController]
    [Route("[controller]")]
    public class NsfwSpyController : ControllerBase
    {
        private INsfwSpy _nsfwSpy;

        public NsfwSpyController(INsfwSpy nsfwSpy)
        {
            _nsfwSpy = nsfwSpy;
        }

        [HttpGet("url/{url}")]
        public async Task<FileContentResult> GetUrlMediaAsync(string url)
        {
            url = HttpUtility.UrlDecode(url);
            var httpClient = new HttpClient();
            httpClient.DefaultRequestHeaders.Add("User-Agent", "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/101.0.4951.67 Safari/537.36");
            var byteArray = await httpClient.GetByteArrayAsync(url);
            var mimeType = MimeGuesser.GuessMimeType(byteArray);
            return new FileContentResult(byteArray, mimeType);
        }

        [HttpPost("image")]
        public ActionResult<NsfwSpyResult> ClassifyImage(IFormFile file)
        {
            var fileBytes = ConvertFormFileToByteArray(file);
            var result = _nsfwSpy.ClassifyImage(fileBytes);
            return Ok(result);
        }

        [HttpPost("gif")]
        public ActionResult<NsfwSpyFramesResult> ClassifyGif(IFormFile file)
        {
            var fileBytes = ConvertFormFileToByteArray(file);
            var videoOptions = new VideoOptions
            {
                EarlyStopOnNsfw = false
            };
            var result = _nsfwSpy.ClassifyGif(fileBytes, videoOptions);
            return Ok(result);
        }

        [HttpPost("video")]
        public ActionResult<NsfwSpyFramesResult> ClassifyVideo(IFormFile file)
        {
            var fileBytes = ConvertFormFileToByteArray(file);
            var videoOptions = new VideoOptions
            {
                EarlyStopOnNsfw = false
            };
            var result = _nsfwSpy.ClassifyVideo(fileBytes, videoOptions);
            return Ok(result);
        }

        private byte[] ConvertFormFileToByteArray(IFormFile file)
        {
            using (var ms = new MemoryStream())
            {
                file.CopyTo(ms);
                var fileBytes = ms.ToArray();
                return fileBytes;
            }
        }
    }

    public class MediaInfo
    {
        public IFormFile File { get; set; }
        public string MimeType { get; set; }
    }
}

================================================
FILE: NsfwSpy.App/NsfwSpy.App.csproj
================================================
<Project Sdk="Microsoft.NET.Sdk.Web">

  <PropertyGroup>
    <TargetFramework>net6.0</TargetFramework>
    <Nullable>enable</Nullable>
    <TypeScriptCompileBlocked>true</TypeScriptCompileBlocked>
    <TypeScriptToolsVersion>Latest</TypeScriptToolsVersion>
    <IsPackable>false</IsPackable>
    <SpaRoot>client-app\</SpaRoot>
    <DefaultItemExcludes>$(DefaultItemExcludes);$(SpaRoot)node_modules\**</DefaultItemExcludes>
    <SpaProxyServerUrl>https://localhost:3000</SpaProxyServerUrl>
    <SpaProxyLaunchCommand>npm start</SpaProxyLaunchCommand>
    <ImplicitUsings>enable</ImplicitUsings>
  </PropertyGroup>

  <ItemGroup>
    <PackageReference Include="Microsoft.AspNetCore.SpaProxy" Version="6.0.5" />
    <PackageReference Include="Microsoft.TypeScript.MSBuild" Version="4.7.2">
      <PrivateAssets>all</PrivateAssets>
      <IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
    </PackageReference>
    <PackageReference Include="Mime" Version="3.4.0" />
  </ItemGroup>

  <ItemGroup>
    <!-- Don't publish the SPA source files, but do show them in the project files list -->
    <Content Remove="$(SpaRoot)**" />
    <None Remove="$(SpaRoot)**" />
    <None Include="$(SpaRoot)**" Exclude="$(SpaRoot)node_modules\**" />
  </ItemGroup>

  <ItemGroup>
    <None Remove="client-app\src\aspnetcore-https.ts" />
    <None Remove="client-app\src\aspnetcore-react.ts" />
  </ItemGroup>

  <ItemGroup>
    <TypeScriptCompile Remove="client-app\src\functions\getContentType.ts" />
    <TypeScriptCompile Remove="client-app\src\functions\sortBy.ts" />
    <TypeScriptCompile Remove="client-app\src\models\MediaInfo.ts" />
  </ItemGroup>

  <ItemGroup>
    <ProjectReference Include="..\NsfwSpy\NsfwSpy.csproj" />
  </ItemGroup>

  <ItemGroup>
    <TypeScriptCompile Include="client-app\src\aspnetcore-https.ts" />
    <TypeScriptCompile Include="client-app\src\aspnetcore-react.ts" />
  </ItemGroup>

  <Target Name="DebugEnsureNodeEnv" BeforeTargets="Build" Condition=" '$(Configuration)' == 'Debug' And !Exists('$(SpaRoot)node_modules') ">
    <!-- Ensure Node.js is installed -->
    <Exec Command="node --version" ContinueOnError="true">
      <Output TaskParameter="ExitCode" PropertyName="ErrorCode" />
    </Exec>
    <Error Condition="'$(ErrorCode)' != '0'" Text="Node.js is required to build and run this project. To continue, please install Node.js from https://nodejs.org/, and then restart your command prompt or IDE." />
    <Message Importance="high" Text="Restoring dependencies using 'npm'. This may take several minutes..." />
    <Exec WorkingDirectory="$(SpaRoot)" Command="npm install" />
  </Target>

  <Target Name="PublishRunWebpack" AfterTargets="ComputeFilesToPublish">
    <!-- As part of publishing, ensure the JS resources are freshly built in production mode -->
    <Exec WorkingDirectory="$(SpaRoot)" Command="npm install" />
    <Exec WorkingDirectory="$(SpaRoot)" Command="npm run build" />

    <!-- Include the newly-built files in the publish output -->
    <ItemGroup>
      <DistFiles Include="$(SpaRoot)build\**" />
      <ResolvedFileToPublish Include="@(DistFiles->'%(FullPath)')" Exclude="@(ResolvedFileToPublish)">
        <RelativePath>wwwroot\%(RecursiveDir)%(FileName)%(Extension)</RelativePath>
        <CopyToPublishDirectory>PreserveNewest</CopyToPublishDirectory>
        <ExcludeFromSingleFile>true</ExcludeFromSingleFile>
      </ResolvedFileToPublish>
    </ItemGroup>
  </Target>
</Project>


================================================
FILE: NsfwSpy.App/Pages/Error.cshtml
================================================
@page
@model ErrorModel
@{
    ViewData["Title"] = "Error";
}

<h1 class="text-danger">Error.</h1>
<h2 class="text-danger">An error occurred while processing your request.</h2>

@if (Model.ShowRequestId)
{
    <p>
        <strong>Request ID:</strong> <code>@Model.RequestId</code>
    </p>
}

<h3>Development Mode</h3>
<p>
    Swapping to the <strong>Development</strong> environment displays detailed information about the error that occurred.
</p>
<p>
    <strong>The Development environment shouldn't be enabled for deployed applications.</strong>
    It can result in displaying sensitive information from exceptions to end users.
    For local debugging, enable the <strong>Development</strong> environment by setting the <strong>ASPNETCORE_ENVIRONMENT</strong> environment variable to <strong>Development</strong>
    and restarting the app.
</p>


================================================
FILE: NsfwSpy.App/Pages/Error.cshtml.cs
================================================
using Microsoft.AspNetCore.Mvc;
using Microsoft.AspNetCore.Mvc.RazorPages;
using System.Diagnostics;

namespace NsfwSpyNS.App.Pages
{
    [ResponseCache(Duration = 0, Location = ResponseCacheLocation.None, NoStore = true)]
    public class ErrorModel : PageModel
    {
        private readonly ILogger<ErrorModel> _logger;

        public ErrorModel(ILogger<ErrorModel> logger)
        {
            _logger = logger;
        }

        public string? RequestId { get; set; }

        public bool ShowRequestId => !string.IsNullOrEmpty(RequestId);

        public void OnGet()
        {
            RequestId = Activity.Current?.Id ?? HttpContext.TraceIdentifier;
        }
    }
}

================================================
FILE: NsfwSpy.App/Pages/_ViewImports.cshtml
================================================
@using NsfwSpyNS.App
@namespace NsfwSpyNS.App.Pages
@addTagHelper *, Microsoft.AspNetCore.Mvc.TagHelpers


================================================
FILE: NsfwSpy.App/Program.cs
================================================
using NsfwSpyNS;

var builder = WebApplication.CreateBuilder(args);

// Add services to the container.

builder.Services.AddControllersWithViews();
builder.Services.AddSingleton<INsfwSpy, NsfwSpy>();

var app = builder.Build();

