2994 Repositories
Python -Study-CSRNet-pytorch Libraries
Romanian Automatic Speech Recognition from the ROBIN project
RobinASR This repository contains Robin's Automatic Speech Recognition (RobinASR) for the Romanian language based on the DeepSpeech2 architecture, tog
The code for 'Deep Residual Fourier Transformation for Single Image Deblurring'
Deep Residual Fourier Transformation for Single Image Deblurring Xintian Mao, Yiming Liu, Wei Shen, Qingli Li and Yan Wang code will be released soon
Pytorch implementation for "Density-aware Chamfer Distance as a Comprehensive Metric for Point Cloud Completion" (NeurIPS 2021)
Density-aware Chamfer Distance This repository contains the official PyTorch implementation of our paper: Density-aware Chamfer Distance as a Comprehe
This is the official PyTorch implementation for "Sharpness-aware Quantization for Deep Neural Networks".
Sharpness-aware Quantization for Deep Neural Networks This is the official repository for our paper: Sharpness-aware Quantization for Deep Neural Netw
OpenMMLab Text Detection, Recognition and Understanding Toolbox
Introduction English | ็ฎไฝไธญๆ MMOCR is an open-source toolbox based on PyTorch and mmdetection for text detection, text recognition, and the correspondi
OpenMMLab Image Classification Toolbox and Benchmark
Introduction English | ็ฎไฝไธญๆ MMClassification is an open source image classification toolbox based on PyTorch. It is a part of the OpenMMLab project. D
K-Nearest Neighbor in Pytorch
Pytorch KNN CUDA 2019/11/02 This repository will no longer be maintained as pytorch supports sort() and kthvalue on tensors. git clone https://github.
PyTorch implementation for the visual prior component (i.e. perception module) of the Visually Grounded Physics Learner [Li et al., 2020].
VGPL-Visual-Prior PyTorch implementation for the visual prior component (i.e. perception module) of the Visually Grounded Physics Learner (VGPL). Give
Official pytorch implementation of "DSPoint: Dual-scale Point Cloud Recognition with High-frequency Fusion"
DSPoint Official implementation of "DSPoint: Dual-scale Point Cloud Recognition with High-frequency Fusion". Paper link: https://arxiv.org/abs/2111.10
Pytorch implementation for "Density-aware Chamfer Distance as a Comprehensive Metric for Point Cloud Completion" (NeurIPS 2021)
Density-aware Chamfer Distance This repository contains the official PyTorch implementation of our paper: Density-aware Chamfer Distance as a Comprehe
Official Pytorch implementation of "DivCo: Diverse Conditional Image Synthesis via Contrastive Generative Adversarial Network" (CVPR'21)
DivCo: Diverse Conditional Image Synthesis via Contrastive Generative Adversarial Network Pytorch implementation for our DivCo. We propose a simple ye
Official PyTorch implementation of "Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning" (ICCV2021 Oral)
MeTAL - Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning (ICCV2021 Oral) Sungyong Baik, Janghoon Choi, Heewon Kim, Dohee Cho, Jaes
Delve is a Python package for analyzing the inference dynamics of your PyTorch model.
Delve is a Python package for analyzing the inference dynamics of your PyTorch model.
Manifold-Mixup implementation for fastai V2
Manifold Mixup Unofficial implementation of ManifoldMixup (Proceedings of ICML 19) for fast.ai (V2) based on Shivam Saboo's pytorch implementation of
FasterAI: A library to make smaller and faster models with FastAI.
Fasterai fasterai is a library created to make neural network smaller and faster. It essentially relies on common compression techniques for networks
๐ Audio and fastai v2
Fastaudio An audio module for fastai v2. We want to help you build audio machine learning applications while minimizing the need for audio domain expe
Walk with fastai
Shield: This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Walk with fastai What is this p
Minimal fastai code needed for working with pytorch
fastai_minima A mimal version of fastai with the barebones needed to work with Pytorch #all_slow Install pip install fastai_minima How to use This lib
An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.
Welcome to AdaptNLP A high level framework and library for running, training, and deploying state-of-the-art Natural Language Processing (NLP) models
An Agnostic Computer Vision Framework - Pluggable to any Training Library: Fastai, Pytorch-Lightning with more to come
An Agnostic Object Detection Framework IceVision is the first agnostic computer vision framework to offer a curated collection with hundreds of high-q
A fastai/PyTorch package for unpaired image-to-image translation.
Unpaired image-to-image translation A fastai/PyTorch package for unpaired image-to-image translation currently with CycleGAN implementation. This is a
A modular domain adaptation library written in PyTorch.
A modular domain adaptation library written in PyTorch.
This is the official PyTorch implementation for "Mesa: A Memory-saving Training Framework for Transformers".
A Memory-saving Training Framework for Transformers This is the official PyTorch implementation for Mesa: A Memory-saving Training Framework for Trans
OCR Streamlit App is used to extract text from images using python's easyocr, pytorch and streamlit packages
OCR-Streamlit-App OCR Streamlit App is used to extract text from images using python's easyocr, pytorch and streamlit packages OCR app gets an image a
An example project using OpenPrompt under pytorch-lightning for prompt-based SST2 sentiment analysis model
pl_prompt_sst An example project using OpenPrompt under the framework of pytorch-lightning for a training prompt-based text classification model on SS
PyTorch code for Composing Partial Differential Equations with Physics-Aware Neural Networks
FInite volume Neural Network (FINN) This repository contains the PyTorch code for models, training, and testing, and Python code for data generation t
PyTorch implementation for "Sharpness-aware Quantization for Deep Neural Networks".
