1763 Repositories
Python image-effects Libraries
Advance Image Steganography
Chaya Advance Image Steganography Using LSB-LPS + AES-256-GCM + FLIF Right To Privacy! United Nations Declaration of Human Rights (UDHR) 1948, Article
This script runs neural style transfer against the provided content image.
Neural Style Transfer Content Style Output Description: This script runs neural style transfer against the provided content image. The content image m
A denoising autoencoder + adversarial losses and attention mechanisms for face swapping.
faceswap-GAN Adding Adversarial loss and perceptual loss (VGGface) to deepfakes'(reddit user) auto-encoder architecture. Updates Date Update 2018-08-2
Converts given image (png, jpg, etc) to amogus gif.
Image to Amogus Converter Converts given image (.png, .jpg, etc) to an amogus gif! Usage Place image in the /target/ folder (or anywhere realistically
MRQy is a quality assurance and checking tool for quantitative assessment of magnetic resonance imaging (MRI) data.
Front-end View Backend View Table of Contents Description Prerequisites Running Basic Information Measurements User Interface Feedback and usage Descr
Image and video quality assessment
CenseoQoE: 视觉感知画质评价框架 项目介绍 图像/视频在编解码、传输和显示等过程中难免引入不同类型/程度的失真导致图像质量下降。图像/视频质量评价(IVQA)的研究目标是希望模仿人类视觉感知系统, 通过算法评估图片/视频在终端用户的眼中画质主观体验的好坏,目前在视频编解码、画质增强、画质监。
This is an official implementation for "SimMIM: A Simple Framework for Masked Image Modeling".
Project This repo has been populated by an initial template to help get you started. Please make sure to update the content to build a great experienc
A Linux program to create a Windows USB stick installer from a real Windows DVD or image.
WoeUSB-ng A Linux program to create a Windows USB stick installer from a real Windows DVD or image. This package contains two programs: woeusb: A comm
A not exist cat image generator python package
A not exist cat image generator python package
You Can download any video/image in all social medias very easy and High Speed.
All-Downloader You Can download any video/image in all social medias very easy and High Speed. also you can easily download videos from web browsers s
Reference PyTorch implementation of "End-to-end optimized image compression with competition of prior distributions"
PyTorch reference implementation of "End-to-end optimized image compression with competition of prior distributions" by Benoit Brummer and Christophe
Pytorch implementation of the paper: "SAPNet: Segmentation-Aware Progressive Network for Perceptual Contrastive Image Deraining"
SAPNet This repository contains the official Pytorch implementation of the paper: "SAPNet: Segmentation-Aware Progressive Network for Perceptual Contr
This is an official implementation for "SimMIM: A Simple Framework for Masked Image Modeling".
Project This repo has been populated by an initial template to help get you started. Please make sure to update the content to build a great experienc
Official repository for "Restormer: Efficient Transformer for High-Resolution Image Restoration". SOTA results for single-image motion deblurring, image deraining, image denoising (synthetic and real data), and dual-pixel defocus deblurring.
Restormer: Efficient Transformer for High-Resolution Image Restoration Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan,
Simple image captioning model
CLIP prefix captioning. Inference Notebook: 🥳 New: 🥳 Our technical papar is finally out! Official implementation for the paper "ClipCap: CLIP Prefix
A very simple baseline to estimate 2D & 3D SMPL-compatible keypoints from a single color image.
Minimal Body A very simple baseline to estimate 2D & 3D SMPL-compatible keypoints from a single color image. The model file is only 51.2 MB and runs a
Official PyTorch implementation of "BlendGAN: Implicitly GAN Blending for Arbitrary Stylized Face Generation" (NeurIPS 2021)
BlendGAN: Implicitly GAN Blending for Arbitrary Stylized Face Generation Official PyTorch implementation of the NeurIPS 2021 paper Mingcong Liu, Qiang
Contrastive Feature Loss for Image Prediction
Contrastive Feature Loss for Image Prediction We provide a PyTorch implementation of our contrastive feature loss presented in: Contrastive Feature Lo
The codes and related files to reproduce the results for Image Similarity Challenge Track 1.
