
backgroundremover
Background Remover lets you Remove Background from images and video using AI with a simple command line interface that is free and open source.
Stars: 6247

BackgroundRemover is a command line tool to remove background from image and video using AI. It requires python >= 3.6, torch, torchvision, and ffmpeg. The tool can be installed via pip or Docker. It offers various options for image and video background removal, including alpha matting and different models. Users can also use it as a library to remove background from images. The project aims to enhance background removal capabilities, improve documentation, add new features like real-time background removal for videos, and provide the ability to use custom models.
README:
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.
-
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
Go to https://pytorch.org and scroll down to INSTALL PYTORCH
section and follow the instructions.
For example:
PyTorch Build: Stable (1.7.1)
Your OS: Windows
Package: Pip
Language: Python
CUDA: None
To install ffmpeg and python-dev
sudo apt install ffmpeg python3.6-dev
To Install backgroundremover, install it from pypi
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
python -m backgroundremover.cmd.cli -i "video.mp4" -mk -o "output.mov"
and for windows
python.exe -m backgroundremover.cmd.cli -i "video.mp4" -mk -o "output.mov"
git clone https://github.com/nadermx/backgroundremover.git
cd backgroundremover
docker build -t bgremover .
alias backgroundremover='docker run -it --rm -v "$(pwd):/tmp" bgremover:latest'
Remove the background from a local file image
backgroundremover -i "/path/to/image.jpeg" -o "output.png"
Sometimes it is possible to achieve better results by turning on alpha matting. Example:
backgroundremover -i "/path/to/image.jpeg" -a -ae 15 -o "output.png"
change the model for different background removal methods between u2netp
, u2net
, or u2net_human_seg
backgroundremover -i "/path/to/image.jpeg" -m "u2net_human_seg" -o "output.png"
backgroundremover -i "/path/to/video.mp4" -tv -o "output.mov"
backgroundremover -i "/path/to/video.mp4" -tov "/path/to/videtobeoverlayed.mp4" -o "output.mov"
backgroundremover -i "/path/to/video.mp4" -toi "/path/to/videtobeoverlayed.mp4" -o "output.mov"
backgroundremover -i "/path/to/video.mp4" -tg -o "output.gif"
Make a matte file for premiere
backgroundremover -i "/path/to/video.mp4" -mk -o "output.matte.mp4"
Change the framerate of the video (default is set to 30)
backgroundremover -i "/path/to/video.mp4" -fr 30 -tv -o "output.mov"
Set total number of frames of the video (default is set to -1, ie the remove background from full video)
backgroundremover -i "/path/to/video.mp4" -fl 150 -tv -o "output.mov"
Change the gpu batch size of the video (default is set to 1)
backgroundremover -i "/path/to/video.mp4" -gb 4 -tv -o "output.mov"
Change the number of workers working on video (default is set to 1)
backgroundremover -i "/path/to/video.mp4" -wn 4 -tv -o "output.mov"
change the model for different background removal methods between u2netp
, u2net
, or u2net_human_seg
and limit the frames to 150
backgroundremover -i "/path/to/video.mp4" -m "u2net_human_seg" -fl 150 -tv -o "output.mov"
from backgroundremover.bg import remove
def remove_bg(src_img_path, out_img_path):
model_choices = ["u2net", "u2net_human_seg", "u2netp"]
f = open(src_img_path, "rb")
data = f.read()
img = remove(data, model_name=model_choices[0],
alpha_matting=True,
alpha_matting_foreground_threshold=240,
alpha_matting_background_threshold=10,
alpha_matting_erode_structure_size=10,
alpha_matting_base_size=1000)
f.close()
f = open(out_img_path, "wb")
f.write(img)
f.close()
- convert logic from video to image to utilize more GPU on image removal
- clean up documentation a bit more
- add ability to adjust and give feedback images or videos to datasets
- add ability to realtime background removal for videos, for streaming
- finish flask server api
- add ability to use other models than u2net, ie your own
- other
Accepted
Give a link to our project BackgroundRemoverAI.com or this git, telling people that you like it or use it.
We made it our own package after merging together parts of others, adding in a few features of our own via posting parts as bounty questions on superuser, etc. As well as asked on hackernews earlier to open source the image part, so decided to add in video, and a bit more.
- https://arxiv.org/pdf/2005.09007.pdf
- https://github.com/NathanUA/U-2-Net
- https://github.com/pymatting/pymatting
- https://github.com/danielgatis/rembg
- https://github.com/ecsplendid/rembg-greenscreen
- https://superuser.com/questions/1647590/have-ffmpeg-merge-a-matte-key-file-over-the-normal-video-file-removing-the-backg
- https://superuser.com/questions/1648680/ffmpeg-alphamerge-two-videos-into-a-gif-with-transparent-background/1649339?noredirect=1#comment2522687_1649339
- https://superuser.com/questions/1649817/ffmpeg-overlay-a-video-after-alphamerging-two-others/1649856#1649856
- Copyright (c) 2021-present Johnathan Nader
- Copyright (c) 2020-present Lucas Nestler
- Copyright (c) 2020-present Dr. Tim Scarfe
- Copyright (c) 2020-present Daniel Gatis
Code Licensed under MIT License Models Licensed under Apache License 2.0
For Tasks:
Click tags to check more tools for each tasksFor Jobs:
Alternative AI tools for backgroundremover
Similar Open Source Tools

