Python Image-matting Resources

crfill Usage | Web App | | Paper | Supplementary Material | More results | code for paper ``CR-Fill: Generative Image Inpainting with Auxiliary Contex

A Collection of Papers and Codes for ICCV2021 Low Level Vision and Image Generation

Image Completion Transformer (ICT) Project Page | Paper (ArXiv) | Pre-trained Models | Supplemental Material This repository is the official pytorch i

Documentation The documentation is available on populse_mia's website here Installation From PyPI, for users By cloning the package, for developers Fr

Cutout tools for astronomical images Astrocut provides tools for making cutouts from sets of astronomical images with shared footprints. It is under a

Pure Python implementation of the GIMP image formats (.xcf projects as well as brushes, patterns, etc)

A modern, web-based photo management server. Run it on your home server and it will let you find the right photo from your collection on any device. Smart filtering is made possible by object recognition, face recognition, location awareness, color analysis and other ML algorithms.

impy is All You Need in Image Analysis impy is an all-in-one image analysis library, equipped with parallel processing, GPU support, GUI based tools a

Kimimaro: Skeletonize Densely Labeled Images # Produce SWC files from volumetric images. kimimaro forge labels.npy --progress # writes to ./kimimaro_o

Vignette Vignette is a Python library to create and manage thumbnails following the FreeDesktop standard. Thumbnails are stored in a shared directory

The ScreenTeX project By: Seanpm2001 / ScreenTeX, Et; Al. Top README.md Read this article in a different language 🌐 List of languages Sorted by: A-Z

An Image Captioning codebase This is a codebase for image captioning research. It supports: Self critical training from Self-critical Sequence Trainin

img2texture Command line utility for converting images to seamless tiles. The resulting tiles can be used as textures in games, compositing and 3D mod

A Multi-attribute Controllable Generative Model for Histopathology Image Synthesis This is the pytorch implementation for our MICCAI 2021 paper. A Mul

MODEL SUMMARY 모델의 구조는 크게 6단계로 나뉩니다. STEP 0: Input Image Predict 할 이미지를 모델에 입력합니다. STEP 1: Make Black and White Image STEP 1 은 입력받은 이미지의 글자를 흑색으로, 배경을

Self-Attention Context Network for Hyperspectral Image Classification PyTorch implementation of our method for adversarial attacks and defenses in hyp

Diverse Image Inpainting with Bidirectional and Autoregressive Transformers Installation pip install -r requirements.txt Dataset Preparation Given the

Vision Transformer Pytorch reimplementation of Google's repository for the ViT model that was released with the paper An Image is Worth 16x16 Words: T

Automatic Image Background Subtraction This repo contains set of scripts for automatic one-shot image background subtraction task using the following

Pytorch Implementation of Deep Orthogonal Fusion of Local and Global Features (DOLG) This is the unofficial PyTorch Implementation of "DOLG: Single-St

push-container-image-to-docker-registry 概要 push-container-image-to-docker-registry は、エッジコンピューティング環境において、特定のエッジ端末上の Private Docker Registry に特定のコンテナイメー

Install Library pypi $ pip3 install xremovebg

A Jupyter notebook to play with NVIDIA's StyleGAN3 and OpenAI's CLIP for a text-based guided image generation.

Semi-Supervised Graph Prototypical Networks for Hyperspectral Image Classification, IGARSS, 2021. Bobo Xi, Jiaojiao Li, Yunsong Li and Qian Du. Code f

Image Optimization Using Python steps to run the script run the command to install the required libraries pip install -r requirements.txt create a dir

rscolorq Rust port of Derrick Coetzee's scolorq, based on the 1998 paper "On spatial quantization of color images" by Jan Puzicha, Markus Held, Jens K

ANTsPyNet A collection of deep learning architectures and applications ported to the python language and tools for basic medical image processing. Bas

MONAI Deploy App SDK offers a framework and associated tools to design, develop and verify AI-driven applications in the healthcare imaging domain.

