2244 Repositories
Python image-classification Libraries
Implementation of Segformer, Attention + MLP neural network for segmentation, in Pytorch
Segformer - Pytorch Implementation of Segformer, Attention + MLP neural network for segmentation, in Pytorch. Install $ pip install segformer-pytorch
Official PyTorch implementation of Less is More: Pay Less Attention in Vision Transformers.
Less is More: Pay Less Attention in Vision Transformers Official PyTorch implementation of Less is More: Pay Less Attention in Vision Transformers. By
This is a GUI based text and image messenger. Other functionalities will be added soon.
Pigeon-Messenger (Requires Python and Kivy) Pigeon is a GUI based text and image messenger using Kivy and Python. Currently the layout is built. Funct
A Icon Maker GUI Made - Convert your image into icon ( .ico format ).
Icon-Maker-GUI A Icon Maker GUI Made Using Python 3.9.0 . It will take any image and convert it to ICO file, for web site favicon or Windows applicati
PyTorch implementation of Pay Attention to MLPs
gMLP PyTorch implementation of Pay Attention to MLPs. Quickstart Clone this repository. git clone https://github.com/jaketae/g-mlp.git Navigate to th
Official PyTorch implementation of "Adversarial Reciprocal Points Learning for Open Set Recognition"
Adversarial Reciprocal Points Learning for Open Set Recognition Official PyTorch implementation of "Adversarial Reciprocal Points Learning for Open Se
ImVoxelNet: Image to Voxels Projection for Monocular and Multi-View General-Purpose 3D Object Detection
ImVoxelNet: Image to Voxels Projection for Monocular and Multi-View General-Purpose 3D Object Detection This repository contains implementation of the
EDPN: Enhanced Deep Pyramid Network for Blurry Image Restoration
EDPN: Enhanced Deep Pyramid Network for Blurry Image Restoration Ruikang Xu, Zeyu Xiao, Jie Huang, Yueyi Zhang, Zhiwei Xiong. EDPN: Enhanced Deep Pyra
DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification
DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification Created by Yongming Rao, Wenliang Zhao, Benlin Liu, Jiwen Lu, Jie Zhou, Ch
[ICML 2021, Long Talk] Delving into Deep Imbalanced Regression
Delving into Deep Imbalanced Regression This repository contains the implementation code for paper: Delving into Deep Imbalanced Regression Yuzhe Yang
This is an implementation for the CVPR2020 paper "Learning Invariant Representation for Unsupervised Image Restoration"
Learning Invariant Representation for Unsupervised Image Restoration (CVPR 2020) Introduction This is an implementation for the paper "Learning Invari
An esoteric visual language that takes image files as input based on a multi-tape turing machine, designed for compatibility with C.
vizh An esoteric visual language that takes image files as input based on a multi-tape turing machine, designed for compatibility with C. Overview Her
A simple programming language for manipulating images.
f-stop A simple programming language for manipulating images. Examples OPEN "image.png" AS image RESIZE image (300, 300) SAVE image "out.jpg" CLOSE im
Rubik's cube assistant on Flask webapp
webcube Rubik's cube assistant on Flask webapp. This webapp accepts the six faces of your cube and gives you the voice instructions as a response. Req
simpleT5 is built on top of PyTorch-lightning⚡️ and Transformers🤗 that lets you quickly train your T5 models.
Quickly train T5 models in just 3 lines of code + ONNX support simpleT5 is built on top of PyTorch-lightning ⚡️ and Transformers 🤗 that lets you quic
SparseML is a libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models
SparseML is a toolkit that includes APIs, CLIs, scripts and libraries that apply state-of-the-art sparsification algorithms such as pruning and quantization to any neural network. General, recipe-driven approaches built around these algorithms enable the simplification of creating faster and smaller models for the ML performance community at large.
Learned image compression
Overview Pytorch code of our recent work A Unified End-to-End Framework for Efficient Deep Image Compression. We first release the code for Variationa
Code for CVPR2021 "Visualizing Adapted Knowledge in Domain Transfer". Visualization for domain adaptation. #explainable-ai
Visualizing Adapted Knowledge in Domain Transfer @inproceedings{hou2021visualizing, title={Visualizing Adapted Knowledge in Domain Transfer}, auth
Deep Image Search - AI-Based Image Search Engine
Deep Image Search is an AI-based image search engine that includes deep transfer learning features Extraction and tree-based vectorized search technique.
Framework for joint representation learning, evaluation through multimodal registration and comparison with image translation based approaches
CoMIR: Contrastive Multimodal Image Representation for Registration Framework 🖼 Registration of images in different modalities with Deep Learning 🤖
Code of U2Fusion: a unified unsupervised image fusion network for multiple image fusion tasks, including multi-modal, multi-exposure and multi-focus image fusion.