// Configure the HTTP request pipeline.
if (!app.Environment.IsDevelopment())
{
    // The default HSTS value is 30 days. You may want to change this for production scenarios, see https://aka.ms/aspnetcore-hsts.
    app.UseHsts();
}

app.UseHttpsRedirection();
app.UseStaticFiles();
app.UseRouting();


app.MapControllerRoute(
    name: "default",
    pattern: "{controller}/{action=Index}/{id?}");

app.MapFallbackToFile("index.html"); ;

app.Run();


================================================
FILE: NsfwSpy.App/Properties/launchSettings.json
================================================
{
  "iisSettings": {
    "windowsAuthentication": false,
    "anonymousAuthentication": true,
    "iisExpress": {
      "applicationUrl": "http://localhost:57025",
      "sslPort": 44385
    }
  },
  "profiles": {
    "NsfwSpy.App": {
      "commandName": "Project",
      "launchBrowser": true,
      "applicationUrl": "https://localhost:7260;http://localhost:5260",
      "environmentVariables": {
        "ASPNETCORE_ENVIRONMENT": "Development",
        "ASPNETCORE_HOSTINGSTARTUPASSEMBLIES": "Microsoft.AspNetCore.SpaProxy"
      }
    },
    "IIS Express": {
      "commandName": "IISExpress",
      "launchBrowser": true,
      "environmentVariables": {
        "ASPNETCORE_ENVIRONMENT": "Development",
        "ASPNETCORE_HOSTINGSTARTUPASSEMBLIES": "Microsoft.AspNetCore.SpaProxy"
      }
    }
  }
}


================================================
FILE: NsfwSpy.App/README.md
================================================
# Getting Started
Looking for a quick way to try out NsfwSpy? Use our dedicated, self-hosted web app to classify images, gifs and videos with ease.

1. Check you have [NodeJS](https://nodejs.org/) installed by using the following command in the terminal:
  ```
  node -v
  ```
2. Clone the git repository to your local machine.
3. Open the NsfwSpy.sln solution in Visual Studio or your preferred IDE.
4. Run the NsfwSpy.App project using IIS Express:
<img src="https://raw.githubusercontent.com/NsfwSpy/NsfwSpy.NET/main/_art/NsfwSpy.App step 3.jpg" alt="NsfwSpy App config" />
5. Upload your images and videos or paste a link to have them classified. 

<img src="https://raw.githubusercontent.com/NsfwSpy/NsfwSpy.NET/main/_art/NsfwSpy.App.gif" alt="NsfwSpy App" width="400" />


================================================
FILE: NsfwSpy.App/appsettings.json
================================================
{
  "Logging": {
      "LogLevel": {
      "Default": "Information",
      "Microsoft": "Warning",
      "Microsoft.Hosting.Lifetime": "Information"
      }
    },
"AllowedHosts": "*"
}


================================================
FILE: NsfwSpy.App/client-app/.gitignore
================================================
.DS_STORE
node_modules
scripts/flow/*/.flowconfig
.flowconfig
*~
*.pyc
.grunt
_SpecRunner.html
__benchmarks__
build/
remote-repo/
coverage/
.module-cache
fixtures/dom/public/react-dom.js
fixtures/dom/public/react.js
test/the-files-to-test.generated.js
*.log*
chrome-user-data
*.sublime-project
*.sublime-workspace
.idea
*.iml
.vscode
*.swp
*.swo

packages/react-devtools-core/dist
packages/react-devtools-extensions/chrome/build
packages/react-devtools-extensions/chrome/*.crx
packages/react-devtools-extensions/chrome/*.pem
packages/react-devtools-extensions/firefox/build
packages/react-devtools-extensions/firefox/*.xpi
packages/react-devtools-extensions/firefox/*.pem
packages/react-devtools-extensions/shared/build
packages/react-devtools-extensions/.tempUserDataDir
packages/react-devtools-inline/dist
packages/react-devtools-shell/dist
packages/react-devtools-timeline/dist

================================================
FILE: NsfwSpy.App/client-app/package.json
================================================
{
  "name": "client-app",
  "version": "0.1.0",
  "private": true,
  "proxy": "https://localhost:44385",
  "type": "module",
  "dependencies": {
    "@fortawesome/fontawesome-svg-core": "^6.1.1",
    "@fortawesome/free-solid-svg-icons": "^6.1.1",
    "@fortawesome/react-fontawesome": "^0.1.18",
    "@testing-library/jest-dom": "^5.11.4",
    "@testing-library/react": "^11.1.0",
    "@testing-library/user-event": "^12.1.10",
    "@types/jest": "^26.0.15",
    "@types/react": "^17.0.0",
    "@types/react-dom": "^17.0.0",
    "node-sass": "^8.0.0",
    "react": "^17.0.2",
    "react-dom": "^17.0.2",
    "react-scripts": "^5.0.1",
    "recharts": "^2.2.0",
    "ts-node": "^10.4.0",
    "typescript": "^4.1.2",
    "web-vitals": "^1.0.1"
  },
  "scripts": {
    "prestart": "node --loader ts-node/esm ./src/aspnetcore-https.ts && node --loader ts-node/esm ./src/aspnetcore-react.ts",
    "start": "react-scripts start",
    "build": "react-scripts build",
    "test": "react-scripts test",
    "eject": "react-scripts eject"
  },
  "eslintConfig": {
    "extends": [
      "react-app",
      "react-app/jest"
    ]
  },
  "browserslist": {
    "production": [
      ">0.2%",
      "not dead",
      "not op_mini all"
    ],
    "development": [
      "last 1 chrome version",
      "last 1 firefox version",
      "last 1 safari version"
    ]
  },
  "devDependencies": {
    "@types/node": "^16.11.36"
  }
}


================================================
FILE: NsfwSpy.App/client-app/public/index.html
================================================
<!DOCTYPE html>
<html lang="en">

<head>
  <meta charset="utf-8" />
  <link rel="icon" href="%PUBLIC_URL%/favicon.ico" />
  <meta name="viewport" content="width=device-width, initial-scale=1" />
  <meta name="theme-color" content="#000000" />
  <meta name="description" content="NsfwSpy | Pornographic .NET image classifier" />
  <link rel="apple-touch-icon" href="%PUBLIC_URL%/logo192.png" />
  <!--
      manifest.json provides metadata used when your web app is installed on a
      user's mobile device or desktop. See https://developers.google.com/web/fundamentals/web-app-manifest/
    -->
  <link rel="manifest" href="%PUBLIC_URL%/manifest.json" />
  <!--
      Notice the use of %PUBLIC_URL% in the tags above.
      It will be replaced with the URL of the `public` folder during the build.
      Only files inside the `public` folder can be referenced from the HTML.

      Unlike "/favicon.ico" or "favicon.ico", "%PUBLIC_URL%/favicon.ico" will
      work correctly both with client-side routing and a non-root public URL.
      Learn how to configure a non-root public URL by running `npm run build`.
    -->
  <link rel="preconnect" href="https://fonts.googleapis.com">
  <link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
  <link href="https://fonts.googleapis.com/css2?family=Roboto:wght@900&display=swap" rel="stylesheet">
  <title>NsfwSpy | Pornographic .NET image classifier</title>
</head>

<body>
  <noscript>You need to enable JavaScript to run this app.</noscript>
  <div id="root"></div>
  <!--
      This HTML file is a template.
      If you open it directly in the browser, you will see an empty page.

      You can add webfonts, meta tags, or analytics to this file.
      The build step will place the bundled scripts into the <body> tag.

      To begin the development, run `npm start` or `yarn start`.
      To create a production bundle, use `npm run build` or `yarn build`.
    -->
</body>

</html>

================================================
FILE: NsfwSpy.App/client-app/public/manifest.json
================================================
{
  "short_name": "NsfwSpy App",
  "name": "NsfwSpy App",
  "icons": [
    {
      "src": "favicon.ico",
      "sizes": "64x64 32x32 24x24 16x16",
      "type": "image/x-icon"
    },
    {
      "src": "./assets/images/NsfwSpy-Icon.png",
      "type": "image/png",
      "sizes": "256x256"
    }
  ],
  "start_url": ".",
  "display": "standalone",
  "theme_color": "#000000",
  "background_color": "#ffffff"
}


================================================
FILE: NsfwSpy.App/client-app/public/robots.txt
================================================
# https://www.robotstxt.org/robotstxt.html
User-agent: *
Disallow:


================================================
FILE: NsfwSpy.App/client-app/src/App.scss
================================================
.app {
    color: #fff;
    font-family: Roboto, -apple-system, BlinkMacSystemFont, 'Segoe UI', Oxygen, Ubuntu, Cantarell, 'Open Sans', 'Helvetica Neue', sans-serif;
}

header {
    align-items: center;
    background-color: #000000;
    display: flex;
    height: 80px;
    justify-content: center;
}

main {
    background-color: #1b1b1b;
    height: calc(100vh - 80px);
    display: flex;
    flex: 1 1 0;
    flex-direction: column;
    align-items: center;
    justify-content: center;