ISC-Track1-Submission The codes and related files to reproduce the results for Image Similarity Challenge Track 1. Required dependencies To begin with
Official implementation of UTNet: A Hybrid Transformer Architecture for Medical Image Segmentation
UTNet (Accepted at MICCAI 2021) Official implementation of UTNet: A Hybrid Transformer Architecture for Medical Image Segmentation Introduction Transf
Lightweight Face Image Quality Assessment
LightQNet This is a demo code of training and testing [LightQNet] using Tensorflow. Uncertainty Losses: IDQ loss PCNet loss Uncertainty Networks: Mobi
A transformer-based method for Healthcare Image Captioning in Vietnamese
vieCap4H Challenge 2021: A transformer-based method for Healthcare Image Captioning in Vietnamese This repo GitHub contains our solution for vieCap4H
Clip Bing Maps backgound as RGB geotif image using center-point from vector data of a shapefile and Bing Maps zoom
Clip Bing Maps backgound as RGB geotif image using center-point from vector data of a shapefile and Bing Maps zoom. Also, rasterize shapefile vectors as corresponding label image.
Configure request params such as text, color, size etc. And then download the image
Configure request params such as text, color, size etc. And then download the image
natural image generation using ConvNets
The Eyescream Project Generating Natural Images using Neural Networks. For our research summary on this work, please read the Arxiv paper: http://arxi
GeneGAN: Learning Object Transfiguration and Attribute Subspace from Unpaired Data
GeneGAN: Learning Object Transfiguration and Attribute Subspace from Unpaired Data By Shuchang Zhou, Taihong Xiao, Yi Yang, Dieqiao Feng, Qinyao He, W
Learning infinite-resolution image processing with GAN and RL from unpaired image datasets, using a differentiable photo editing model.
Exposure: A White-Box Photo Post-Processing Framework ACM Transactions on Graphics (presented at SIGGRAPH 2018) Yuanming Hu1,2, Hao He1,2, Chenxi Xu1,
PyTorch implementation for ComboGAN
ComboGAN This is our ongoing PyTorch implementation for ComboGAN. Code was written by Asha Anoosheh (built upon CycleGAN) [ComboGAN Paper] If you use
Toward Multimodal Image-to-Image Translation
BicycleGAN Project Page | Paper | Video Pytorch implementation for multimodal image-to-image translation. For example, given the same night image, our
Pytorch implementation AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
AttnGAN Pytorch implementation for reproducing AttnGAN results in the paper AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative
Official repository for ABC-GAN
ABC-GAN The work represented in this repository is the result of a 14 week semesterthesis on photo-realistic image generation using generative adversa
Single/multi view image(s) to voxel reconstruction using a recurrent neural network
3D-R2N2: 3D Recurrent Reconstruction Neural Network This repository contains the source codes for the paper Choy et al., 3D-R2N2: A Unified Approach f
Randomized Correspondence Algorithm for Structural Image Editing
===================================== README: Inpainting based PatchMatch ===================================== @Author: Younesse ANDAM @Conta
Official Chainer implementation of GP-GAN: Towards Realistic High-Resolution Image Blending (ACMMM 2019, oral)
GP-GAN: Towards Realistic High-Resolution Image Blending (ACMMM 2019, oral) [Project] [Paper] [Demo] [Related Work: A2RL (for Auto Image Cropping)] [C
Torch Implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"
Photo-Realistic-Super-Resoluton Torch Implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network" [Paper]
Image super-resolution through deep learning
srez Image super-resolution through deep learning. This project uses deep learning to upscale 16x16 images by a 4x factor. The resulting 64x64 images
Image Completion with Deep Learning in TensorFlow
Image Completion with Deep Learning in TensorFlow See my blog post for more details and usage instructions. This repository implements Raymond Yeh and
[CVPR 2016] Unsupervised Feature Learning by Image Inpainting using GANs
Context Encoders: Feature Learning by Inpainting CVPR 2016 [Project Website] [Imagenet Results] Sample results on held-out images: This is the trainin
Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
CycleGAN PyTorch | project page | paper Torch implementation for learning an image-to-image translation (i.e. pix2pix) without input-output pairs, for
Image-to-image translation with conditional adversarial nets
