AI Powered Video Background Removal Tool

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.

Contents

Table of contents:

• State of development
• Installation
• Usage
• Example
• Contribution

How it works and state of development

• Initial Selection: Users draw a bounding box around the desired character in the first frame of the video. Current state: user gives a bounding box as a txt file.
• Processing: The tool then processes the video, tracking and isolating the selected subject in all subsequent frames.
• Output: The final output is a sequence of the selected subject rendered against a green screen, suitable for further video editing and composition.

Installation

git clone https://github.com/killian31/VideoBackgroundRemoval.git
cd VideoBackgroundRemoval
pip install -r requirements.txt --upgrade

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

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] [--output_dir OUTPUT_DIR] [--output_video OUTPUT_VIDEO]

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
  --output_dir OUTPUT_DIR
                        directory to store the output frames
  --output_video OUTPUT_VIDEO
                        path to store the output video

Example

The following command line is a working example from a video stored in the repo:

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

pip install black

Usage

To format your code:

black .

This setup will help maintain a consistent coding style throughout the project.