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.

You might also like...
Implementation of Common Image Evaluation Metrics by Sayed Nadim (sayednadim.github.io). The repo is built based on full reference image quality metrics such as L1, L2, PSNR, SSIM, LPIPS. and feature-level quality metrics such as FID, IS. It can be used for evaluating image denoising, colorization, inpainting, deraining, dehazing etc. where we have access to ground truth.

Image Quality Evaluation Metrics Implementation of some common full reference image quality metrics. The repo is built based on full reference image q

Sayed Nadim 10 Jan 1, 2023
This repository contains several image-to-image translation models, whcih were tested for RGB to NIR image generation. The models are Pix2Pix, Pix2PixHD, CycleGAN and PointWise.

RGB2NIR_Experimental This repository contains several image-to-image translation models, whcih were tested for RGB to NIR image generation. The models

null 5 Jan 4, 2023
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

H2O H2O is an in-memory platform for distributed, scalable machine learning. H2O uses familiar interfaces like R, Python, Scala, Java, JSON and the Fl

H2O.ai 6.1k Jan 5, 2023
⚾🤖⚾ Automatic baseball pitching overlay in realtime
⚾🤖⚾ Automatic baseball pitching overlay in realtime

⚾ Automatically overlaying pitch motion and trajectory with machine learning! This project takes your baseball pitching clips and automatically genera

Tony Chou 240 Dec 5, 2022
DNA-RECON { Automatic Web Reconnaissance Tool }
DNA-RECON { Automatic Web Reconnaissance Tool }

ABOUT TOOL : DNA-RECON is an automatic web reconnaissance tool written in python. This tool made for reconnaissance and information gathering with an

NIKUNJ BHATT 25 Aug 11, 2021
Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT
Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT

CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT CheXbert is an accurate, automated dee

Stanford Machine Learning Group 51 Dec 8, 2022
PyTorch Lightning implementation of Automatic Speech Recognition

lasr Lightening Automatic Speech Recognition An MIT License ASR research library, built on PyTorch-Lightning, for developing end-to-end ASR models. In

Soohwan Kim 40 Sep 19, 2022
automatic color-grading
automatic color-grading

color-matcher Description color-matcher enables color transfer across images which comes in handy for automatic color-grading of photographs, painting

hahnec 168 Jan 5, 2023
Scale-aware Automatic Augmentation for Object Detection (CVPR 2021)
Scale-aware Automatic Augmentation for Object Detection (CVPR 2021)

SA-AutoAug Scale-aware Automatic Augmentation for Object Detection Yukang Chen, Yanwei Li, Tao Kong, Lu Qi, Ruihang Chu, Lei Li, Jiaya Jia [Paper] [Bi

DV Lab 182 Dec 29, 2022
Owner
Oleg Sémery
Mathematician
Oleg Sémery
GitHub Repository
Where-Got-Time - An NUS timetable generator which uses a genetic algorithm to optimise timetables to suit the needs of NUS students

Where Got Time(table)? A timetable optimsier which uses an evolutionary algorith

Nicholas Lee 3 Jan 09, 2022
Convolutional Neural Networks

Darknet Darknet is an open source neural network framework written in C and CUDA. It is fast, easy to install, and supports CPU and GPU computation. D

Joseph Redmon 23.7k Jan 05, 2023
A simple PyTorch Implementation of Generative Adversarial Networks, focusing on anime face drawing.