Unsupervised Image Generation with Infinite Generative Adversarial Networks Here is the implementation of MICGANs using DCGAN architecture on MNIST da

HCaptcha solver using requests and an image recognition package! Report Bug · Request Feature Features Image recognition Requests base

A collection of papers about Transformer in the field of medical image analysis.

unfoldedVBA Unrolled Variational Bayesian Algorithm for Image Blind Deconvolution This repository contains the Pytorch implementation of the unrolled

Semi-supervised Transfer Learning for Image Rain Removal This package contains the Python implementation of "Semi-supervised Transfer Learning for Ima

Feedback Network for Image Super-Resolution [arXiv] [CVF] [Poster] Update: Our proposed Gated Multiple Feedback Network (GMFN) will appear in BMVC2019

Progressive Image Deraining Networks: A Better and Simpler Baseline [arxiv] [pdf] [supp] Introduction This paper provides a better and simpler baselin

SRNTT: Image Super-Resolution by Neural Texture Transfer Tensorflow implementation of the paper Image Super-Resolution by Neural Texture Transfer acce

Gated Multiple Feedback Network for Image Super-Resolution This repository contains the PyTorch implementation for the proposed GMFN [arXiv]. The fram

About PyTorch 1.2.0 Now the master branch supports PyTorch 1.2.0 by default. Due to the serious version problem (especially torch.utils.data.dataloade

IGNN Code repo for "Cross-Scale Internal Graph Neural Network for Image Super-Resolution" [paper] [supp] Prepare datasets 1 Download training dataset

##Dependencies pillow(~2.6.0) Numpy(~1.9.0) If the scripts throw AttributeError: __float__, make sure your pillow has jpeg support e.g. try: $ sudo ap

DID-MDN Density-aware Single Image De-raining using a Multi-stream Dense Network He Zhang, Vishal M. Patel [Paper Link] (CVPR'18) We present a novel d

Spatial Attentive Single-Image Deraining with a High Quality Real Rain Dataset (CVPR'19) Tianyu Wang*, Xin Yang*, Ke Xu, Shaozhe Chen, Qiang Zhang, Ry

Second-order Attention Network for Single Image Super-resolution (CVPR-2019) "Second-order Attention Network for Single Image Super-resolution" is pub

Residual Dense Network for Image Super-Resolution This repository is for RDN introduced in the following paper Yulun Zhang, Yapeng Tian, Yu Kong, Bine

Multi-Scale Progressive Fusion Network for Single Image Deraining (MSPFN) This is an implementation of the MSPFN model proposed in the paper (Multi-Sc

Single Image Deraining Using Bilateral Recurrent Network Introduction Single image deraining has received considerable progress based on deep convolut

DFN：Distributed Feedback Network for Single-Image Deraining Abstract Recently, deep convolutional neural networks have achieved great success for sing

pycls pycls is an image classification codebase, written in PyTorch. It was originally developed for the On Network Design Spaces for Visual Recogniti

PointRend A PyTorch implementation of PointRend: Image Segmentation as Rendering [arxiv] [Official Implementation: Detectron2] This repo for Only Sema

Unet network with mean teacher for altrasound image segmentation

Image Colorization API Machine Learning Model used- https://github.com/richzhang/colorization/tree/caffe Paper - https://arxiv.org/abs/1603.08511 Step

clip-search (WIP) A simple tool for searching images inside a local folder with text/image input using CLIP 10 results for "a blonde woman" in a folde

DeCLIP Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm. Our paper is available in arxiv Updates ** Ou

Video Scene Cut Detection and Analysis Tool Latest Release: v0.5.6.1 (October 11, 2021) Main Webpage: py.scenedetect.com Documentation: manual.scenede

Collection of Docker images for ML/DL and video processing projects. Overview of images Three types of images differ by tag postfix: base: Python with

image2excel A program which converts images and video into Excel spreadsheets. Usage examples can be found in examples Videos can take a long time to

Face-Mask-Detection Face Mask Detection on Image and Video using tensorflow and keras Train Neural Network on face-mask dataset using tensorflow and k

PyPhotoshop Python implementation of image filters Use Python to adjust brightness and contrast, add blur, and detect edges! Follow along tutorial: ht

PyTransKit Python Transport Based Signal Processing Toolkit Website and documentation: https://pytranskit.readthedocs.io/ Installation The library cou

This is a repository for the paper of "Well-classified Examples are Underestimated in Classification with Deep Neural Networks" The implementation and

DSN-IQA Source code for paper "Deep Superpixel-based Network for Blind Image Quality Assessment" Requirements Python =3.8.0 Pytorch =1.7.1 Usage wit

Breaking the Dilemma of Medical Image-to-image Translation Supervised Pix2Pix and unsupervised Cycle-consistency are two modes that dominate the field

Fast Fourier Convolution (FFC) for Image Classification This is the official code of Fast Fourier Convolution for image classification on ImageNet. Ma

Breaking the Dilemma of Medical Image-to-image Translation Supervised Pix2Pix and unsupervised Cycle-consistency are two modes that dominate the field

======================================== Paper-Question-recognition ======================================== question‘s area recognition using image p

DSN-IQA Source code for paper "Deep Superpixel-based Network for Blind Image Quality Assessment" Requirements Python =3.8.0 Pytorch =1.7.1 Usage wit

