NsfwSpy 3.5.0

.NET Core 2.0
dotnet add package NsfwSpy --version 3.5.0
NuGet\Install-Package NsfwSpy -Version 3.5.0
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package.
<PackageReference Include="NsfwSpy" Version="3.5.0" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add NsfwSpy --version 3.5.0
#r "nuget: NsfwSpy, 3.5.0"
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package.
// Install NsfwSpy as a Cake Addin
#addin nuget:?package=NsfwSpy&version=3.5.0

// Install NsfwSpy as a Cake Tool
#tool nuget:?package=NsfwSpy&version=3.5.0


NsfwSpy is a nudity/pornography image and video classifier built for .NET Core 2.0 and later, with support for Windows, macOS and Linux, to aid in moderating user-generated content for various different application types, written in C#. The ML.NET model has been trained against the ResNet V250 neural net architecture with 537,000 images (186GB), from 4 different categories:

Label Description Files
Pornography Images that depict sexual acts and nudity. 108,000
Sexy Images of people in their underwear and men who are topless. 76,000
Hentai Drawings or animations of sexual acts and nudity. 83,000
Neutral Images that are not sexual in nature. 268,000

Other Projects

Looking for a JavaScript version of NsfwSpy? We have you covered - NsfwSpy.js 😎


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 (pornography + sexy + hentai >= 0.5) 96.5% 97.2% 95.1% 3.7%
Correctly Predicted Label 86.0% 83.2% 91.8% 96.8%

Quick Start

Looking to quickly try out NsfwSpy? Check out our steps to use NsfwSpy.App.

This project is available as a NuGet package and can be installed with the following commands:

Package Manager

Install-Package NsfwSpy


dotnet add package NsfwSpy

Classify an Image File

var nsfwSpy = new NsfwSpy();
var result = nsfwSpy.ClassifyImage(@"C:\Users\username\Documents\flower.jpg");

Classify a Web Image

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

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

Classify Multiple Image Files

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

var nsfwSpy = new NsfwSpy();
var result = nsfwSpy.ClassifyGif(@"C:\Users\username\Documents\happy.gif");

Classify a Web Gif

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

var nsfwSpy = new NsfwSpy();
var result = nsfwSpy.ClassifyVideo(@"C:\Users\username\Documents\happy.mp4");

Classify a Web Video

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

services.AddScoped<INsfwSpy, NsfwSpy>();

Classify Video Support

To be able to make use of the ClassifyVideo methods, FFmpeg needs to be installed and available in the command line via the 'ffmpeg' command.


Follow this guide to download FFmpeg, extract it to your C:\ drive and add the required environment path variable.


Install FFmpeg on macOS using Homebrew via the following command:

brew install ffmpeg


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 to install CUDA v10.1 and CUDNN v7.6.4. 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 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


dotnet add package SciSharp.TensorFlow.Redist --version 2.3.1

Please note that Macs that use M1 chips currently do not support TensorFlow 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 or find us on Twitter at @nsfw_spy.


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 on GitHub and we'll try to help as best as possible.

Product Compatible and additional computed target framework versions.
.NET net5.0 was computed.  net5.0-windows was computed.  net6.0 was computed.  net6.0-android was computed.  net6.0-ios was computed.  net6.0-maccatalyst was computed.  net6.0-macos was computed.  net6.0-tvos was computed.  net6.0-windows was computed.  net7.0 was computed.  net7.0-android was computed.  net7.0-ios was computed.  net7.0-maccatalyst was computed.  net7.0-macos was computed.  net7.0-tvos was computed.  net7.0-windows was computed.  net8.0 was computed.  net8.0-android was computed.  net8.0-ios was computed.  net8.0-maccatalyst was computed.  net8.0-macos was computed.  net8.0-tvos was computed.  net8.0-windows was computed. 
.NET Core netcoreapp2.0 is compatible.  netcoreapp2.1 was computed.  netcoreapp2.2 was computed.  netcoreapp3.0 was computed.  netcoreapp3.1 was computed. 
Compatible target framework(s)
Additional computed target framework(s)
Learn more about Target Frameworks and .NET Standard.

NuGet packages

This package is not used by any NuGet packages.

GitHub repositories

This package is not used by any popular GitHub repositories.

Version Downloads Last updated
3.5.0 23,659 11/5/2022
3.4.3 5,062 5/28/2022
3.4.2 3,372 5/18/2022
3.4.1 2,841 5/17/2022
3.4.0 4,420 5/3/2022
3.3.1 3,181 5/3/2022
3.3.0 3,209 4/25/2022
3.2.0 3,227 4/15/2022
3.1.0 2,757 12/24/2021
3.0.1 2,056 12/14/2021
3.0.0 2,198 12/8/2021
2.5.0 1,999 11/3/2021
2.4.0 2,142 10/9/2021
2.3.0 2,110 10/6/2021
2.2.0 2,123 10/6/2021
2.2.0-beta.1 285 10/6/2021
2.2.0-alpha 1,698 10/6/2021
2.1.0 2,260 9/24/2021
2.0.0 2,054 9/23/2021
1.2.0 2,285 9/19/2021
1.1.1 2,216 9/19/2021
1.1.0 1,941 9/18/2021
1.0.11 2,126 9/17/2021
1.0.10 2,124 9/17/2021
1.0.9 2,190 9/17/2021
1.0.8 2,100 9/16/2021
1.0.7 2,198 9/16/2021
1.0.6 1,349 9/16/2021
1.0.5 1,461 9/16/2021
1.0.4 1,355 9/16/2021
1.0.3 2,086 9/16/2021
1.0.2 573 9/16/2021
1.0.1 611 9/16/2021
1.0.0 564 9/16/2021