U2Fusion Code of U2Fusion: a unified unsupervised image fusion network for multiple image fusion tasks, including multi-modal (VIS-IR, medical), multi
Implementation of CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification
CrossViT : Cross-Attention Multi-Scale Vision Transformer for Image Classification This is an unofficial PyTorch implementation of CrossViT: Cross-Att
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
This is an official implementation of CvT: Introducing Convolutions to Vision Transformers.
Introduction This is an official implementation of CvT: Introducing Convolutions to Vision Transformers. We present a new architecture, named Convolut
Third party Pytorch implement of Image Processing Transformer (Pre-Trained Image Processing Transformer arXiv:2012.00364v2)
ImageProcessingTransformer Third party Pytorch implement of Image Processing Transformer (Pre-Trained Image Processing Transformer arXiv:2012.00364v2)
Medical Image Segmentation using Squeeze-and-Expansion Transformers
Medical Image Segmentation using Squeeze-and-Expansion Transformers Introduction This repository contains the code of the IJCAI'2021 paper 'Medical Im
A list of hyperspectral image super-solution resources collected by Junjun Jiang
A list of hyperspectral image super-resolution resources collected by Junjun Jiang. If you find that important resources are not included, please feel free to contact me.
This is the official implementation of TrivialAugment and a mini-library for the application of multiple image augmentation strategies including RandAugment and TrivialAugment.
Trivial Augment This is the official implementation of TrivialAugment (https://arxiv.org/abs/2103.10158), as was used for the paper. TrivialAugment is
Deep Image Search is an AI-based image search engine that includes deep transfor learning features Extraction and tree-based vectorized search.
Deep Image Search - AI-Based Image Search Engine Deep Image Search is an AI-based image search engine that includes deep transfer learning features Ex
Extract MNIST handwritten digits dataset binary file into bmp images
MNIST-dataset-extractor Extract MNIST handwritten digits dataset binary file into bmp images More info at http://yann.lecun.com/exdb/mnist/ Dependenci
Code for reproducing our analysis in the paper titled: Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency
Image Crop Analysis This is a repo for the code used for reproducing our Image Crop Analysis paper as shared on our blog post. If you plan to use this
Non-Official Pytorch implementation of "Face Identity Disentanglement via Latent Space Mapping" https://arxiv.org/abs/2005.07728 Using StyleGAN2 instead of StyleGAN
Face Identity Disentanglement via Latent Space Mapping - Implement in pytorch with StyleGAN 2 Description Pytorch implementation of the paper Face Ide
PyTorch code for our paper "Attention in Attention Network for Image Super-Resolution"
Under construction... Attention in Attention Network for Image Super-Resolution (A2N) This repository is an PyTorch implementation of the paper "Atten
Image data augmentation scheduler for albumentations transforms
albu_scheduler Scheduler for albumentations transforms based on PyTorch schedulers interface Usage TransformMultiStepScheduler import albumentations a
A Joint Video and Image Encoder for End-to-End Retrieval
Frozen️ in Time ❄️ ️️️️ ⏳ A Joint Video and Image Encoder for End-to-End Retrieval (arXiv) Repository to contain the code, models, data for end-to-end
MASA-SR: Matching Acceleration and Spatial Adaptation for Reference-Based Image Super-Resolution (CVPR2021)
MASA-SR Official PyTorch implementation of our CVPR2021 paper MASA-SR: Matching Acceleration and Spatial Adaptation for Reference-Based Image Super-Re
Learning to Reconstruct 3D Manhattan Wireframes from a Single Image
Learning to Reconstruct 3D Manhattan Wireframes From a Single Image This repository contains the PyTorch implementation of the paper: Yichao Zhou, Hao
Finding an Unsupervised Image Segmenter in each of your Deep Generative Models
Finding an Unsupervised Image Segmenter in each of your Deep Generative Models Description Recent research has shown that numerous human-interpretable
[CVPRW 2021] Code for Region-Adaptive Deformable Network for Image Quality Assessment
RADN [CVPRW 2021] Code for Region-Adaptive Deformable Network for Image Quality Assessment [Paper on arXiv] Overview Update [2021/5/7] add codes for W
Text to Image Generation with Semantic-Spatial Aware GAN
text2image This repository includes the implementation for Text to Image Generation with Semantic-Spatial Aware GAN This repo is not completely. Netwo
Code for Referring Image Segmentation via Cross-Modal Progressive Comprehension, CVPR2020.