pix2pix Project | Arxiv | PyTorch Torch implementation for learning a mapping from input images to output images, for example: Image-to-Image Translat
Image De-raining Using a Conditional Generative Adversarial Network
Image De-raining Using a Conditional Generative Adversarial Network [Paper Link] [Project Page] He Zhang, Vishwanath Sindagi, Vishal M. Patel In this
Invertible conditional GANs for image editing
Invertible Conditional GANs This is the implementation of the IcGAN model proposed in our paper: Invertible Conditional GANs for image editing. Novemb
Generative Adversarial Text-to-Image Synthesis
###Generative Adversarial Text-to-Image Synthesis Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, Honglak Lee This is the
Text to image synthesis using thought vectors
Text To Image Synthesis Using Thought Vectors This is an experimental tensorflow implementation of synthesizing images from captions using Skip Though
StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks
StackGAN Pytorch implementation Inception score evaluation StackGAN-v2-pytorch Tensorflow implementation for reproducing main results in the paper Sta
Interactive Image Generation via Generative Adversarial Networks
iGAN: Interactive Image Generation via Generative Adversarial Networks Project | Youtube | Paper Recent projects: [pix2pix]: Torch implementation for
[SIGGRAPH Asia 2019] Artistic Glyph Image Synthesis via One-Stage Few-Shot Learning
AGIS-Net Introduction This is the official PyTorch implementation of the Artistic Glyph Image Synthesis via One-Stage Few-Shot Learning. paper | suppl
This piece of code is a User Welcomer with Image Manipulation using Python and Pillow (PIL).
This piece of code is a User Welcomer with Image Manipulation using Python and Pillow (PIL).
Powerful and efficient Computer Vision Annotation Tool (CVAT)
Computer Vision Annotation Tool (CVAT) CVAT is free, online, interactive video and image annotation tool for computer vision. It is being used by our
Semantic Image Synthesis with SPADE
Semantic Image Synthesis with SPADE New implementation available at imaginaire repository We have a reimplementation of the SPADE method that is more
🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
Image Super-Resolution (ISR) The goal of this project is to upscale and improve the quality of low resolution images. This project contains Keras impl
Convert a DOS Punk image to text
DOS Punk Text Inspired by MAX CAPACITY's DOS Punks & the amazing DOS Punk community. DOS Punk Text is a Python 3 script that renders a DOS Punk image
cisip-FIRe - Fast Image Retrieval
Fast Image Retrieval (FIRe) is an open source image retrieval project release by Center of Image and Signal Processing Lab (CISiP Lab), Universiti Malaya. This project implements most of the major binary hashing methods to date, together with different popular backbone networks and public datasets.
Code of Classification Saliency-Based Rule for Visible and Infrared Image Fusion
CSF Code of Classification Saliency-Based Rule for Visible and Infrared Image Fusion Tips: For testing: CUDA_VISIBLE_DEVICES=0 python main.py For trai
Official implementation for "Image Quality Assessment using Contrastive Learning"
Image Quality Assessment using Contrastive Learning Pavan C. Madhusudana, Neil Birkbeck, Yilin Wang, Balu Adsumilli and Alan C. Bovik This is the offi
Frequency Domain Image Translation: More Photo-realistic, Better Identity-preserving
Frequency Domain Image Translation: More Photo-realistic, Better Identity-preserving This is the source code for our paper Frequency Domain Image Tran
Semi-supervised Representation Learning for Remote Sensing Image Classification Based on Generative Adversarial Networks
SSRL-for-image-classification Semi-supervised Representation Learning for Remote Sensing Image Classification Based on Generative Adversarial Networks
Fast Image Retrieval (FIRe) is an open source image retrieval project
Fast Image Retrieval (FIRe) is an open source image retrieval project release by Center of Image and Signal Processing Lab (CISiP Lab), Universiti Malaya. This project implements most of the major binary hashing methods to date, together with different popular backbone networks and public datasets.
Single-stage Keypoint-based Category-level Object Pose Estimation from an RGB Image
CenterPose Overview This repository is the official implementation of the paper "Single-stage Keypoint-based Category-level Object Pose Estimation fro
Pnuemonia Normal detection by using XRay images.