backgroundremover
BackgroundRemover is a command line tool to remove background from image and video using AI. It requires python >= 3.6, torch, torchvision, and ffmpeg. The tool can be installed via pip or Docker. It offers various options for image and video background removal, including alpha matting and different models. Users can also use it as a library to remove background from images. The project aims to enhance background removal capabilities, improve documentation, add new features like real-time background removal for videos, and provide the ability to use custom models.

sdfx
SDFX is the ultimate no-code platform for building and sharing AI apps with beautiful UI. It enables the creation of user-friendly interfaces for complex workflows by combining Comfy workflow with a UI. The tool is designed to merge the benefits of form-based UI and graph-node based UI, allowing users to create intricate graphs with a high-level UI overlay. SDFX is fully compatible with ComfyUI, abstracting the need for installing ComfyUI. It offers features like animated graph navigation, node bookmarks, UI debugger, custom nodes manager, app and template export, image and mask editor, and more. The tool compiles as a native app or web app, making it easy to maintain and add new features.

june
june-va is a local voice chatbot that combines Ollama for language model capabilities, Hugging Face Transformers for speech recognition, and the Coqui TTS Toolkit for text-to-speech synthesis. It provides a flexible, privacy-focused solution for voice-assisted interactions on your local machine, ensuring that no data is sent to external servers. The tool supports various interaction modes including text input/output, voice input/text output, text input/audio output, and voice input/audio output. Users can customize the tool's behavior with a JSON configuration file and utilize voice conversion features for voice cloning. The application can be further customized using a configuration file with attributes for language model, speech-to-text model, and text-to-speech model configurations.

lexido
Lexido is an innovative assistant for the Linux command line, designed to boost your productivity and efficiency. Powered by Gemini Pro 1.0 and utilizing the free API, Lexido offers smart suggestions for commands based on your prompts and importantly your current environment. Whether you're installing software, managing files, or configuring system settings, Lexido streamlines the process, making it faster and more intuitive.

clickclickclick
ClickClickClick is a framework designed to enable autonomous Android and computer use using various LLM models, both locally and remotely. It supports tasks such as drafting emails, opening browsers, and starting games, with current support for local models via Ollama, Gemini, and GPT 4o. The tool is highly experimental and evolving, with the best results achieved using specific model combinations. Users need prerequisites like `adb` installation and USB debugging enabled on Android phones. The tool can be installed via cloning the repository, setting up a virtual environment, and installing dependencies. It can be used as a CLI tool or script, allowing users to configure planner and finder models for different tasks. Additionally, it can be used as an API to execute tasks based on provided prompts, platform, and models.