CMPC-Refseg Code of our CVPR 2020 paper Referring Image Segmentation via Cross-Modal Progressive Comprehension. Shaofei Huang*, Tianrui Hui*, Si Liu,
A PaddlePaddle version image model zoo.
Paddle-Image-Models English | 简体中文 A PaddlePaddle version image model zoo. Install Package Install by pip: $ pip install ppim Install by wheel package
Implementation of Stochastic Image-to-Video Synthesis using cINNs.
Stochastic Image-to-Video Synthesis using cINNs Official PyTorch implementation of Stochastic Image-to-Video Synthesis using cINNs accepted to CVPR202
HINet: Half Instance Normalization Network for Image Restoration
HINet: Half Instance Normalization Network for Image Restoration Liangyu Chen, Xin Lu, Jie Zhang, Xiaojie Chu, Chengpeng Chen Paper: https://arxiv.org
PyMatting: A Python Library for Alpha Matting
Given an input image and a hand-drawn trimap (top row), alpha matting estimates the alpha channel of a foreground object which can then be composed onto a different background (bottom row).
Unofficial implementation of MLP-Mixer: An all-MLP Architecture for Vision
MLP-Mixer: An all-MLP Architecture for Vision This repo contains PyTorch implementation of MLP-Mixer: An all-MLP Architecture for Vision. Usage : impo
RepMLP: Re-parameterizing Convolutions into Fully-connected Layers for Image Recognition
RepMLP RepMLP: Re-parameterizing Convolutions into Fully-connected Layers for Image Recognition Released the code of RepMLP together with an example o
tsai is an open-source deep learning package built on top of Pytorch & fastai focused on state-of-the-art techniques for time series classification, regression and forecasting.
Time series Timeseries Deep Learning Pytorch fastai - State-of-the-art Deep Learning with Time Series and Sequences in Pytorch / fastai
Official implement of Paper:A deeply supervised image fusion network for change detection in high resolution bi-temporal remote sening images
A deeply supervised image fusion network for change detection in high resolution bi-temporal remote sensing images 深度监督影像融合网络DSIFN用于高分辨率双时相遥感影像变化检测 Of
Unofficial implementation of Google's FNet: Mixing Tokens with Fourier Transforms
FNet: Mixing Tokens with Fourier Transforms Pytorch implementation of Fnet : Mixing Tokens with Fourier Transforms. Citation: @misc{leethorp2021fnet,
CellProfiler is a open-source application for biological image analysis
CellProfiler is a free open-source software designed to enable biologists without training in computer vision or programming to quantitatively measure phenotypes from thousands of images automatically.
Implementation of ResMLP, an all MLP solution to image classification, in Pytorch
ResMLP - Pytorch Implementation of ResMLP, an all MLP solution to image classification out of Facebook AI, in Pytorch Install $ pip install res-mlp-py
Deep learning toolbox based on PyTorch for hyperspectral data classification.
Deep learning toolbox based on PyTorch for hyperspectral data classification.
This is the codebase for Diffusion Models Beat GANS on Image Synthesis.
This is the codebase for Diffusion Models Beat GANS on Image Synthesis.
This is a Computer vision package that makes its easy to run Image processing and AI functions. At the core it uses OpenCV and Mediapipe libraries.
CVZone This is a Computer vision package that makes its easy to run Image processing and AI functions. At the core it uses OpenCV and Mediapipe librar
Unofficial Implementation of MLP-Mixer in TensorFlow
mlp-mixer-tf Unofficial Implementation of MLP-Mixer [abs, pdf] in TensorFlow. Note: This project may have some bugs in it. I'm still learning how to i
Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch
30 Days Of Machine Learning Using Pytorch Objective of the repository is to learn and build machine learning models using Pytorch. List of Algorithms
Vision Transformer for 3D medical image registration (Pytorch).
ViT-V-Net: Vision Transformer for Volumetric Medical Image Registration keywords: vision transformer, convolutional neural networks, image registratio
Official implementation of Deep Convolutional Dictionary Learning for Image Denoising.
DCDicL for Image Denoising Hongyi Zheng*, Hongwei Yong*, Lei Zhang, "Deep Convolutional Dictionary Learning for Image Denoising," in CVPR 2021. (* Equ
Unsupervised Language Modeling at scale for robust sentiment classification
** DEPRECATED ** This repo has been deprecated. Please visit Megatron-LM for our up to date Large-scale unsupervised pretraining and finetuning code.
A simple command line tool for text to image generation, using OpenAI's CLIP and a BigGAN.
