Automatic Image Background Subtraction

Related tags

Deep Learningbackground-subtraction
Overview

Automatic Image Background Subtraction

GitHub License Python Version

This repo contains set of scripts for automatic one-shot image background subtraction task using the following strategies:

  1. the appropriate background subtraction services (mostly human based):
  1. U-Net human segmentation net + CascadePSP refinement net:
  2. BackgroundMattingV2 net.

Installation

git clone https://github.com/osmr/bgsub.git
cd bgsub
pip install -r requirements.txt

Usage

  1. Launch a script for background subtraction via benzin.io/remove.bg service:
python subtract_bg_service.py --service=<service> --token=<your token> --input=<directory with images> --output=<output directory with binary masks>

Here:

  • service is benzinio for benzin.io service or removebg for remove.bg,
  • token is a service API token value, which you will receive after registering on the selected service,
  • input is a directory with processing JPEG images (can contain subdirectories),
  • output is a directory with resulted PNG binary masks (it is assumed that all original images had unique names).

Optional parameters:

  • middle is a directory with intermediate images with original masks obtained from the service (PNG with alpha mask),
  • ppdir is a flag for adding extra parrent+parrent directory to the output one (should use as --ppdir).
  • threshold is a threshold for mask binarization (default value is 127),
  • url is an optional custom URL for service,
  • jpg is a flag for forced recompression an input image as JPG (should use as --jpg),
  • not-resize is a flag for suppressing forcible scale the mask to the input image (should use as --not-resize).
  1. Launch a script for background subtraction via human segmentation network:
python subtract_bg_human.py --input=<directory with images> --output=<output directory with binary masks>

Here:

  • input is a directory with processing JPEG images (can contain subdirectories),
  • output is a directory with resulted PNG binary masks (it is assumed that all original images had unique names).

Optional parameters:

  • ppdir is a flag for adding extra parrent+parrent directory to the output one (should use as --ppdir).
  • use-cuda is a flag for using CUDA for network inference (should use as --use-cuda).
  1. Launch a script for background subtraction via matting network:
python subtract_bg_matting.py --input=<directory with images> --bg=<background image path> --output=<output directory with binary masks>

Here:

  • input is a directory with processing JPEG images (can contain subdirectories),
  • bg is a background image file path,
  • output is a directory with resulted PNG binary masks (it is assumed that all original images had unique names).

Optional parameters:

  • threshold is a threshold for mask binarization (default value is 127),
  • ppdir is a flag for adding extra parrent+parrent directory to the output one (should use as --ppdir).
  • use-cuda is a flag for using CUDA for network inference (should use as --use-cuda).

Remark

The script does not recalculate the masks if the target images already exist.

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