    .image-section {
        flex-direction: column;
    }
    
    section {
        display: flex;
        flex: 1;
        flex-direction: column;
        align-items: center;
        max-width: 1000px;
        padding: 16px 0;
        width: calc(100% - 48px);
    }
}

.image-canvas {
    align-items: center;
    border: dashed #fff 6px;
    border-radius: 32px;
    cursor: pointer;
    display: flex;
    flex-direction: column;
    flex: 1 1 auto;
    font-size: 18px;
    justify-content: center;
    margin: 16px;
    padding: 16px;
    height: 30vh;

    .icons {
        display: flex;
        font-size: 56px;
        margin: 16px 0;

        div {
            margin: 16px 16px 0;
        }
    }

    .subtitle {
        font-size: 16px;
    }

    .image-preview,
    .video-preview {
        height: 100%;
        object-fit: contain;
        width: 100%;
    }
}

.result-value {
    display: flex;
    font-size: 18px;
    margin: 8px 0;
    text-transform: capitalize;
    width: 300px;

    &.hentai {
        color: #c25452;
    }

    &.neutral {
        color: #fff;
    }

    &.pornography {
        color: #ffa31a;
    }

    &.sexy {
        color: #fdfd66;
    }

    span {
        flex: 50%;
    }
}

input[type=text] {
    background: #292929;
    border: 1px solid #111;
    border-radius: 4px;
    box-shadow: inset 0 1px 2px #111;
    box-sizing: border-box;
    color: #fff;
    display: inline-block;
    font-family: Roboto, -apple-system, BlinkMacSystemFont, 'Segoe UI', Oxygen, Ubuntu, Cantarell, 'Open Sans', 'Helvetica Neue', sans-serif;
    margin: 8px 0;
    outline: none;
    padding: 12px 20px;
    width: 60%;
}

================================================
FILE: NsfwSpy.App/client-app/src/App.tsx
================================================
import React, { useEffect, useState } from 'react';
import { FontAwesomeIcon } from '@fortawesome/react-fontawesome';
import { faImage, faVideo } from '@fortawesome/free-solid-svg-icons'
import { Logo } from './components/Logo/Logo';
import { selectFiles } from './functions/selectFiles';
import { ImageFile } from './models/ImageFile';
import { getMediaInfo, uploadGif, uploadImage, uploadVideo } from './functions/client';
import { LineChart, Line, XAxis, YAxis, CartesianGrid, Tooltip, Legend, ResponsiveContainer } from 'recharts';
import './App.scss';
import { NsfwSpyFramesResult } from './models/NsfwSpyFramesResult';
import { NsfwSpyResult } from './models/NsfwSpyResult';
import { sortNsfwResult } from './functions/sortBy';
import { getContentType } from './functions/getContentType';
import { MediaInfo } from './models/MediaInfo';

export const App: React.FC = () => {
    const [url, setUrl] = useState<string>();
    const [image, setImage] = useState<ImageFile>();
    const [video, setVideo] = useState<ImageFile>();
    const [imageResults, setImageResults] = useState<NsfwSpyResult>();
    const [videoResults, setVideoResults] = useState<NsfwSpyFramesResult>();
    const [processing, setProcessing] = useState<boolean>(false);

    useEffect(() => {
        if (!url) return;

        const handleUrl = async () => {
            const result = await getMediaInfo(url);
            const data = await result.blob()
            handleFile(data);
        }

        handleUrl();
    }, [url])

    const selectFile = () => {
        selectFiles({ accept: 'image/*;video/*', multiple: false }).then(async files => {
            if (files) {
                handleFile(files[0])
            }
        });
    }

    const handleFile = async (file: Blob) => {
        const imageFile: ImageFile = {
            file: file,
            url: URL.createObjectURL(file)
        };

        setImage(undefined);
        setVideo(undefined);
        setImageResults(undefined);
        setVideoResults(undefined);

        const fileType = imageFile.file.type;

        setProcessing(true);
        if (fileType === "image/gif") {
            setImage(imageFile);
            const result = await uploadGif(imageFile.file);
            const data: NsfwSpyFramesResult = await result.json();
            setVideoResults(data);
        } else if (fileType.startsWith("image/")) {
            setImage(imageFile);
            const result = await uploadImage(imageFile.file);
            const data: NsfwSpyResult = await result.json();
            setImageResults(data);
        } else if (fileType.startsWith("video/")) {
            setVideo(imageFile);
            const result = await uploadVideo(imageFile.file);
            const data: NsfwSpyFramesResult = await result.json();
            setVideoResults(data);
        }
        setProcessing(false);
    }

    let sortedImageResults: [string, any][] | undefined = undefined;
    if (imageResults) {
        sortedImageResults = sortNsfwResult(imageResults);
    }

    return (
        <div className="app">
            <header>
                <Logo />
            </header>
            <main>
                <section className="image-section">
                    <div className="image-canvas" onClick={selectFile}>
                        {!image && !video &&
                            <>
                                <div>
                                    Select an image, Gif or video.
                                </div>
                                <div className="icons">
                                    <div><FontAwesomeIcon icon={faImage} /></div>
                                    <div><FontAwesomeIcon icon={faVideo} /></div>
                                </div>
                                <div className="subtitle">
                                    Or paste a link below...
                                </div>
                            </>}
                        {image &&
                            <img src={image.url} className="image-preview" />}
                        {video &&
                            <video
                                src={video.url}
                                autoPlay
                                loop
                                muted
                                className="video-preview" />}
                    </div>
                    <input
                        type="text"
                        placeholder="https://i3.ytimg.com/vi/dQw4w9WgXcQ/maxresdefault.jpg"
                        onChange={(e) => setUrl(e.target.value)} />
                </section>
                <section className="results-section">
                    {processing &&
                        <div>
                            Processing...
                        </div>}
                    {videoResults &&
                        <>
                            <ResponsiveContainer height="100%" width="100%">
                                <LineChart
                                    width={500}
                                    height={300}
                                    data={Object.values(videoResults.frames)}
                                    margin={{
                                        top: 5,
                                        right: 30,
                                        left: 20,
                                        bottom: 5,
                                    }}>
                                    <XAxis dataKey="name" />
                                    <YAxis />
                                    <Tooltip contentStyle={{ background: "#292929" }} />
                                    <Legend />
                                    <Line type="monotone" dataKey="hentai" stroke="#c25452" strokeWidth={3} dot={false} />
                                    <Line type="monotone" dataKey="neutral" stroke="#ffffff" strokeWidth={3} dot={false} />
                                    <Line type="monotone" dataKey="pornography" stroke="#ffa31a" strokeWidth={3} dot={false} />
                                    <Line type="monotone" dataKey="sexy" stroke="#fdfd66" strokeWidth={3} dot={false} />
                                </LineChart>
                            </ResponsiveContainer>
                            <span>{videoResults.frameCount} Frames Analysed</span>
                        </>}
                    {sortedImageResults &&
                        <div>
                            {sortedImageResults.map((result) =>
                                <div className={`result-value ${result[0]}`}>
                                    <span>{result[0]}</span>
                                    <span>{result[1]}</span>
                                </div>
                            )}
                        </div>}
                </section>
            </main >
        </div >
    );
}

export default App;


================================================
FILE: NsfwSpy.App/client-app/src/aspnetcore-https.ts
================================================
import * as fs from 'fs'
import * as path from 'path'
import * as child_process from 'child_process'

const spawn = child_process.spawn;

const baseFolder = process.env.APPDATA !== undefined && process.env.APPDATA !== ''
    ? `${process.env.APPDATA}/ASP.NET/https`
    : `${process.env.HOME}/.aspnet/https`;

const certArg = process.argv.map(arg => arg.match('/--name=(?<value>.+)/i')).filter(Boolean)[0];
const certName = certArg ? certArg?.groups?.value : process.env.npm_package_name;

if (!certName) {
    console.error('Invalid certificate name. Run this script in the context of an npm/yarn script or pass --name=<<app>> explicitly');
    process.exit(-1);
}

const moduleCertFilePath = path.join(baseFolder, `${certName}.pem`);
const moduleKeyFilePath = path.join(baseFolder, `${certName}.key`);

if (!fs.existsSync(moduleCertFilePath) || !fs.existsSync(moduleKeyFilePath)) {
    spawn('dotnet', [
        'dev-certs',
        'https',
        '--export-path',
        moduleCertFilePath,
        '--format',
        'Pem',
        '--no-password',
    ], { stdio: 'inherit', })
        .on('exit', (code: any) => process.exit(code));
}