MMSceneGraph Introduction MMSceneneGraph is an open source code hub for scene graph generation as well as supporting downstream tasks based on the sce

SlideGraph+: Whole Slide Image Level Graphs to Predict HER2 Status in Breast Cancer A novel graph neural network (GNN) based model (termed SlideGraph+

TGImageHosting This is a simple bot that can be used to upload images to a third party cloud (image hosting). Currently, only the imgbb.com website su

GAN-image-detection This repository contains a GAN-generated image detector developed to distinguish real images from synthetic ones. The detector is

I'm Listening to This (song that I've sent you an image about detailing its metadata in a nifty way) Few lines describing your project. 📝 Table of Co

Generates a random prnt.sc link and display image.

OCR-Tool It is a image ocr tool made in Python using the Tesseract-OCR engine with the pytesseract package and has a GUI. This is my second ever pytho

TorchOk - The toolkit for fast Deep Learning experiments in Computer Vision

Simple image captioning model - CLIP prefix captioning.

[ICCV'2021] Image Inpainting via Conditional Texture and Structure Dual Generation

Simple PoC script that allows you to exploit telegram's "send with timer" feature by saving any media sent with this functionality.

Surgically remove layers from a Docker image (with a chainsaw)

Image Detector and Convertor App created using python's Pillow, OpenCV, cvlib, numpy and streamlit packages.

Room Formatter This tool allows the user to convert a 16 by 16 image into a list with numbers representing an object/character. There is cur

NanoImgPro Nanosensor Image Processor (NanoImgPro), a python-based image analysis tool for dopamine nanosensors NanoImgPro.py contains the main class

Instance-level Image Retrieval using Reranking Transformers Fuwen Tan, Jiangbo Yuan, Vicente Ordonez, ICCV 2021. Abstract Instance-level image retriev

MeshGraphormer ✨ ✨ This is our research code of Mesh Graphormer. Mesh Graphormer is a new transformer-based method for human pose and mesh reconsructi

TRREASURE_IMAGE TRREASURE_IMAGE is a python third-party library with Command-Line Interface[cli] feature. Table of Contents General Info Python librar

CMIC-Retrieval Code for Single Image 3D Shape Retrieval via Cross-Modal Instance and Category Contrastive Learning. ICCV 2021. Introduction In this wo

AutoRiddleMaster Automatically resolve RidderMaster based on TensorFlow & OpenCV 基于 TensorFlow 和 OpenCV 实现的全自动化解御迷士小马谜题 Demo How to use Deploy the ser

Background_Changer Table of Contents: About the Program Features Requirements Preview Credits Reach Me See Also About the Program: You can change your

GRAF This repository contains official code for the paper GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis. You can find detailed usage i

IBRNet: Learning Multi-View Image-Based Rendering PyTorch implementation of paper "IBRNet: Learning Multi-View Image-Based Rendering", CVPR 2021. IBRN

Blue noise image stippling in Processing (requires GPU)

Python Image Morpher (PIM) is a program that can take two images and blend them to whatever extent or precision that you like! It is designed to emulate some of Python's OpenCV image processing from scratch without reference.

A 3D multi-modal medical image segmentation library in PyTorch We strongly believe in open and reproducible deep learning research. Our goal is to imp

Social Distance Detector A Real-Time Social Distance Monitoring Tool Table of Contents Motivation YOLO Theory Detection Output Tech Stack Functionalit

Transfer-Learn is an open-source and well-documented library for Transfer Learning. It is based on pure PyTorch with high performance and friendly API. Our code is pythonic, and the design is consistent with torchvision. You can easily develop new algorithms, or readily apply existing algorithms.

Towards Flexible Blind JPEG Artifacts Removal (FBCNN, ICCV 2021) Jiaxi Jiang, Kai Zhang, Radu Timofte Computer Vision Lab, ETH Zurich, Switzerland 🔥

imgp is a command line image resizer and rotator for JPEG and PNG images.

Uformer: A General U-Shaped Transformer for Image Restoration Zhendong Wang, Xiaodong Cun, Jianmin Bao and Jianzhuang Liu Paper: https://arxiv.org/abs

GANimation: Anatomically-aware Facial Animation from a Single Image [Project] [Paper] Official implementation of GANimation. In this work we introduce

Differentiable Architecture Search Code accompanying the paper DARTS: Differentiable Architecture Search Hanxiao Liu, Karen Simonyan, Yiming Yang. arX

Imbalanced Dataset Sampler Introduction In many machine learning applications, we often come across datasets where some types of data may be seen more