AnimeGAN A simple PyTorch Implementation of Generative Adversarial Networks, focusing on anime face drawing. Randomly Generated Images The images are

Jie Lei 雷杰 1.2k Jan 03, 2023
Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience

Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience This repository is the official implementation of [https://www.bi

Eulerlab 6 Oct 09, 2022
Python package for Bayesian Machine Learning with scikit-learn API

Python package for Bayesian Machine Learning with scikit-learn API Installing & Upgrading package pip install https://github.com/AmazaspShumik/sklearn

Amazasp Shaumyan 482 Jan 04, 2023
Quantile Regression DQN a Minimal Working Example, Distributional Reinforcement Learning with Quantile Regression

Quantile Regression DQN Quantile Regression DQN a Minimal Working Example, Distributional Reinforcement Learning with Quantile Regression (https://arx

Arsenii Senya Ashukha 80 Sep 17, 2022
Text-Based Ideal Points

Text-Based Ideal Points Source code for the paper: Text-Based Ideal Points by Keyon Vafa, Suresh Naidu, and David Blei (ACL 2020). Update (June 29, 20

Keyon Vafa 37 Oct 09, 2022
NeuroLKH: Combining Deep Learning Model with Lin-Kernighan-Helsgaun Heuristic for Solving the Traveling Salesman Problem

NeuroLKH: Combining Deep Learning Model with Lin-Kernighan-Helsgaun Heuristic for Solving the Traveling Salesman Problem Liang Xin, Wen Song, Zhiguang

xinliangedu 33 Dec 27, 2022
Nvidia Semantic Segmentation monorepo

Paper | YouTube | Cityscapes Score Pytorch implementation of our paper Hierarchical Multi-Scale Attention for Semantic Segmentation. Please refer to t

NVIDIA Corporation 1.6k Jan 04, 2023
Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers [CVPR 2021]

Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers [BCNet, CVPR 2021] This is the official pytorch implementation of BCNet built on

Lei Ke 434 Dec 01, 2022
Replication Package for AequeVox:Automated Fariness Testing for Speech Recognition Systems

AequeVox Replication Package for AequeVox:Automated Fariness Testing for Speech Recognition Systems README under development. Python Packages Required

Sai Sathiesh 2 Aug 28, 2022
This repository gives an example on how to preprocess the data of the HECKTOR challenge

HECKTOR 2021 challenge This repository gives an example on how to preprocess the data of the HECKTOR challenge. Any other preprocessing is welcomed an

56 Dec 01, 2022
Official implementation for “Unsupervised Low-Light Image Enhancement via Histogram Equalization Prior”

HEP Unsupervised Low-Light Image Enhancement via Histogram Equalization Prior Implementation Python3 PyTorch=1.0 NVIDIA GPU+CUDA Training process The

FengZhang 34 Dec 04, 2022
A voice recognition assistant similar to amazon alexa, siri and google assistant.

kenyan-Siri Build an Artificial Assistant Full tutorial (video) To watch the tutorial, click on the image below Installation For windows users (run th

Alison Parker 3 Aug 19, 2022
phylotorch-bito is a package providing an interface to BITO for phylotorch

phylotorch-bito phylotorch-bito is a package providing an interface to BITO for phylotorch Dependencies phylotorch BITO Installation Get the source co

Mathieu Fourment 2 Sep 01, 2022
Official implementation of the network presented in the paper "M4Depth: A motion-based approach for monocular depth estimation on video sequences"

M4Depth This is the reference TensorFlow implementation for training and testing depth estimation models using the method described in M4Depth: A moti

Michaël Fonder 76 Jan 03, 2023
Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition

Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition How Fast Compare to Other Zero-Shot NAS Proxies on CIFAR-10/100 Pre-trained Model

190 Dec 29, 2022
PyTorch implementation for our paper "Deep Facial Synthesis: A New Challenge"

FSGAN Here is the official PyTorch implementation for our paper "Deep Facial Synthesis: A New Challenge". This project achieve the translation between

Deng-Ping Fan 32 Oct 10, 2022
Official repository of the AAAI'2022 paper "Contrast and Generation Make BART a Good Dialogue Emotion Recognizer"

CoG-BART Contrast and Generation Make BART a Good Dialogue Emotion Recognizer Quick Start: To run the model on test sets of four datasets, Download th

39 Dec 24, 2022
Style transfer, deep learning, feature transform

FastPhotoStyle License Copyright (C) 2018 NVIDIA Corporation. All rights reserved. Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons

NVIDIA Corporation 10.9k Jan 02, 2023