Masking Tools Save

open source background removal and masking tools useful for photogrammetry

Project README

Masking / Background removal

Image Eraser

Image Eraser allows users to perform image segmentation inside browser using a vector editor (FabricJS) and JS implementations of superpixel algorithms. https://github.com/AKSHAYUBHAT/ImageSegmentation

License: MIT Author: Akshay Bhat

Mask R-CNN

for object detection and instance segmentation on Keras and TensorFlow

This is an implementation of Mask R-CNN on Python 3, Keras, and TensorFlow. The model generates bounding boxes and segmentation masks for each instance of an object in the image. It's based on Feature Pyramid Network (FPN) and a ResNet101 backbone

https://github.com/matterport/Mask_RCNN

An edited version: https://colab.research.google.com/github/zaidalyafeai/Notebooks/blob/master/Mask_RCNN.ipynb#scrollTo=IIDafmcXSNns

License: MIT Author: Matterport, Inc.

image-background-remove-tool (cli/gui/python)

Tool for removing background from image using neural networks using U^2-net, BASNet & DeepLabV3

https://github.com/OPHoperHPO/image-background-remove-tool

backgroundremover (python/cli)

BackgroundRemover is a command line tool to remove background from video and image https://github.com/nadermx/backgroundremover

U-2-Net

https://github.com/NathanUA/U-2-Net

https://github.com/shreyas-bk/U-2-Net-Demo

https://github.com/dennisbappert/u-2-net-portrait

Rembg (python/cli)

Rembg is a tool to remove images background. https://github.com/danielgatis/rembg

Background Matting

https://github.com/senguptaumd/Background-Matting

MODNet

MODNet is a model for real-time portrait matting with only RGB image input. https://github.com/ZHKKKe/MODNet

Background Removal

You can deploy an API to remove background from an image. Such an API can be used in e-commerce, retail and fashion.

https://github.com/rorodata/background-removal

https://gitlab.com/fast-science/background-removal-server/tree/master/webapp/model

https://medium.com/@burgalon/deploying-your-keras-model-35648f9dc5fb

Demo: https://greenscreen-ai.boorgle.com/

License: "open source", unknown license Authors: The model is developed by Alon Burg and Gidi Shperber

Portrait Segmentation using Tensorflow

https://github.com/susheelsk/image-background-removal

Background subtraction using deep learning method.

https://github.com/SaoYan/bgsCNN

Background Removal based on U-Net

https://github.com/eti-p-doray/unet-gan-matting

Background-removal-using-deep-learning (introduction)

https://github.com/YunanWu2168/Background-removal-using-deep-learning

Background removal of an image using OpenCV and Deep Learning.

https://github.com/aadityavikram/Background-Removal

Simple Interactive Object Extraction

This is a Fiji plugin based on the SIOX project to segment color images. SIOX stands for Simple Interactive Object Extraction, a method for extracting foreground from still images with very little user interaction.

http://www.siox.org/

https://www.youtube.com/watch?v=A_FWoD82U_o

https://imagej.net/SIOX:_Simple_Interactive_Object_Extraction

https://github.com/fiji/SIOX_segmentation

License: Apache License/GNU GPL, for details read here Authors: Ignacio Arganda-Carreras & Contributors

G´MIC

The G’MIC plug-in for GIMP allows to interactively extract a foreground object present in a color image, from its background (considering a single-layered bitmap image as the input)

http://opensource.graphics/

http://opensource.graphics/how-to-code-a-nice-user-guided-foreground-extraction-algorithm/

http://opensource.graphics/how-to-code-a-nice-user-guided-foreground-extraction-algorithm-addendum/

http://opensource.graphics/category/algorithm/

https://www.youtube.com/watch?v=JfxTTU4yba8

http://opensource.graphics/tag/image-segmentation/

OpenCV

https://docs.opencv.org/3.4.3/d1/dc5/tutorial_background_subtraction.html

Interactive Foreground Extraction using GrabCut Algorithm

https://docs.opencv.org/trunk/d8/d83/tutorial_py_grabcut.html

https://codeloop.org/python-opencv-grabcut-foreground-detection/

OpenCV Implementation of the FASA (Fast, Accurate, and Size-Aware Salient Object Detection) algorithm

[code] [wiki] [example] Abstract/code

Text_Segmentation_Image_Inpainting

https://github.com/yu45020/Text_Segmentation_Image_Inpainting

DoubleDIP

https://github.com/yossigandelsman/DoubleDIP http://www.wisdom.weizmann.ac.il/~vision/DoubleDIP/index.html

Image Segmentation

https://hackernoon.com/releasing-supervisely-person-dataset-for-teaching-machines-to-segment-humans-1f1fc1f28469

https://github.com/facebookresearch/deepmask/blob/master/README.md https://code.fb.com/ml-applications/segmenting-and-refining-images-with-sharpmask/

https://courses.cs.washington.edu/courses/cse576/book/ch10.pdf

Interactive Image Segmentation with Latent Diversity http://vladlen.info/publications/interactive-image-segmentation-latent-diversity/ https://github.com/IntelVCL/Intseg

https://www.ilastik.org/

http://structuralsegm.sourceforge.net/

http://matthewalunbrown.com/segment/segment.html

http://www4.comp.polyu.edu.hk/~cslzhang/MSRM/PR_MSRM_website.htm

https://www.groundai.com/project/interactive-full-image-segmentation/

https://github.com/kozistr/Awesome-Segmentations

https://github.com/davidstutz/graph-based-image-segmentation

https://github.com/shrutisingala/opencv-Image-Segmentation

https://github.com/lim-anggun/FgSegNet

List of Interactive_Segmentation_Models

https://github.com/horvitzs/Interactive_Segmentation_Models

Segmentation_based_Semantic_Matting

https://github.com/Griffin98/Segmentation_based_Semantic_Matting

Open Source Agenda is not affiliated with "Masking Tools" Project. README Source: natowi/masking_tools

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