================================================
FILE: NsfwSpy.App/client-app/src/aspnetcore-react.ts
================================================
import * as fs from 'fs'
import * as path from 'path'

const baseFolder = process.env.APPDATA !== undefined && process.env.APPDATA !== ''
    ? `${process.env.APPDATA}/ASP.NET/https`
    : `${process.env.HOME}/.aspnet/https`;

const certArg = process.argv.map(arg => arg.match('/--name=(?<value>.+)/i')).filter(Boolean)[0];
const certName = certArg ? certArg?.groups?.value : process?.env?.npm_package_name;

if (!certName) {
    console.error('Invalid certificate name. Run this script in the context of an npm/yarn script or pass --name=<<app>> explicitly');
    process.exit(-1);
}

const certFilePath = path.join(baseFolder, `${certName}.pem`);
const keyFilePath = path.join(baseFolder, `${certName}.key`);

if (!fs.existsSync('.env.development.local')) {
    fs.writeFileSync(
        '.env.development.local',
        `BROWSER=none
        HTTPS=true
        SSL_CRT_FILE=${certFilePath}
        SSL_KEY_FILE=${keyFilePath}`,
    );
} else {
    let lines = fs.readFileSync('.env.development.local')
        .toString()
        .split('\n');

    let hasCert, hasCertKey = false;
    for (const line of lines) {
        if (/SSL_CRT_FILE=.*/i.test(line)) {
            hasCert = true;
        }
        if (/SSL_KEY_FILE=*/i.test(line)) {
            hasCertKey = true;
        }
    }

    if (!hasCert) {
        fs.appendFileSync(
            '.env.development.local',
            `\nSSL_CRT_FILE=${certFilePath}`
        );
    }
    if (!hasCertKey) {
        fs.appendFileSync(
            '.env.development.local',
            `\nSSL_KEY_FILE=${keyFilePath}`
        )
    }
}

================================================
FILE: NsfwSpy.App/client-app/src/components/Logo/Logo.scss
================================================
.logo {
    font-family: 'Roboto';
    font-size: 56px;
    margin: 16px;
    user-select: none;

    .white {
        color: #fff;
    }

    .orange {
        color: #ffa31a;
    }
}

================================================
FILE: NsfwSpy.App/client-app/src/components/Logo/Logo.tsx
================================================
import './Logo.scss';

export const Logo = () => {
    return (
        <span className="logo">
            <span className="white">Nsfw</span>
            <span className="orange">Spy</span>
        </span>
    )
}

================================================
FILE: NsfwSpy.App/client-app/src/functions/client.ts
================================================
export const uploadGif = (file: Blob) => {
    return uploadFile("/nsfwspy/gif", file);
}

export const uploadImage = (file: Blob) => {
    return uploadFile("/nsfwspy/image", file);
}

export const uploadVideo = (file: Blob) => {
    return uploadFile("/nsfwspy/video", file);
}

export const getMediaInfo = (url: string) => {
    return fetch(`/nsfwspy/url/${encodeURIComponent(url)}`);
}

const uploadFile = (url: string, file: Blob) => {
    var postSettings: RequestInit = {
        method: 'POST',
        mode: 'cors'
    };
    var data = new FormData();
    data.append('file', file);
    postSettings.body = data;

    return fetch(url, postSettings);
}

================================================
FILE: NsfwSpy.App/client-app/src/functions/getContentType.ts
================================================
export const getContentType = (url: string) => {
    return new Promise((resolve, reject) => {
        var req = new XMLHttpRequest();
        req.open("GET", url, true);
        req.setRequestHeader("Range", "bytes=0");
        req.onreadystatechange = () => {
            if (req.readyState === req.DONE) {
                resolve(req.getResponseHeader("Content-Type"));
            }
        };
        req.send();
    });
}

================================================
FILE: NsfwSpy.App/client-app/src/functions/selectFiles.ts
================================================
/**
 * Custom type for file input element (`<input type="file" />`).
 */
type InputFile = HTMLInputElement & {
    capture?: boolean | string;
};

/**
 * Type of options for file input element (`<input type="file" />`) virtually
 * created to select files.
 */
export type Options = {
    /**
     * Defines accepted file types. It's a comma-separated list of file
     * extensions, mime-types or unique file type specifiers.
     *
     * https://developer.mozilla.org/docs/Web/HTML/Element/input/file#Unique_file_type_specifiers
     *
     * @example ```js
     * "image/*,video/*,.pdf,.doc,.docx,.xls"
     * ```
     */
    accept?: string;

    /**
     * Combined with `accept` property it specifies which camera to use for
     * capture of image or video. It was previously a Boolean value.
     */
    capture?: string | null;

    /**
     * Allow multiple files selection.
     */
    multiple?: boolean;
};

/**
 * Creates a virtual file input element (`<input type="file" />`) with options.
 * @param options
 */
const createInputFile = ({
    accept = '',
    capture = null,
    multiple = false,
}: Options = {}): InputFile => {
    const input = document.createElement('input') as InputFile;

    input.type = 'file';
    input.accept = accept;
    if (capture !== null)
        input.capture = capture;
    input.multiple = multiple;

    return input;
};

/**
 * Virtually creates a file input element (`<input type="file" />`), triggers it
 * and returns selected files.
 *
 * @example
 * selectFiles({ accept: 'image/*', multiple: true }).then(files => {
 *   // ...
 * });
 *
 * @param options
 */
export const selectFiles = (options?: Options) =>
    new Promise<null | FileList>((resolve) => {
        const input = createInputFile(options);

        input.addEventListener('change', () => resolve(input.files || null));

        setTimeout(() => {
            const event = new MouseEvent('click');
            input.dispatchEvent(event);
        }, 0);
    });


================================================
FILE: NsfwSpy.App/client-app/src/functions/sortBy.ts
================================================
import { NsfwSpyResult } from '../models/NsfwSpyResult';

export const sortNsfwResult = (result: NsfwSpyResult) => {
    const validKeys = ['hentai', 'neutral', 'pornography', 'sexy'];
    const sortableArray = Object.entries(result);
    let sortedArray = sortableArray.sort(([, a], [, b]) => b - a);
    sortedArray = sortableArray.filter((i) => validKeys.includes(i[0]));
    return sortedArray;
}

================================================
FILE: NsfwSpy.App/client-app/src/index.scss
================================================
body {
  margin: 0;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}

================================================
FILE: NsfwSpy.App/client-app/src/index.tsx
================================================
import React from 'react';
import ReactDOM from 'react-dom';
import './index.scss';
import App from './App';
import reportWebVitals from './reportWebVitals';

ReactDOM.render(
  <React.StrictMode>
    <App />
  </React.StrictMode>,
  document.getElementById('root')
);

// If you want to start measuring performance in your app, pass a function
// to log results (for example: reportWebVitals(console.log))
// or send to an analytics endpoint. Learn more: https://bit.ly/CRA-vitals
reportWebVitals();


================================================
FILE: NsfwSpy.App/client-app/src/models/ImageFile.ts
================================================
export interface ImageFile {
    file: Blob
    url: string
}

================================================
FILE: NsfwSpy.App/client-app/src/models/MediaInfo.ts
================================================
export interface MediaInfo {
    file: Blob
    mimeType: string
}

================================================
FILE: NsfwSpy.App/client-app/src/models/NsfwSpyFramesResult.ts
================================================
import { NsfwSpyResult } from "./NsfwSpyResult"

export interface NsfwSpyFramesResult {
    frames: { [frame: number]: NsfwSpyResult }
    frameCount: number
    isNsfw: boolean
}

================================================
FILE: NsfwSpy.App/client-app/src/models/NsfwSpyResult.ts
================================================
export interface NsfwSpyResult {
    hentai: number
    neutral: number
    pornography: number
    sexy: number
    predictedLabel: string
    isNsfw: boolean
}

================================================
FILE: NsfwSpy.App/client-app/src/react-app-env.d.ts
================================================
/// <reference types="react-scripts" />


================================================
FILE: NsfwSpy.App/client-app/src/reportWebVitals.ts
================================================
import { ReportHandler } from 'web-vitals';

const reportWebVitals = (onPerfEntry?: ReportHandler) => {
  if (onPerfEntry && onPerfEntry instanceof Function) {
    import('web-vitals').then(({ getCLS, getFID, getFCP, getLCP, getTTFB }) => {
      getCLS(onPerfEntry);
      getFID(onPerfEntry);
      getFCP(onPerfEntry);
      getLCP(onPerfEntry);
      getTTFB(onPerfEntry);
    });
  }
};

export default reportWebVitals;