Ryan Murdock has done it again, combining OpenAI's CLIP and the generator from a BigGAN! This repository wraps up his work so it is easily accessible to anyone who owns a GPU.
An easier way to build neural search on the cloud
Jina is geared towards building search systems for any kind of data, including text, images, audio, video and many more. With the modular design & multi-layer abstraction, you can leverage the efficient patterns to build the system by parts, or chaining them into a Flow for an end-to-end experience.
Code for "Unsupervised Layered Image Decomposition into Object Prototypes" paper
DTI-Sprites Pytorch implementation of "Unsupervised Layered Image Decomposition into Object Prototypes" paper Check out our paper and webpage for deta
Codes for our paper "SentiLARE: Sentiment-Aware Language Representation Learning with Linguistic Knowledge" (EMNLP 2020)
SentiLARE: Sentiment-Aware Language Representation Learning with Linguistic Knowledge Introduction SentiLARE is a sentiment-aware pre-trained language
Domain Generalization with MixStyle, ICLR'21.
MixStyle This repo contains the code of our ICLR'21 paper, "Domain Generalization with MixStyle". The OpenReview link is https://openreview.net/forum?
Official implementation of "Towards Good Practices for Efficiently Annotating Large-Scale Image Classification Datasets" (CVPR2021)
Towards Good Practices for Efficiently Annotating Large-Scale Image Classification Datasets This is the official implementation of "Towards Good Pract
A simple image/video to Desmos graph converter run locally
Desmos Bezier Renderer A simple image/video to Desmos graph converter run locally Sample Result Setup Install dependencies apt update apt install git
Implementation of different ML Algorithms from scratch, written in Python 3.x
Implementation of different ML Algorithms from scratch, written in Python 3.x
Multi-Scale Vision Longformer: A New Vision Transformer for High-Resolution Image Encoding
Vision Longformer This project provides the source code for the vision longformer paper. Multi-Scale Vision Longformer: A New Vision Transformer for H
Range Image-based LiDAR Localization for Autonomous Vehicles Using Mesh Maps
Range Image-based 3D LiDAR Localization This repo contains the code for our ICRA2021 paper: Range Image-based LiDAR Localization for Autonomous Vehicl
Invert and perturb GAN images for test-time ensembling
GAN Ensembling Project Page | Paper | Bibtex Ensembling with Deep Generative Views. Lucy Chai, Jun-Yan Zhu, Eli Shechtman, Phillip Isola, Richard Zhan
TorchFlare is a simple, beginner-friendly, and easy-to-use PyTorch Framework train your models effortlessly.
TorchFlare TorchFlare is a simple, beginner-friendly and an easy-to-use PyTorch Framework train your models without much effort. It provides an almost
Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)
Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu,
The code of “Similarity Reasoning and Filtration for Image-Text Matching” [AAAI2021]
SGRAF PyTorch implementation for AAAI2021 paper of “Similarity Reasoning and Filtration for Image-Text Matching”. It is built on top of the SCAN and C
CVPR 2021: "The Spatially-Correlative Loss for Various Image Translation Tasks"
Spatially-Correlative Loss arXiv | website We provide the Pytorch implementation of "The Spatially-Correlative Loss for Various Image Translation Task
CorNet Correlation Networks for Extreme Multi-label Text Classification
CorNet Correlation Networks for Extreme Multi-label Text Classification Prerequisites python==3.6.3 pytorch==1.2.0 torchgpipe==0.0.5 click==7.0 ruamel
Code for Dual Contrastive Learning for Unsupervised Image-to-Image Translation, NTIRE, CVPRW 2021.
arXiv Dual Contrastive Learning Adversarial Generative Networks (DCLGAN) We provide our PyTorch implementation of DCLGAN, which is a simple yet powerf
Two-Stage Peer-Regularized Feature Recombination for Arbitrary Image Style Transfer
Two-Stage Peer-Regularized Feature Recombination for Arbitrary Image Style Transfer Paper on arXiv Public PyTorch implementation of two-stage peer-reg
PyKale is a PyTorch library for multimodal learning and transfer learning as well as deep learning and dimensionality reduction on graphs, images, texts, and videos
PyKale is a PyTorch library for multimodal learning and transfer learning as well as deep learning and dimensionality reduction on graphs, images, texts, and videos. By adopting a unified pipeline-based API design, PyKale enforces standardization and minimalism, via reusing existing resources, reducing repetitions and redundancy, and recycling learning models across areas.
ivadomed is an integrated framework for medical image analysis with deep learning.
Repository on the collaborative IVADO medical imaging project between the Mila and NeuroPoly labs.
