README

BackgroundRemover
!Background Remover

BackgroundRemover is a command line tool to remove background from image and video using AI, made by nadermx to power https://BackgroundRemoverAI.com. If you wonder why it was made read this short blog post.


 Requirements

 python = 3.6
 python3.6-dev or what ever version of python you use
 torch and torchvision stable version (https://pytorch.org)
 ffmpeg 4.4+

 To clarify, you must install both python and whatever dev version of python you installed. IE; python3.10-dev with python3.10 or python3.8-dev with python3.8

 How to install torch and ffmpeg

Go to https://pytorch.org and scroll down to INSTALL PYTORCH section and follow the instructions.

For CPU-only (default):

bash
pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cpu


For GPU (CUDA) support:

bash
 For CUDA 11.8
pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu118

 For CUDA 12.1
pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu121


Visit https://pytorch.org/get-started/locally/ to find the correct command for your CUDA version.

To install ffmpeg and python-dev:

bash
sudo apt install ffmpeg python3.6-dev


 Installation
To Install backgroundremover, install it from pypi

bash
pip install --upgrade pip
pip install backgroundremover

Please note that when you first run the program, it will check to see if you have the u2net models, if you do not, it will pull them from this repo

It is also possible to run this without installing it via pip, just clone the git to local start a virtual env and install requirements and run
bash
python -m backgroundremover.cmd.cli -i "video.mp4" -mk -o "output.mov"

and for windows
bash
python.exe -m backgroundremover.cmd.cli -i "video.mp4" -mk -o "output.mov"

 Installation using Docker
bash
git clone https://github.com/nadermx/backgroundremover.git
cd backgroundremover
docker build -t bgremover .
 Basic usage (models will be downloaded on each run)
alias backgroundremover='docker run -it --rm -v "$(pwd):/tmp" bgremover:latest'

 Recommended: Persist models between runs to avoid re-downloading
mkdir -p ~/.u2net
alias backgroundremover='docker run -it --rm -v "$(pwd):/tmp" -v "$HOME/.u2net:/root/.u2net" bgremover:latest'

 For video processing: Increase shared memory to avoid multiprocessing errors
alias backgroundremover='docker run -it --rm --shm-size=2g -v "$(pwd):/tmp" -v "$HOME/.u2net:/root/.u2net" bgremover:latest'


Note for Docker video processing: Video processing uses multiprocessing which requires adequate shared memory. If you encounter errors like OSError: [Errno 95] Operation not supported, use --shm-size=2g (or higher) or --ipc=host when running the container.

 GPU Acceleration

BackgroundRemover automatically detects and uses your GPU if available, which provides significant speed improvements (typically 5-10x faster than CPU).

To verify GPU is being used:

bash
python3 -c "import torch; print('GPU available: