smutminer's Introduction

smutminer

Extract/Score NSFW images from local directory structures. Updated for Tensorflow2 and OpenNSFW2

Install and configure Tensorflow

Install Miniconda

curl https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -o Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh

Create a conda environment

conda create --name opennsfw2 python=3.9
conda activate opennsfw2

GPU Setup

conda install -c conda-forge cudatoolkit=11.2 cudnn=8.1.0
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$CONDA_PREFIX/lib/
mkdir -p $CONDA_PREFIX/etc/conda/activate.d
echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$CONDA_PREFIX/lib/' > $CONDA_PREFIX/etc/conda/activate.d/env_vars.sh

Install TensorFlow

pip install --upgrade pip
pip install tensorflow

Install other requirements

Ensure the correct conda environment is activated and run

pip install -r requirements.txt

Running

Activate the conda environment you created above

conda activate opennsfw2

smutminer.py --help
usage: smutminer.py [-h] [-t THRESHOLD] [-l | --list | --no-list] [-v] [-a | --all | --no-all] {move,copy,link,score} [directory] [output]

positional arguments:
  {move,copy,link,score}
                        Action to take, default: Print the image path and NSFW Score to stdout
  directory             Input Directory. Default: current working directory.
  output                Output Subdirectory. Default: ./nsfw

options:
  -h, --help            show this help message and exit
  -t THRESHOLD, --threshold THRESHOLD
                        Default matching threshold for the open_nsfw model (0 - 1). Default: .7
  -l, --list, --no-list
                        Write a list of original file paths to the output directory
  -v, --verbose         Output verbosity (1-3). Default: Print paths and scores only
  -a, --all, --no-all   Print scores for every image found

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