================================================
FILE: NsfwSpy.App/client-app/tsconfig.json
================================================
{
  "compilerOptions": {
    "target": "ES6",
    "lib": [
      "dom",
      "dom.iterable",
      "esnext"
    ],
    "allowJs": true,
    "skipLibCheck": true,
    "esModuleInterop": true,
    "allowSyntheticDefaultImports": true,
    "strict": true,
    "forceConsistentCasingInFileNames": true,
    "noFallthroughCasesInSwitch": true,
    "module": "ESNext",
    "moduleResolution": "Node",
    "resolveJsonModule": true,
    "isolatedModules": true,
    "noEmit": true,
    "jsx": "react-jsx"
  },
  "include": [
    "src"
  ]
}


================================================
FILE: NsfwSpy.PerformanceTesting/NsfwSpy.PerformanceTesting.csproj
================================================
<Project Sdk="Microsoft.NET.Sdk">

  <PropertyGroup>
    <OutputType>Exe</OutputType>
    <TargetFramework>net6.0</TargetFramework>
  </PropertyGroup>

  <ItemGroup>
    <ProjectReference Include="..\NsfwSpy\NsfwSpy.csproj" />
  </ItemGroup>

</Project>


================================================
FILE: NsfwSpy.PerformanceTesting/PerformanceResult.cs
================================================
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;

namespace NsfwSpyNS.PerformanceTesting
{
    class PerformanceResult
    {
        public string Key { get; set; }
        public List<NsfwSpyResult> Results { get; set; }
        public int CorrectAsserts => Results.Count(r => r.PredictedLabel == Key);
        public int NsfwAsserts => Results.Count(r => r.IsNsfw);
        public int HentaiAsserts => Results.Count(r => r.PredictedLabel == "Hentai");
        public int NeutralAsserts => Results.Count(r => r.PredictedLabel == "Neutral");
        public int PornographyAsserts => Results.Count(r => r.PredictedLabel == "Pornography");
        public int SexyAsserts => Results.Count(r => r.PredictedLabel == "Sexy");
        public int TotalAsserts => Results.Count();

        public PerformanceResult(string key)
        {
            Key = key;
            Results = new List<NsfwSpyResult>();
        }
    }
}


================================================
FILE: NsfwSpy.PerformanceTesting/Program.cs
================================================
using System;
using System.Collections.Generic;
using System.IO;
using System.Linq;
using System.Threading.Tasks;

namespace NsfwSpyNS.PerformanceTesting
{
    class Program
    {
        static void Main(string[] args)
        {
            var assetsPath = @"E:\NsfwSpy\Images";
            var testImagesPath = @"E:\NsfwSpy\Test";

            var classificationTypes = new[]
            {
                "Hentai",
                "Neutral",
                "Pornography",
                "Sexy",
            };

            var results = new List<PerformanceResult>();
            var nsfwSpy = new NsfwSpy();

            foreach (var classificationType in classificationTypes)
            {
                var testFilesDirectory = Path.Combine(testImagesPath, classificationType);
                var testFiles = Directory.Exists(testFilesDirectory) ? Directory.GetFiles(testFilesDirectory).ToList() : new List<string>();

                if (!testFiles.Any())
                {
                    var directory = Path.Combine(assetsPath, classificationType);
                    var files = Directory.GetFiles(directory).OrderBy(f => Guid.NewGuid()).ToList();

                    var length = files.Count > 10000 ? 10000 : files.Count;
                    files = files.Take(length).ToList();

                    Console.WriteLine($"Copying {classificationType} test files...");

                    if (!Directory.Exists(testFilesDirectory))
                        Directory.CreateDirectory(testFilesDirectory);

                    Parallel.ForEach(files, file => {
                        var filename = Path.GetFileName(file);
                        var dest = Path.Combine(testFilesDirectory, filename);
                        File.Copy(file, dest);
                    });

                    testFiles = Directory.GetFiles(testFilesDirectory).ToList();
                }

                var pr = new PerformanceResult(classificationType);

                nsfwSpy.ClassifyImages(testFiles, (filePath, result) =>
                {
                    pr.Results.Add(result);
                    Console.WriteLine($"{pr.Key} | Correct Asserts: {pr.CorrectAsserts} / {pr.TotalAsserts} ({(Convert.ToDouble(pr.CorrectAsserts) / pr.TotalAsserts) * 100}%) | IsNsfw: {pr.NsfwAsserts} / {pr.TotalAsserts} ({(Convert.ToDouble(pr.NsfwAsserts) / pr.TotalAsserts) * 100}%)");
                });

                results.Add(pr);
            }

            Console.WriteLine(Environment.NewLine);
            foreach (var pr in results)
            {
                Console.WriteLine($"{pr.Key} | Correct Asserts: {pr.CorrectAsserts} / {pr.TotalAsserts} ({(Convert.ToDouble(pr.CorrectAsserts) / pr.TotalAsserts) * 100}%) | IsNsfw: {pr.NsfwAsserts} / {pr.TotalAsserts} ({(Convert.ToDouble(pr.NsfwAsserts) / pr.TotalAsserts) * 100}%)");
            }

            Console.WriteLine(Environment.NewLine);
            Console.WriteLine("Confusion Matrix\n");

            Console.WriteLine("\t\t\tPredicted Label");
            Console.WriteLine("Actual Label\t\tHentai\t\tNeutral\t\tPornography\tSexy");
            Console.WriteLine();
            foreach (var pr in results)
            {
                Console.WriteLine($"{pr.Key}\t\t{(pr.Key != "Pornography" ? "\t" : "")}{pr.HentaiAsserts}\t\t{pr.NeutralAsserts}\t\t{pr.PornographyAsserts}\t\t{pr.SexyAsserts}");
            }

            Console.WriteLine(Environment.NewLine);
            Console.WriteLine("Average Confidence\n");

            foreach (var pr in results)
            {
                Console.WriteLine($"{pr.Key}\t\t{(pr.Key != "Pornography" ? "\t" : "")}{pr.Results.Sum(r => r.ToDictionary()[pr.Key]) / pr.Results.Count}");
            }
        }
    }
}


================================================
FILE: NsfwSpy.Test/NsfwSpy.Test.csproj
================================================
<Project Sdk="Microsoft.NET.Sdk">

  <PropertyGroup>
    <TargetFramework>net6.0</TargetFramework>

    <IsPackable>false</IsPackable>
  </PropertyGroup>

  <ItemGroup>
    <PackageReference Include="Microsoft.NET.Test.Sdk" Version="17.2.0" />
    <PackageReference Include="xunit" Version="2.4.1" />
    <PackageReference Include="xunit.runner.visualstudio" Version="2.4.5">
      <IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
      <PrivateAssets>all</PrivateAssets>
    </PackageReference>
    <PackageReference Include="coverlet.collector" Version="3.1.2">
      <IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
      <PrivateAssets>all</PrivateAssets>
    </PackageReference>
  </ItemGroup>

  <ItemGroup>
    <ProjectReference Include="..\NsfwSpy\NsfwSpy.csproj" />
  </ItemGroup>

  <ItemGroup>
    <Folder Include="Assets\" />
  </ItemGroup>

  <ItemGroup>
    <None Update="Assets\bikini.avi">
      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
    </None>
    <None Update="Assets\bikini.gif">
      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
    </None>
    <None Update="Assets\bikini.mkv">
      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
    </None>
    <None Update="Assets\bikini.mp4">
      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
    </None>
    <None Update="Assets\bikini.webm">
      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
    </None>
    <None Update="Assets\cool.gif">
      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
    </None>
    <None Update="Assets\flower.jpg">
      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
    </None>
    <None Update="Assets\flower.png">
      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
    </None>
    <None Update="Assets\flower.webp">
      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
    </None>
  </ItemGroup>

</Project>


================================================
FILE: NsfwSpy.Test/UnitTests.cs
================================================
using System;
using System.IO;
using System.Linq;
using System.Net;
using System.Threading.Tasks;
using Xunit;

namespace NsfwSpyNS.Test
{
    public class UnitTests
    {
        [Theory]
        [InlineData("flower.jpg")]
        [InlineData("flower.png")]
        [InlineData("flower.webp")]
        public void ClassifyImageByteArray_ValidByteArray(string filename)
        {
            var filePath = Path.Combine(AppContext.BaseDirectory, $@"Assets/{filename}");
            var imageBytes = File.ReadAllBytes(filePath);

            var nsfwSpy = new NsfwSpy();
            var result = nsfwSpy.ClassifyImage(imageBytes);

            Assert.Equal("Neutral", result.PredictedLabel);
        }

        [Fact]
        public void ClassifyImageByteArray_InvalidByteArray()
        {
            var nsfwSpy = new NsfwSpy();
            Assert.Throws<ClassificationFailedException>(() => nsfwSpy.ClassifyImage(new byte[0]));
        }

