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---
title: Video Background Removal
emoji: 👁
colorFrom: green
colorTo: yellow
sdk: streamlit
sdk_version: 1.31.1
app_file: app.py
pinned: false
---
# AI Powered Video Background Removal Tool
[](https://github.com/killian31/VideoBackgroundRemoval/stargazers)
[](https://github.com/killian31/VideoBackgroundRemoval/actions/workflows/github-actions-black-formatting.yml)
[](https://wakatime.com/badge/github/killian31/VideoBackgroundRemoval)
The Video Background Removal Tool is designed to enable users to effortlessly remove backgrounds from videos by selecting a subject in a single frame. This powerful tool is optimized to run on CPUs and boasts a user-friendly interface, making it ideal for a wide range of users, especially online content creators like YouTubers.
<p align="center">
<table>
<tr>
<td>
<img src="assets/example.gif" width="385" height="216" />
</td>
<td>
<img src="assets/output_example.gif" width="385" height="216" />
</td>
</tr>
</table>
</p>
## Contents
Table of contents:
- [Installation](#installation)
- [Usage](#usage)
- [Example](#example)
- [Contribution](#how-to-contribute)
## Installation
### With pyenv and poetry
```bash
git clone https://github.com/killian31/VideoBackgroundRemoval.git
cd VideoBackgroundRemoval
pyenv virtualenv 3.11.9 vbr
pyenv activate vbr
pip install poetry
poetry install
```
## Usage
### Using the Streamlit app (locally)
Run `streamlit run app.py` to launch the Streamlit app. Then, upload a video, draw a
bounding box around what you want to remove the background from, using the sliders,
and click on Segment Video.
### Command line
```bash
usage: main.py [-h] [--video_filename VIDEO_FILENAME] [--dir_frames DIR_FRAMES] [--image_start IMAGE_START] [--image_end IMAGE_END] [--bbox_file BBOX_FILE] [--skip_vid2im]
[--mobile_sam_weights MOBILE_SAM_WEIGHTS] [--tracker_name {yolov7,yoloS}] [--output_dir OUTPUT_DIR] [--output_video OUTPUT_VIDEO] [--auto_detect]
[--background_color BACKGROUND_COLOR]
options:
-h, --help show this help message and exit
--video_filename VIDEO_FILENAME
path to the video
--dir_frames DIR_FRAMES
path to the directory in which all input frames will be stored
--image_start IMAGE_START
first image to be stored
--image_end IMAGE_END
last image to be stored, last one if 0
--bbox_file BBOX_FILE
path to the bounding box text file
--skip_vid2im whether to write the video frames as images
--mobile_sam_weights MOBILE_SAM_WEIGHTS
path to MobileSAM weights
--tracker_name {yolov7,yoloS}
tracker name
--output_dir OUTPUT_DIR
directory to store the output frames
--output_video OUTPUT_VIDEO
path to store the output video
--auto_detect whether to use a bounding box to force the model to segment the object
--background_color BACKGROUND_COLOR
background color for the output (hex)
```
## Example
The following command line is a working example from a video stored in the repo:
```bash
python3 main.py --video_filename assets/example.mp4 --dir_frames ./frames --bbox_file bbox.txt --mobile_sam_weights models/mobile_sam.pt --output_dir output_frames --output_video output.mp4
```
## How to Contribute
We welcome contributions from the community! To ensure a consistent code style, we ask contributors to follow these guidelines:
### Code Format
Please format your code using the `black` code formatter.
#### Installation
```bash
pip install black
```
#### Usage
To format your code:
```bash
black .
```
This setup will help maintain a consistent coding style throughout the project.
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