memobase
Memobase is a user profile-based memory system designed to enhance Generative AI applications by enabling them to remember, understand, and evolve with users. It provides structured user profiles, scalable profiling, easy integration with existing LLM stacks, batch processing for speed, and is production-ready. Users can manage users, insert data, get memory profiles, and track user preferences and behaviors. Memobase is ideal for applications that require user analysis, tracking, and personalized interactions.

core
The Cheshire Cat is a framework for building custom AIs on top of any language model. It provides an API-first approach, making it easy to add a conversational layer to your application. The Cat remembers conversations and documents, and uses them in conversation. It is extensible via plugins, and supports event callbacks, function calling, and conversational forms. The Cat is easy to use, with an admin panel that allows you to chat with the AI, visualize memory and plugins, and adjust settings. It is also production-ready, 100% dockerized, and supports any language model.

chat-mcp
A Cross-Platform Interface for Large Language Models (LLMs) utilizing the Model Context Protocol (MCP) to connect and interact with various LLMs. The desktop app, built on Electron, ensures compatibility across Linux, macOS, and Windows. It simplifies understanding MCP principles, facilitates testing of multiple servers and LLMs, and supports dynamic LLM configuration and multi-client management. The UI can be extracted for web use, ensuring consistency across web and desktop versions.

langserve
LangServe helps developers deploy `LangChain` runnables and chains as a REST API. This library is integrated with FastAPI and uses pydantic for data validation. In addition, it provides a client that can be used to call into runnables deployed on a server. A JavaScript client is available in LangChain.js.

supabase-mcp
Supabase MCP Server standardizes how Large Language Models (LLMs) interact with Supabase, enabling AI assistants to manage tables, fetch config, and query data. It provides tools for project management, database operations, project configuration, branching (experimental), and development tools. The server is pre-1.0, so expect some breaking changes between versions.

ai-artifacts
AI Artifacts is an open source tool that replicates Anthropic's Artifacts UI in the Claude chat app. It utilizes E2B's Code Interpreter SDK and Core SDK for secure AI code execution in a cloud sandbox environment. Users can run AI-generated code in various languages such as Python, JavaScript, R, and Nextjs apps. The tool also supports running AI-generated Python in Jupyter notebook, Next.js apps, and Streamlit apps. Additionally, it offers integration with Vercel AI SDK for tool calling and streaming responses from the model.

Kolo
Kolo is a lightweight tool for fast and efficient data generation, fine-tuning, and testing of Large Language Models (LLMs) on your local machine. It simplifies the fine-tuning and data generation process, runs locally without the need for cloud-based services, and supports popular LLM toolkits. Kolo is built using tools like Unsloth, Torchtune, Llama.cpp, Ollama, Docker, and Open WebUI. It requires Windows 10 OS or higher, Nvidia GPU with CUDA 12.1 capability, and 8GB+ VRAM, and 16GB+ system RAM. Users can join the Discord group for issues or feedback. The tool provides easy setup, training data generation, and integration with major LLM frameworks.

aiconfig
AIConfig is a framework that makes it easy to build generative AI applications for production. It manages generative AI prompts, models and model parameters as JSON-serializable configs that can be version controlled, evaluated, monitored and opened in a local editor for rapid prototyping. It allows you to store and iterate on generative AI behavior separately from your application code, offering a streamlined AI development workflow.

gemini-srt-translator
Gemini SRT Translator is a tool that utilizes Google Generative AI to provide accurate and efficient translations for subtitle files. Users can customize translation settings, such as model name and batch size, and list available models from the Gemini API. The tool requires a free API key from Google AI Studio for setup and offers features like translating subtitles to a specified target language and resuming partial translations. Users can further customize translation settings with optional parameters like gemini_api_key2, output_file, start_line, model_name, batch_size, and more.