Pnuemonia Normal detection by using XRay images. Got image datas from kaggle(link is given in sources.txt file) also normal xray images from other site (also link is given) in order to avoid data disbalancing.
[NeurIPS 2021] Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data
Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data (NeurIPS 2021) This repository will provide the official PyTorch implementa
The codes and related files to reproduce the results for Image Similarity Challenge Track 2.
ISC-Track2-Submission The codes and related files to reproduce the results for Image Similarity Challenge Track 2. Required dependencies To begin with
The codes and related files to reproduce the results for Image Similarity Challenge Track 1.
ISC-Track1-Submission The codes and related files to reproduce the results for Image Similarity Challenge Track 1. Required dependencies To begin with
Large-scale Hyperspectral Image Clustering Using Contrastive Learning, CIKM 21 Workshop
Spectral-spatial contrastive clustering (SSCC) Yaoming Cai, Yan Liu, Zijia Zhang, Zhihua Cai, and Xiaobo Liu, Large-scale Hyperspectral Image Clusteri
A simple Python script to convert multiple images (well technically also a single image) into a pdf.
PythonImage2PDF A simple Python script to convert multiple images into a single PDF-document. Created basically for only my own needs for converting m
imgAnalyser - Un script pour obtenir la liste des pixels d'une image correspondant à plusieurs couleurs
imgAnalyser - Un script pour obtenir la liste des pixels d'une image correspondant à plusieurs couleurs Ce script à pour but, à partir d'une image, de
Image processing using OpenCv
Image processing using OpenCv Write a program that opens the webcam, and the user selects one of the following on the video: ✅ If the user presses the
Fast Image Retrieval is an open source image retrieval framework
Fast Image Retrieval is an open source image retrieval framework release by Center of Image and Signal Processing Lab (CISiP Lab), Universiti Malaya. This framework implements most of the major binary hashing methods, together with both popular backbone networks and public datasets.
A Gtk based Image Selector with Preview
gtk-image-selector This is an attempt to restore Gtk Image Chooser "lost functionality": displaying an image preview when selecting images... This is
Spectralformer: Rethinking hyperspectral image classification with transformers
The code in this toolbox implements the "Spectralformer: Rethinking hyperspectral image classification with transformers". More specifically, it is detailed as follow.
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
DoWhy | An end-to-end library for causal inference Amit Sharma, Emre Kiciman Introducing DoWhy and the 4 steps of causal inference | Microsoft Researc
PyTorch implementation of UNet++ (Nested U-Net).
PyTorch implementation of UNet++ (Nested U-Net) This repository contains code for a image segmentation model based on UNet++: A Nested U-Net Architect
Code for our paper "Multi-scale Guided Attention for Medical Image Segmentation"
Medical Image Segmentation with Guided Attention This repository contains the code of our paper: "'Multi-scale self-guided attention for medical image
Implementation for paper LadderNet: Multi-path networks based on U-Net for medical image segmentation
Implementation for paper LadderNet: Multi-path networks based on U-Net for medical image segmentation This implementation is based on orobix implement
Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation
Attention Gated Networks (Image Classification & Segmentation) Pytorch implementation of attention gates used in U-Net and VGG-16 models. The framewor
Full Resolution Residual Networks for Semantic Image Segmentation
Full-Resolution Residual Networks (FRRN) This repository contains code to train and qualitatively evaluate Full-Resolution Residual Networks (FRRNs) a
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
Multipath RefineNet A MATLAB based framework for semantic image segmentation and general dense prediction tasks on images. This is the source code for
Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images
Keras-ICNet [paper] Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images. Training in progress! Requisites Python 3.6.3 K
Dilated Convolution for Semantic Image Segmentation
Multi-Scale Context Aggregation by Dilated Convolutions Introduction Properties of dilated convolution are discussed in our ICLR 2016 conference paper
DilatedNet in Keras for image segmentation
Keras implementation of DilatedNet for semantic segmentation A native Keras implementation of semantic segmentation according to Multi-Scale Context A
Fully Convolutional DenseNet (A.K.A 100 layer tiramisu) for semantic segmentation of images implemented in TensorFlow.