        [Theory]
        [InlineData("https://raw.githubusercontent.com/d00ML0rDz/NsfwSpy/main/NsfwSpy.Test/Assets/flower.jpg")]
        [InlineData("https://raw.githubusercontent.com/d00ML0rDz/NsfwSpy/main/NsfwSpy.Test/Assets/flower.png")]
        [InlineData("https://raw.githubusercontent.com/d00ML0rDz/NsfwSpy/main/NsfwSpy.Test/Assets/flower.webp")]
        public void ClassifyImageUri_ValidUri(string url)
        {
            var uri = new Uri(url);

            var nsfwSpy = new NsfwSpy();
            var result = nsfwSpy.ClassifyImage(uri);

            Assert.Equal("Neutral", result.PredictedLabel);
        }

        [Theory]
        [InlineData("https://raw.githubusercontent.com/d00ML0rDz/NsfwSpy/main/NsfwSpy.Test/Assets/flower.jpg")]
        [InlineData("https://raw.githubusercontent.com/d00ML0rDz/NsfwSpy/main/NsfwSpy.Test/Assets/flower.png")]
        [InlineData("https://raw.githubusercontent.com/d00ML0rDz/NsfwSpy/main/NsfwSpy.Test/Assets/flower.webp")]
        public void ClassifyImageUri_CustomWebClient(string url)
        {
            var uri = new Uri(url);
            var webClient = new WebClient();
            webClient.Headers["User-Agent"] = "test";

            var nsfwSpy = new NsfwSpy();
            var result = nsfwSpy.ClassifyImage(uri, webClient);

            Assert.Equal("Neutral", result.PredictedLabel);
        }

        [Theory]
        [InlineData("flower.jpg")]
        [InlineData("flower.png")]
        [InlineData("flower.webp")]
        public void ClassifyImageFilePath_ValidFilePath(string filename)
        {
            var filePath = Path.Combine(AppContext.BaseDirectory, $@"Assets/{filename}");

            var nsfwSpy = new NsfwSpy();
            var result = nsfwSpy.ClassifyImage(filePath);

            Assert.Equal("Neutral", result.PredictedLabel);
        }

        [Fact]
        public void ClassifyImageFilePath_InvalidFilePath()
        {
            var filePath = Path.Combine(AppContext.BaseDirectory, @"Assets/filedoesnotexist.jpg");

            var nsfwSpy = new NsfwSpy();
            Assert.Throws<FileNotFoundException>(() => nsfwSpy.ClassifyImage(filePath));
        }

        [Theory]
        [InlineData("https://raw.githubusercontent.com/d00ML0rDz/NsfwSpy/main/NsfwSpy.Test/Assets/flower.jpg")]
        [InlineData("https://raw.githubusercontent.com/d00ML0rDz/NsfwSpy/main/NsfwSpy.Test/Assets/flower.png")]
        [InlineData("https://raw.githubusercontent.com/d00ML0rDz/NsfwSpy/main/NsfwSpy.Test/Assets/flower.webp")]
        public async Task ClassifyImageUriAsync_ValidUri(string url)
        {
            var uri = new Uri(url);

            var nsfwSpy = new NsfwSpy();
            var result = await nsfwSpy.ClassifyImageAsync(uri);

            Assert.Equal("Neutral", result.PredictedLabel);
        }

        [Theory]
        [InlineData("https://raw.githubusercontent.com/d00ML0rDz/NsfwSpy/main/NsfwSpy.Test/Assets/flower.jpg")]
        [InlineData("https://raw.githubusercontent.com/d00ML0rDz/NsfwSpy/main/NsfwSpy.Test/Assets/flower.png")]
        [InlineData("https://raw.githubusercontent.com/d00ML0rDz/NsfwSpy/main/NsfwSpy.Test/Assets/flower.webp")]
        public async Task ClassifyImageUriAsync_CustomWebClient(string url)
        {
            var uri = new Uri(url);
            var webClient = new WebClient();
            webClient.Headers["User-Agent"] = "test";

            var nsfwSpy = new NsfwSpy();
            var result = await nsfwSpy.ClassifyImageAsync(uri, webClient);

            Assert.Equal("Neutral", result.PredictedLabel);
        }

        [Theory]
        [InlineData("flower.jpg")]
        [InlineData("flower.png")]
        [InlineData("flower.webp")]
        public async Task ClassifyImageFilePathAsync_ValidFilePath(string filename)
        {
            var filePath = Path.Combine(AppContext.BaseDirectory, $@"Assets/{filename}");

            var nsfwSpy = new NsfwSpy();
            var result = await nsfwSpy.ClassifyImageAsync(filePath);

            Assert.Equal("Neutral", result.PredictedLabel);
        }

        [Fact]
        public void ClassifyGifByteArray_ValidByteArray()
        {
            var filePath = Path.Combine(AppContext.BaseDirectory, @"Assets/cool.gif");
            var imageBytes = File.ReadAllBytes(filePath);

            var nsfwSpy = new NsfwSpy();
            var result = nsfwSpy.ClassifyGif(imageBytes);

            Assert.Equal(10, result.Frames.Count);
            Assert.False(result.IsNsfw);
        }

        [Fact]
        public void ClassifyGifFilePath_ValidFilePath()
        {
            var filePath = Path.Combine(AppContext.BaseDirectory, @"Assets/cool.gif");

            var nsfwSpy = new NsfwSpy();
            var result = nsfwSpy.ClassifyGif(filePath);

            Assert.Equal(10, result.Frames.Count);
            Assert.False(result.IsNsfw);
        }

        [Fact]
        public void ClassifyGifFilePath_ClassifyEvery2ndFrame()
        {
            var filePath = Path.Combine(AppContext.BaseDirectory, @"Assets/cool.gif");
            var videoOptions = new VideoOptions
            {
                ClassifyEveryNthFrame = 2
            };

            var nsfwSpy = new NsfwSpy();
            var result = nsfwSpy.ClassifyGif(filePath, videoOptions);

            Assert.Equal(5, result.Frames.Count);
            Assert.False(result.IsNsfw);
        }

        [Fact]
        public void ClassifyGifFilePath_EndEarlyOnNsfw()
        {
            var filePath = Path.Combine(AppContext.BaseDirectory, @"Assets/bikini.gif");
            var videoOptions = new VideoOptions
            {
                EarlyStopOnNsfw = true
            };

            var nsfwSpy = new NsfwSpy();
            var result = nsfwSpy.ClassifyGif(filePath, videoOptions: videoOptions);

            Assert.True(result.IsNsfw);
            Assert.True(result.Frames.Count < 181); // This Gif has 181 frames
        }

        [Fact]
        public void ClassifyGifUri_ValidUri()
        {
            var uri = new Uri("https://media2.giphy.com/media/62PP2yEIAZF6g/giphy.gif");

            var nsfwSpy = new NsfwSpy();
            var result = nsfwSpy.ClassifyGif(uri);

            Assert.Equal(10, result.Frames.Count);
            Assert.False(result.IsNsfw);
        }

        [Fact]
        public void ClassifyGifUri_ClassifyEvery2ndFrame()
        {
            var uri = new Uri("https://media2.giphy.com/media/62PP2yEIAZF6g/giphy.gif");
            var videoOptions = new VideoOptions
            {
                ClassifyEveryNthFrame = 2
            };

            var nsfwSpy = new NsfwSpy();
            var result = nsfwSpy.ClassifyGif(uri, videoOptions: videoOptions);

            Assert.Equal(5, result.Frames.Count);
            Assert.False(result.IsNsfw);
        }

        [Fact]
        public void ClassifyGifUri_EndEarlyOnNsfw()
        {
            var uri = new Uri("https://c.tenor.com/5y-jOowm51MAAAAd/bikini.gif");
            var videoOptions = new VideoOptions
            {
                EarlyStopOnNsfw = true
            };

            var nsfwSpy = new NsfwSpy();
            var result = nsfwSpy.ClassifyGif(uri, videoOptions: videoOptions);

            Assert.True(result.IsNsfw);
            Assert.True(result.Frames.Count < 181); // This Gif has 181 frames
        }

        [Fact]
        public async Task ClassifyGifFilePathAsync_ValidFilePath()
        {
            var filePath = Path.Combine(AppContext.BaseDirectory, @"Assets/cool.gif");

            var nsfwSpy = new NsfwSpy();
            var result = await nsfwSpy.ClassifyGifAsync(filePath);

            Assert.Equal(10, result.Frames.Count);
            Assert.False(result.IsNsfw);
        }

        [Fact]
        public async Task ClassifyGifUriAsync_ValidUri()
        {
            var uri = new Uri("https://media2.giphy.com/media/62PP2yEIAZF6g/giphy.gif");

            var nsfwSpy = new NsfwSpy();
            var result = await nsfwSpy.ClassifyGifAsync(uri);

            Assert.Equal(10, result.Frames.Count);
            Assert.False(result.IsNsfw);
        }