agent-mimir
Agent Mimir is a command line and Discord chat client 'agent' manager for LLM's like Chat-GPT that provides the models with access to tooling and a framework with which accomplish multi-step tasks. It is easy to configure your own agent with a custom personality or profession as well as enabling access to all tools that are compatible with LangchainJS. Agent Mimir is based on LangchainJS, every tool or LLM that works on Langchain should also work with Mimir. The tasking system is based on Auto-GPT and BabyAGI where the agent needs to come up with a plan, iterate over its steps and review as it completes the task.

langchain-extract
LangChain Extract is a simple web server that allows you to extract information from text and files using LLMs. It is built using FastAPI, LangChain, and Postgresql. The backend closely follows the extraction use-case documentation and provides a reference implementation of an app that helps to do extraction over data using LLMs. This repository is meant to be a starting point for building your own extraction application which may have slightly different requirements or use cases.
For similar tasks

backgroundremover
BackgroundRemover is a command line tool to remove background from image and video using AI. It requires python >= 3.6, torch, torchvision, and ffmpeg. The tool can be installed via pip or Docker. It offers various options for image and video background removal, including alpha matting and different models. Users can also use it as a library to remove background from images. The project aims to enhance background removal capabilities, improve documentation, add new features like real-time background removal for videos, and provide the ability to use custom models.
For similar jobs

LLMStack
LLMStack is a no-code platform for building generative AI agents, workflows, and chatbots. It allows users to connect their own data, internal tools, and GPT-powered models without any coding experience. LLMStack can be deployed to the cloud or on-premise and can be accessed via HTTP API or triggered from Slack or Discord.

daily-poetry-image
Daily Chinese ancient poetry and AI-generated images powered by Bing DALL-E-3. GitHub Action triggers the process automatically. Poetry is provided by Today's Poem API. The website is built with Astro.

exif-photo-blog
EXIF Photo Blog is a full-stack photo blog application built with Next.js, Vercel, and Postgres. It features built-in authentication, photo upload with EXIF extraction, photo organization by tag, infinite scroll, light/dark mode, automatic OG image generation, a CMD-K menu with photo search, experimental support for AI-generated descriptions, and support for Fujifilm simulations. The application is easy to deploy to Vercel with just a few clicks and can be customized with a variety of environment variables.

SillyTavern
SillyTavern is a user interface you can install on your computer (and Android phones) that allows you to interact with text generation AIs and chat/roleplay with characters you or the community create. SillyTavern is a fork of TavernAI 1.2.8 which is under more active development and has added many major features. At this point, they can be thought of as completely independent programs.

Twitter-Insight-LLM
This project enables you to fetch liked tweets from Twitter (using Selenium), save it to JSON and Excel files, and perform initial data analysis and image captions. This is part of the initial steps for a larger personal project involving Large Language Models (LLMs).

AISuperDomain
Aila Desktop Application is a powerful tool that integrates multiple leading AI models into a single desktop application. It allows users to interact with various AI models simultaneously, providing diverse responses and insights to their inquiries. With its user-friendly interface and customizable features, Aila empowers users to engage with AI seamlessly and efficiently. Whether you're a researcher, student, or professional, Aila can enhance your AI interactions and streamline your workflow.

ChatGPT-On-CS
This project is an intelligent dialogue customer service tool based on a large model, which supports access to platforms such as WeChat, Qianniu, Bilibili, Douyin Enterprise, Douyin, Doudian, Weibo chat, Xiaohongshu professional account operation, Xiaohongshu, Zhihu, etc. You can choose GPT3.5/GPT4.0/ Lazy Treasure Box (more platforms will be supported in the future), which can process text, voice and pictures, and access external resources such as operating systems and the Internet through plug-ins, and support enterprise AI applications customized based on their own knowledge base.

obs-localvocal
LocalVocal is a live-streaming AI assistant plugin for OBS that allows you to transcribe audio speech into text and perform various language processing functions on the text using AI / LLMs (Large Language Models). It's privacy-first, with all data staying on your machine, and requires no GPU, cloud costs, network, or downtime.