FC-DenseNet-Tensorflow This is a re-implementation of the 100 layer tiramisu, technically a fully convolutional DenseNet, in TensorFlow (Tiramisu). Th
A MatConvNet-based implementation of the Fully-Convolutional Networks for image segmentation
MatConvNet implementation of the FCN models for semantic segmentation This package contains an implementation of the FCN models (training and evaluati
Train DeepLab for Semantic Image Segmentation
Train DeepLab for Semantic Image Segmentation Martin Kersner, [email protected] This repository contains scripts for training DeepLab for Semantic I
This is an (re-)implementation of DeepLab-ResNet in TensorFlow for semantic image segmentation on the PASCAL VOC dataset.
DeepLab-ResNet-TensorFlow This is an (re-)implementation of DeepLab-ResNet in TensorFlow for semantic image segmentation on the PASCAL VOC dataset. Up
DeepLab is a state-of-art deep learning system for semantic image segmentation built on top of Caffe.
DeepLab Introduction DeepLab is a state-of-art deep learning system for semantic image segmentation built on top of Caffe. It combines densely-compute
A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
Segnet is deep fully convolutional neural network architecture for semantic pixel-wise segmentation. This is implementation of http://arxiv.org/pdf/15
Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
Python library with Neural Networks for Image Segmentation based on Keras and TensorFlow. The main features of this library are: High level API (just
UNet model with VGG11 encoder pre-trained on Kaggle Carvana dataset
TernausNet: U-Net with VGG11 Encoder Pre-Trained on ImageNet for Image Segmentation By Vladimir Iglovikov and Alexey Shvets Introduction TernausNet is
Implementation of Segnet, FCN, UNet , PSPNet and other models in Keras.
Image Segmentation Keras : Implementation of Segnet, FCN, UNet, PSPNet and other models in Keras. Implementation of various Deep Image Segmentation mo
Generic U-Net Tensorflow implementation for image segmentation
Tensorflow Unet Warning This project is discontinued in favour of a Tensorflow 2 compatible reimplementation of this project found under https://githu
U-Net: Convolutional Networks for Biomedical Image Segmentation
Deep Learning Tutorial for Kaggle Ultrasound Nerve Segmentation competition, using Keras This tutorial shows how to use Keras library to build deep ne
Modification of convolutional neural net "UNET" for image segmentation in Keras framework
ZF_UNET_224 Pretrained Model Modification of convolutional neural net "UNET" for image segmentation in Keras framework Requirements Python 3.*, Keras
unet for image segmentation
Implementation of deep learning framework -- Unet, using Keras The architecture was inspired by U-Net: Convolutional Networks for Biomedical Image Seg
Official Python implementation of the 'Sparse deconvolution'-v0.3.0
Sparse deconvolution Python v0.3.0 Official Python implementation of the 'Sparse deconvolution', and the CPU (NumPy) and GPU (CuPy) calculation backen
CNN Based Meta-Learning for Noisy Image Classification and Template Matching
CNN Based Meta-Learning for Noisy Image Classification and Template Matching Introduction This master thesis used a few-shot meta learning approach to
The Curious Layperson: Fine-Grained Image Recognition without Expert Labels (BMVC 2021)
The Curious Layperson: Fine-Grained Image Recognition without Expert Labels Subhabrata Choudhury, Iro Laina, Christian Rupprecht, Andrea Vedaldi Code
A criticism of a recent paper on buggy image downsampling methods in popular image processing and deep learning libraries.
A criticism of a recent paper on buggy image downsampling methods in popular image processing and deep learning libraries.
[CVPR'20] TTSR: Learning Texture Transformer Network for Image Super-Resolution
TTSR Official PyTorch implementation of the paper Learning Texture Transformer Network for Image Super-Resolution accepted in CVPR 2020. Contents Intr
Screenhook is a script that captures an image of a web page and send it to a discord webhook.
screenshot from the web for discord webhooks screenhook is a script that captures an image of a web page and send it to a discord webhook.
Half Instance Normalization Network for Image Restoration
HINet Half Instance Normalization Network for Image Restoration, based on https://github.com/megvii-model/HINet. Dependencies NumPy PyTorch, preferabl