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This repository is dedicated for building a classifier to detect NSFW Images & Videos.

Table of Contents

• Installation
• Usage
• Development
• License

Installation

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To use this project, first clone the repo on your device using the command given below:

git init

git clone https://github.com/LaxmanSinghTomar/nsfw-classifier.git

Usage

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Install the required libraries & packages using:

pip install requirements.txt

To download the dataset upon which the model was trained run:

python src/scripts/data.sh

If run successfully, this should create a directory data in the project directory.

To run a quick demo using an image and a video run:

python src/scripts/inference.sh

To identify whether an image contains NSFW content or not using the default model run:

python src/inference/inference_image.py [img-path]

To identify whether a video is NSFW or not using the default model run:

python src/inference/inference_video.py [video-path]

Output Video is saved in the output directory.

Note: The default trained model is MobileNetv2 which is smaller in size due to which loads quickly and is good for inference.

Development

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.
├── LICENSE
├── models                         <- Trained and Serialized Models
├── notebooks                      <- Jupyter Notebook
├── NSFW Classifier.png
├── output                         <- Output for Videos
├── README.md
├── references                     <- Reference Materials to understand Approaches & Solutions
├── reports                        <- Reports & Figures Generated
│   ├── figures
├── requirements.txt               <- Requirements File for reproducing the analysis environment 
└── src
    ├── config.py                  <- Script for Configuration like File Paths, default Model
    ├── inference                  <- Scripts for running an inference on either image/video using trained model
    │   ├── inference_image.py
    │   └── inference_video.py
    ├── models                     <- Scripts to train the ML Models
    │   ├── efficientnet.py
    │   ├── mobilenet.py
    │   └── nasnetmobile.py
    ├── scripts                    <- Scripts to download dataset and run inference on an image/video for Demo
    │   ├── data.sh
    │   └── inference.sh
    └── visualizations             <- Scripts to create exploratory and results oriented visualizations
        └── visualizations.py

If you wish to change the default model for predictions i.e. MobileNetv2, change MODEL_PATH in src/config.py to the either of the models available in models directory.

License

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GNU General Public License version 3