Code for the paper "Improving Vision-and-Language Navigation with Image-Text Pairs from the Web" (ECCV 2020)
Improving Vision-and-Language Navigation with Image-Text Pairs from the Web Arjun Majumdar, Ayush Shrivastava, Stefan Lee, Peter Anderson, Devi Parikh
Reimplementation of the paper `Human Attention Maps for Text Classification: Do Humans and Neural Networks Focus on the Same Words? (ACL2020)`
Human Attention for Text Classification Re-implementation of the paper Human Attention Maps for Text Classification: Do Humans and Neural Networks Foc
codes for Image Inpainting with External-internal Learning and Monochromic Bottleneck
Image Inpainting with External-internal Learning and Monochromic Bottleneck This repository is for the CVPR 2021 paper: 'Image Inpainting with Externa
Code for "Learning the Best Pooling Strategy for Visual Semantic Embedding", CVPR 2021
Learning the Best Pooling Strategy for Visual Semantic Embedding Official PyTorch implementation of the paper Learning the Best Pooling Strategy for V
Official Pytorch Implementation of: "ImageNet-21K Pretraining for the Masses"(2021) paper
ImageNet-21K Pretraining for the Masses Paper | Pretrained models Official PyTorch Implementation Tal Ridnik, Emanuel Ben-Baruch, Asaf Noy, Lihi Zelni
FID calculation with proper image resizing and quantization steps
clean-fid: Fixing Inconsistencies in FID Project | Paper The FID calculation involves many steps that can produce inconsistencies in the final metric.
CoaT: Co-Scale Conv-Attentional Image Transformers
CoaT: Co-Scale Conv-Attentional Image Transformers Introduction This repository contains the official code and pretrained models for CoaT: Co-Scale Co
Attack classification models with transferability, black-box attack; unrestricted adversarial attacks on imagenet
Attack classification models with transferability, black-box attack; unrestricted adversarial attacks on imagenet, CVPR2021 安全AI挑战者计划第六期:ImageNet无限制对抗攻击 决赛第四名(team name: Advers)
Rethinking the U-Net architecture for multimodal biomedical image segmentation
MultiResUNet Rethinking the U-Net architecture for multimodal biomedical image segmentation This repository contains the original implementation of "M
Activity image-based video retrieval
Cross-modal-retrieval Our approach is focus on Activity Image-to-Video Retrieval (AIVR) task. The compared methods are state-of-the-art single modalit
Image-Scaling Attacks and Defenses
Image-Scaling Attacks & Defenses This repository belongs to our publication: Erwin Quiring, David Klein, Daniel Arp, Martin Johns and Konrad Rieck. Ad
automatic color-grading
color-matcher Description color-matcher enables color transfer across images which comes in handy for automatic color-grading of photographs, painting
This is a repository for a semantic segmentation inference API using the OpenVINO toolkit
BMW-IntelOpenVINO-Segmentation-Inference-API This is a repository for a semantic segmentation inference API using the OpenVINO toolkit. It's supported
A simple python library for fast image generation of people who do not exist.
Random Face A simple python library for fast image generation of people who do not exist. For more details, please refer to the [paper](https://arxiv.
CVPR 2021 Oral paper "LED2-Net: Monocular 360˚ Layout Estimation via Differentiable Depth Rendering" official PyTorch implementation.
LED2-Net This is PyTorch implementation of our CVPR 2021 Oral paper "LED2-Net: Monocular 360˚ Layout Estimation via Differentiable Depth Rendering". Y
Bayesian Image Reconstruction using Deep Generative Models
Bayesian Image Reconstruction using Deep Generative Models R. Marinescu, D. Moyer, P. Golland For technical inquiries, please create a Github issue. F
Weakly supervised medical named entity classification
Trove Trove is a research framework for building weakly supervised (bio)medical named entity recognition (NER) and other entity attribute classifiers
Implementation of Convolutional enhanced image Transformer
CeiT : Convolutional enhanced image Transformer This is an unofficial PyTorch implementation of Incorporating Convolution Designs into Visual Transfor
Official Implementation of Swapping Autoencoder for Deep Image Manipulation (NeurIPS 2020)
Swapping Autoencoder for Deep Image Manipulation Taesung Park, Jun-Yan Zhu, Oliver Wang, Jingwan Lu, Eli Shechtman, Alexei A. Efros, Richard Zhang UC
This repository allows you to anonymize sensitive information in images/videos. The solution is fully compatible with the DL-based training/inference solutions that we already published/will publish for Object Detection and Semantic Segmentation.
BMW-Anonymization-Api Data privacy and individuals’ anonymity are and always have been a major concern for data-driven companies. Therefore, we design