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46.0 1.0 11.0 18.78 MB

A Docker REST API for NSFW detection

License: MIT License

Dockerfile 7.06% JavaScript 1.71% TypeScript 91.23%

docker nsfw nsfwjs rest-api tensorflow tensorflowjs typescript nodejs

nsfwjs-docker's Introduction

nsfwjs-docker

Features ✨

ℹ️ Return predictions for Neutral, Drawing, Sexy, Hentai and Porn
🎯 Pretty accurate (~93%)
🖼️ Supports different image formats
⚡ 250ms to make predictions to a single image

About 🗞️

A Docker REST API for NSFW detection with NSFWJS. You can find it on the Docker Hub here. Created for my social network app, Rybun

Installation ⚙️

docker run -p 3333:3333 -d --name nsfwjs andresribeiroo/nsfwjs:1.6

If you are deploying in production, you will probably want to pass the --restart always flag to start the container whenever the server restarts

Usage 🔨

One image, multipart/form-data

POST request to /single/multipart-form sending an image in the content field

{
  "prediction": [
    {
      "className": "Neutral",
      "probability": 0.6371303796768188
    },
    {
      "className": "Drawing",
      "probability": 0.3603636920452118
    },
    {
      "className": "Hentai",
      "probability": 0.0024505197070538998
    },
    {
      "className": "Sexy",
      "probability": 0.00003775714503717609
    },
    {
      "className": "Porn",
      "probability": 0.000017730137187754735
    }
  ]
}

Multiple images, multipart/form-data

POST request to /multiple/multipart-form sending images in the contents field

{
  "predictions": [
    [
      {
        "className": "Neutral",
        "probability": 0.6371303796768188
      },
      {
        "className": "Drawing",
        "probability": 0.3603636920452118
      },
      {
        "className": "Hentai",
        "probability": 0.0024505197070538998
      },
      {
        "className": "Sexy",
        "probability": 0.00003775714503717609
      },
      {
        "className": "Porn",
        "probability": 0.000017730137187754735
      }
    ],
    [
      {
        "className": "Neutral",
        "probability": 0.9498893618583679
      },
      {
        "className": "Drawing",
        "probability": 0.04626458138227463
      },
      {
        "className": "Hentai",
        "probability": 0.00267870188690722
      },
      {
        "className": "Sexy",
        "probability": 0.0008198379655368626
      },
      {
        "className": "Porn",
        "probability": 0.0003475486591923982
      }
    ]
  ]
}

nsfwjs-docker's People

Contributors

Stargazers

Watchers

Forkers

daiyuanchuan hewen arnidan chypay lusalem desifeelsapp rossman22590 azure-dragon-ai scipiojr dysf888

nsfwjs-docker's Issues

Error 500: Input to reshape is a tensor with 451584 values, but the requested shape has 150528

Hello,

When I use GIF image with this command line:

curl -F "content=@/images/a.gif" "http://localhost:3333/single/multipart-form"

I have this error:

{"statusCode":500,"error":"Internal Server Error","message":"Invalid TF_Status: 3\nMessage: Input to reshape is a tensor with 451584 values, but the requested shape has 150528"}

Why? How can I fix this?

Thank you!

How to change model content

It doesn't seem to be particularly accurate. I want to try to replace it with a more accurate model

Illegal instruction - ELIFECYCLE Command failed with exit code 132.

When I run the container using the same command defined in the README...

docker run -p 3333:3333 -d --name nsfwjs andresribeiroo/nsfwjs:1.6

...we can see the following error:

2024-05-06 15:31:16 
2024-05-06 15:31:16 > [email protected] start /app
2024-05-06 15:31:16 > node dist/server.js
2024-05-06 15:31:16 
2024-05-06 15:31:18 Illegal instruction
2024-05-06 15:31:18  ELIFECYCLE  Command failed with exit code 132.

Any ideas?

Screenshot 2024-05-06 at 15 33 42

Empty reply from server

After I posted a jpg file by curl like this,
curl -F "[email protected]" "http://localhost:3333/single/multipart-form"
I got the replay
curl: (52) Empty reply from server
And then the server app has been terminated.

Illegal instruction (core dumped)

I cloned the project and did the normal installation without errors. however, after trying to start the project with npm start, this error simply appears in the console.

any solution tips?

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