        [Theory]
        [InlineData("bikini.avi")]
        [InlineData("bikini.mkv")]
        [InlineData("bikini.mp4")]
        [InlineData("bikini.webm")]
        public void ClassifyVideoByteArray_ValidByteArray(string filename)
        {
            var filePath = Path.Combine(AppContext.BaseDirectory, $@"Assets\{filename}");
            var imageBytes = File.ReadAllBytes(filePath);

            var nsfwSpy = new NsfwSpy();
            var result = nsfwSpy.ClassifyVideo(imageBytes);

            if (filename.EndsWith(".webm"))
                Assert.Equal(180, result.Frames.Count);
            else
                Assert.Equal(181, result.Frames.Count);

            Assert.True(result.IsNsfw);
        }

        [Theory]
        [InlineData("bikini.avi")]
        [InlineData("bikini.mkv")]
        [InlineData("bikini.mp4")]
        [InlineData("bikini.webm")]
        public void ClassifyVideoFilePath_ValidFilePath(string filename)
        {
            var filePath = Path.Combine(AppContext.BaseDirectory, $@"Assets\{filename}");

            var nsfwSpy = new NsfwSpy();
            var result = nsfwSpy.ClassifyVideo(filePath);

            if (filename.EndsWith(".webm"))
                Assert.Equal(180, result.Frames.Count);
            else
                Assert.Equal(181, result.Frames.Count);

            Assert.True(result.IsNsfw);
        }

        [Theory]
        [InlineData("bikini.avi")]
        [InlineData("bikini.mkv")]
        [InlineData("bikini.mp4")]
        [InlineData("bikini.webm")]
        public void ClassifyVideoFilePath_ClassifyEvery2ndFrame(string filename)
        {
            var filePath = Path.Combine(AppContext.BaseDirectory, $@"Assets\{filename}");
            var videoOptions = new VideoOptions
            {
                ClassifyEveryNthFrame = 2
            };

            var nsfwSpy = new NsfwSpy();
            var result = nsfwSpy.ClassifyVideo(filePath, videoOptions);

            if (filename.EndsWith(".webm"))
                Assert.Equal(90, result.Frames.Count);
            else
                Assert.Equal(91, result.Frames.Count);

            Assert.True(result.IsNsfw);
        }

        [Theory]
        [InlineData("bikini.avi")]
        [InlineData("bikini.mkv")]
        [InlineData("bikini.mp4")]
        [InlineData("bikini.webm")]
        public void ClassifyVideoFilePath_EndEarlyOnNsfw(string filename)
        {
            var filePath = Path.Combine(AppContext.BaseDirectory, $@"Assets\{filename}");
            var videoOptions = new VideoOptions
            {
                EarlyStopOnNsfw = true
            };

            var nsfwSpy = new NsfwSpy();
            var result = nsfwSpy.ClassifyVideo(filePath, videoOptions: videoOptions);

            Assert.True(result.IsNsfw);
            Assert.True(result.Frames.Count < 181); // This video has 181 frames
        }

        [Fact]
        public void ClassifyVideoUri_ValidUri()
        {
            var uri = new Uri("https://i.imgur.com/MjTH5ZS.mp4");

            var nsfwSpy = new NsfwSpy();
            var result = nsfwSpy.ClassifyVideo(uri);

            Assert.Equal(120, result.Frames.Count);
            Assert.True(result.IsNsfw);
        }

        [Fact]
        public void ClassifyVideoUri_ClassifyEvery2ndFrame()
        {
            var uri = new Uri("https://i.imgur.com/MjTH5ZS.mp4");
            var videoOptions = new VideoOptions
            {
                ClassifyEveryNthFrame = 2
            };

            var nsfwSpy = new NsfwSpy();
            var result = nsfwSpy.ClassifyVideo(uri, videoOptions: videoOptions);

            Assert.Equal(60, result.Frames.Count);
            Assert.True(result.IsNsfw);
        }

        [Fact]
        public void ClassifyVideoUri_EndEarlyOnNsfw()
        {
            var uri = new Uri("https://i.imgur.com/MjTH5ZS.mp4");
            var videoOptions = new VideoOptions
            {
                EarlyStopOnNsfw = true
            };

            var nsfwSpy = new NsfwSpy();
            var result = nsfwSpy.ClassifyVideo(uri, videoOptions: videoOptions);

            Assert.True(result.IsNsfw);
            Assert.True(result.Frames.Count < 120); // This video has 120 frames
        }

        [Theory]
        [InlineData("bikini.avi")]
        [InlineData("bikini.mkv")]
        [InlineData("bikini.mp4")]
        [InlineData("bikini.webm")]
        public async Task ClassifyVideoFilePathAsync_ValidFilePath(string filename)
        {
            var filePath = Path.Combine(AppContext.BaseDirectory, $@"Assets\{filename}");

            var nsfwSpy = new NsfwSpy();
            var result = await nsfwSpy.ClassifyVideoAsync(filePath);

            if (filename.EndsWith(".webm"))
                Assert.Equal(180, result.Frames.Count);
            else
                Assert.Equal(181, result.Frames.Count);

            Assert.True(result.IsNsfw);
        }

        [Fact]
        public async Task ClassifyVideoUriAsync_ValidUri()
        {
            var uri = new Uri("https://i.imgur.com/MjTH5ZS.mp4");

            var nsfwSpy = new NsfwSpy();
            var result = await nsfwSpy.ClassifyVideoAsync(uri);

            Assert.Equal(120, result.Frames.Count);
            Assert.True(result.IsNsfw);
        }
    }
}


================================================
FILE: NsfwSpy.Train/ImageData.cs
================================================
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;

namespace NsfwSpyNS.Train
{
    class ImageData
    {
        public string ImagePath { get; set; }
        public string Label { get; set; }
    }
}


================================================
FILE: NsfwSpy.Train/NsfwSpy.Train.csproj
================================================
<Project Sdk="Microsoft.NET.Sdk">

  <PropertyGroup>
    <OutputType>Exe</OutputType>
    <TargetFramework>net6.0</TargetFramework>
  </PropertyGroup>

  <ItemGroup>
    <Folder Include="Models\" />
    <Folder Include="Workspace\" />
  </ItemGroup>

  <ItemGroup>
    <PackageReference Include="Microsoft.ML" Version="1.7.1" />
    <PackageReference Include="Microsoft.ML.ImageAnalytics" Version="1.7.1" />
    <PackageReference Include="Microsoft.ML.Vision" Version="1.7.1" />
    <PackageReference Include="SciSharp.TensorFlow.Redist-Windows-GPU" Version="2.3.1" />
  </ItemGroup>

</Project>


================================================
FILE: NsfwSpy.Train/Program.cs
================================================
using Microsoft.ML;
using Microsoft.ML.Trainers;
using Microsoft.ML.Vision;
using System;
using System.Collections.Generic;
using System.IO;
using System.Linq;

namespace NsfwSpyNS.Train
{
    class Program
    {
        static void Main(string[] args)
        {
            var projectDirectory = Path.GetFullPath(Path.Combine(AppContext.BaseDirectory, "../../../"));
            var workspaceRelativePath = Path.Combine(projectDirectory, "Workspace");
            var saveModelPath = Path.Combine(projectDirectory, "Models");
            var assetsPath = @"E:\NsfwSpy\Images";

            var mlContext = new MLContext();
            mlContext.Log += (object sender, LoggingEventArgs e) => Console.WriteLine(e.Message);

            var images = LoadImagesFromDirectory(assetsPath);
            var imageData = mlContext.Data.LoadFromEnumerable(images);
            var shuffledData = mlContext.Data.ShuffleRows(imageData);

            var preprocessingPipeline = mlContext.Transforms.Conversion.MapValueToKey(
                    inputColumnName: "Label",
                    outputColumnName: "LabelAsKey")
                .Append(mlContext.Transforms.LoadRawImageBytes(
                    outputColumnName: "Image",
                    imageFolder: assetsPath,
                    inputColumnName: "ImagePath"));

            var preProcessedData = preprocessingPipeline
                                .Fit(shuffledData)
                                .Transform(shuffledData);

            var trainSplit = mlContext.Data.TrainTestSplit(data: preProcessedData, testFraction: 0.1);

            var trainSet = trainSplit.TrainSet;
            var validationSet = trainSplit.TestSet;

            var classifierOptions = new ImageClassificationTrainer.Options()
            {
                FeatureColumnName = "Image",
                LabelColumnName = "LabelAsKey",
                ValidationSet = validationSet,
                Arch = ImageClassificationTrainer.Architecture.ResnetV250,
                MetricsCallback = (metrics) => Console.WriteLine(metrics),
                TestOnTrainSet = true,
                ReuseTrainSetBottleneckCachedValues = true,
                ReuseValidationSetBottleneckCachedValues = true,
                Epoch = 2500,
                BatchSize = 32,
                LearningRate = 0.01f,
                EarlyStoppingCriteria = new ImageClassificationTrainer.EarlyStopping { CheckIncreasing = true, MinDelta = 0.00001f, Patience = 50 },
                WorkspacePath = workspaceRelativePath,
                LearningRateScheduler = new ExponentialLRDecay(numEpochsPerDecay: 5)
            };

            var trainingPipeline = mlContext.MulticlassClassification.Trainers.ImageClassification(classifierOptions)
                .Append(mlContext.Transforms.Conversion.MapKeyToValue("PredictedLabel"));

            var trainedModel = trainingPipeline.Fit(trainSet);

            if (!Directory.Exists(saveModelPath))
                Directory.CreateDirectory(saveModelPath);

            saveModelPath = Path.Combine(saveModelPath, "NsfwSpyModel.zip");
            mlContext.Model.Save(trainedModel, trainSet.Schema, saveModelPath);

            Console.WriteLine("Complete");
        }

        public static IEnumerable<ImageData> LoadImagesFromDirectory(string folder)
        {
            var allowedFileExtensions = new[] { ".jpg", ".jpeg", ".png" };
            var files = Directory.GetFiles(folder, "*", searchOption: SearchOption.AllDirectories);

            foreach (var file in files)
            {
                var extension = Path.GetExtension(file);
                if (!allowedFileExtensions.Contains(extension))
                    continue;

                var label = Directory.GetParent(file).Name;

                yield return new ImageData()
                {
                    ImagePath = file,
                    Label = label
                };
            }
        }
    }
}


================================================
FILE: NsfwSpy.Train/tfjs-convert-command.txt
================================================
tensorflowjs_converter --input_format=tf_frozen_model {input_file} {export_dir} --output_node_names=Score --skip_op_check

================================================
FILE: NsfwSpy.sln
================================================

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EndProject
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================================================
FILE: README.md
================================================
<img src="https://raw.githubusercontent.com/NsfwSpy/NsfwSpy.NET/main/_art/NsfwSpy.jpg" alt="NsfwSpy Logo" width="400"/>

# Introduction
NsfwSpy is a nudity/pornography image and video classifier built for .NET Core 2.0 and later, with support for Windows, [macOS](#macos-support) and Linux, to aid in moderating user-generated content for various different application types, written in C#. The [ML.NET](https://github.com/dotnet/machinelearning) model has been trained against the ResNet V250 neural net architecture with 646,000 images (109GB), from 4 different categories:

| Label       | Description | Files |
| ----------- | ----------- | ----- |
| Pornography | Images that depict sexual acts and nudity. | 106,000 |
| Sexy        | Images of people in their underwear and men who are topless. | 78,000 |
| Hentai      | Drawings or animations of sexual acts and nudity. | 83,000 |
| Neutral     | Images that are not sexual in nature. | 378,000 |

<img src="https://raw.githubusercontent.com/d00ML0rDz/NsfwSpy/main/_art/Examples.gif" />

### Other Projects
Looking for a **JavaScript** version of NsfwSpy? We have you covered - **[NsfwSpy.js](https://github.com/d00ML0rDz/NsfwSpy.js)** 😎

# Performance
NsfwSpy isn't perfect, but the accuracy should be good enough to detect approximately 96% of Nsfw images, those being images that are classed as pornography, sexy or hentai.

|     | Pornography | Sexy | Hentai | Neutral |
| --- | --- | --- | --- | --- |
| Is Nsfw <sub><sup>(pornography + sexy + hentai >= 0.5)</sup></sub> | 95.8% | 97.0% | 95.2% | 3.7% | 
| Correctly Predicted Label | 85.7% | 84.4% | 91.9% | 96.54% |

# Quick Start
Looking to quickly try out NsfwSpy? Check out our steps to use [NsfwSpy.App](https://github.com/d00ML0rDz/NsfwSpy/tree/main/NsfwSpy.App).

This project is available as a [NuGet](https://www.nuget.org/packages/NsfwSpy/) package and can be installed with the following commands:

**Package Manager**
```
Install-Package NsfwSpy
```

**.NET CLI**
```
dotnet add package NsfwSpy
```

### Classify an Image File
```csharp
var nsfwSpy = new NsfwSpy();
var result = nsfwSpy.ClassifyImage(@"C:\Users\username\Documents\flower.jpg");
```

### Classify a Web Image
```csharp
var uri = new Uri("https://raw.githubusercontent.com/d00ML0rDz/NsfwSpy/main/NsfwSpy.Test/Assets/flower.jpg");
var nsfwSpy = new NsfwSpy();
var result = nsfwSpy.ClassifyImage(uri);
```

### Classify an Image from a Byte Array
```csharp
var fileBytes = File.ReadAllBytes(filePath);
var nsfwSpy = new NsfwSpy();
var result = nsfwSpy.ClassifyImage(fileBytes);
```

### Classify Multiple Image Files
```csharp
var files = Directory.GetFiles(@"C:\Users\username\Pictures");
var nsfwSpy = new NsfwSpy();
var results = nsfwSpy.ClassifyImages(files, (filePath, result) =>
{
    Console.WriteLine($"{filePath} - {result.PredictedLabel}");
});
```

### Classify a Gif File
```csharp
var nsfwSpy = new NsfwSpy();
var result = nsfwSpy.ClassifyGif(@"C:\Users\username\Documents\happy.gif");
```

### Classify a Web Gif
```csharp
var uri = new Uri("https://raw.githubusercontent.com/d00ML0rDz/NsfwSpy/main/NsfwSpy.Test/Assets/cool.gif");
var nsfwSpy = new NsfwSpy();
var result = nsfwSpy.ClassifyGif(uri);
```

### Classify a Video File
```csharp
var nsfwSpy = new NsfwSpy();
var result = nsfwSpy.ClassifyVideo(@"C:\Users\username\Documents\happy.mp4");
```

### Classify a Web Video
```csharp
var uri = new Uri("https://raw.githubusercontent.com/d00ML0rDz/NsfwSpy/main/NsfwSpy.Test/Assets/bikini.mp4");
var nsfwSpy = new NsfwSpy();
var result = nsfwSpy.ClassifyVideo(uri);
```

### Dependency Injection
```csharp
services.AddScoped<INsfwSpy, NsfwSpy>();
```

# Classify Video Support
To be able to make use of the ClassifyVideo methods, [FFmpeg](https://www.ffmpeg.org/) needs to be installed and available in the command line via the 'ffmpeg' command.

## Windows 
Follow [this guide](https://www.geeksforgeeks.org/how-to-install-ffmpeg-on-windows/) to download FFmpeg, extract it to your C:\ drive and add the required environment path variable.

## macOS
Install FFmpeg on macOS using [Homebrew](https://brew.sh/) via the following command:
```
brew install ffmpeg
```

## Ubuntu
Install FFmpeg on Ubuntu using the following command:
```
sudo apt install ffmpeg
```

# GPU Support
To get GPU support working, please follow the prerequisite steps [here](https://docs.microsoft.com/en-us/dotnet/api/microsoft.ml.vision.imageclassificationtrainer?view=ml-dotnet&fbclid=IwAR3Ng6Pe1BWDZ3hR20tchutSozmdMojxvpy3pqdwA3fZ_OEstU8C-ptSRZw#gpu-support) to install [CUDA v10.1](https://developer.nvidia.com/cuda-10.1-download-archive-update2) and [CUDNN v7.6.4 for CUDA 10.1](https://developer.nvidia.com/rdp/cudnn-archive). Later versions do not work (as I tried with CUDA v11.4). The SciSharp.TensorFlow.Redist-Windows-GPU and SciSharp.TensorFlow.Redist-Linux-GPU packages are already included as part of the NsfwSpy package.

# macOS Support
To get NsfwSpy working on macOS, the [SciSharp.TensorFlow.Redist v2.3.1](https://www.nuget.org/packages/SciSharp.TensorFlow.Redist/2.3.1) NuGet package also needs to be installed. This not included by default as it interfers with supporting GPUs on Windows and Linux. You can do this with either of the following commands:

**Package Manager**
```
Install-Package SciSharp.TensorFlow.Redist -Version 2.3.1
```

**.NET CLI**
```
dotnet add package SciSharp.TensorFlow.Redist --version 2.3.1
```

Please note that Macs that use M1 chips currently [do not support TensorFlow](https://github.com/dotnet/machinelearning/blob/main/docs/project-docs/platform-limitations.md) with ML.NET and cannot make use of NsfwSpy.

# Contact Us
Interested to get involved in the project? Whether you fancy adding features, providing images to train NsfwSpy with or something else, feel free to contact us via email at [nsfwspy@outlook.com](mailto:nsfwspy@outlook.com) or find us on Twitter at [@nsfw_spy](https://twitter.com/nsfw_spy).

# Notes
Using NsfwSpy? Let us know! We're keen to hear how the technology is being used and improving the safety of applications.

Got a feature request or found something not quite right? Report it [here](https://github.com/d00ML0rDz/NsfwSpy/issues) on GitHub and we'll try to help as best as possible.