Sharpness-aware Quantization for Deep Neural Networks Recent Update 2021.11.23: We release the source code of SAQ. Setup the environments Clone the re
Semantic Segmentation in Pytorch
PyTorch Semantic Segmentation Introduction This repository is a PyTorch implementation for semantic segmentation / scene parsing. The code is easy to
PyTorch implementation of saliency map-aided GAN for Auto-demosaic+denosing
Saiency Map-aided GAN for RAW2RGB Mapping The PyTorch implementations and guideline for Saiency Map-aided GAN for RAW2RGB Mapping. 1 Implementations B
A PyTorch port of the Neural 3D Mesh Renderer
Neural 3D Mesh Renderer (CVPR 2018) This repo contains a PyTorch implementation of the paper Neural 3D Mesh Renderer by Hiroharu Kato, Yoshitaka Ushik
Implementation of the Chamfer Distance as a module for pyTorch
Chamfer Distance for pyTorch This is an implementation of the Chamfer Distance as a module for pyTorch. It is written as a custom C++/CUDA extension.
Deep and online learning with spiking neural networks in Python
Introduction The brain is the perfect place to look for inspiration to develop more efficient neural networks. One of the main differences with modern
Universal Probability Distributions with Optimal Transport and Convex Optimization
Sylvester normalizing flows for variational inference Pytorch implementation of Sylvester normalizing flows, based on our paper: Sylvester normalizing
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models. Hyperactive: is very easy to lear
Tensorboard for pytorch (and chainer, mxnet, numpy, ...)
tensorboardX Write TensorBoard events with simple function call. The current release (v2.3) is tested on anaconda3, with PyTorch 1.8.1 / torchvision 0
Discovering Interpretable GAN Controls [NeurIPS 2020]
GANSpace: Discovering Interpretable GAN Controls Figure 1: Sequences of image edits performed using control discovered with our method, applied to thr
Live training loss plot in Jupyter Notebook for Keras, PyTorch and others
livelossplot Don't train deep learning models blindfolded! Be impatient and look at each epoch of your training! (RECENT CHANGES, EXAMPLES IN COLAB, A
A natural language modeling framework based on PyTorch
Overview PyText is a deep-learning based NLP modeling framework built on PyTorch. PyText addresses the often-conflicting requirements of enabling rapi
PyTorch implementation of the paper:A Convolutional Approach to Melody Line Identification in Symbolic Scores.
Symbolic Melody Identification This repository is an unofficial PyTorch implementation of the paper:A Convolutional Approach to Melody Line Identifica
This will help you study and avoid moving mouse coz u dont need mouse for watching youtube videos
This will help you study and avoid moving mouse coz u dont need mouse for watching youtube videos. Neither u need it for pdfs just use your keyboard
mmfewshot is an open source few shot learning toolbox based on PyTorch
OpenMMLab FewShot Learning Toolbox and Benchmark
A method that utilized Generative Adversarial Network (GAN) to interpret the black-box deep image classifier models by PyTorch.
A method that utilized Generative Adversarial Network (GAN) to interpret the black-box deep image classifier models by PyTorch.
This is the official PyTorch implementation for "Mesa: A Memory-saving Training Framework for Transformers".
Mesa: A Memory-saving Training Framework for Transformers This is the official PyTorch implementation for Mesa: A Memory-saving Training Framework for
Pytorch implementation of "Geometrically Adaptive Dictionary Attack on Face Recognition" (WACV 2022)
Geometrically Adaptive Dictionary Attack on Face Recognition This is the Pytorch code of our paper "Geometrically Adaptive Dictionary Attack on Face R
Implementation of Pix2Seq in PyTorch
pix2seq-pytorch Implementation of Pix2Seq paper Different from the paper image input size 1280 bin size 1280 LambdaLR scheduler used instead of Linear
Detectron2 for Document Layout Analysis
Detectron2 trained on PubLayNet dataset This repo contains the training configurations, code and trained models trained on PubLayNet dataset using Det
Naszilla is a Python library for neural architecture search (NAS)
A repository to compare many popular NAS algorithms seamlessly across three popular benchmarks (NASBench 101, 201, and 301). You can implement your ow
Quantization library for PyTorch. Support low-precision and mixed-precision quantization, with hardware implementation through TVM.
HAWQ: Hessian AWare Quantization HAWQ is an advanced quantization library written for PyTorch. HAWQ enables low-precision and mixed-precision uniform
The pure and clear PyTorch Distributed Training Framework.
The pure and clear PyTorch Distributed Training Framework. Introduction Requirements and Usage Dependency Dataset Basic Usage Slurm Cluster Usage Base
Official pytorch implementation of "DSPoint: Dual-scale Point Cloud Recognition with High-frequency Fusion"
DSPoint Official pytorch implementation of "DSPoint: Dual-scale Point Cloud Recognition with High-frequency Fusion" Coming soon, as soon as I finish a
Learning Neural Painters Fast! using PyTorch and Fast.ai
The Joy of Neural Painting Learning Neural Painters Fast! using PyTorch and Fast.ai Blogpost with more details: The Joy of Neural Painting The impleme
[BMVC'21] Official PyTorch Implementation of Grounded Situation Recognition with Transformers
Grounded Situation Recognition with Transformers Paper | Model Checkpoint This is the official PyTorch implementation of Grounded Situation Recognitio
Deep Learning with PyTorch made easy ๐ !
Deep Learning with PyTorch made easy ๐ ! Carefree? carefree-learn aims to provide CAREFREE usages for both users and developers. It also provides a c
PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
Score-Based Generative Modeling through Stochastic Differential Equations This repo contains a PyTorch implementation for the paper Score-Based Genera
Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation. Intel iHD GPU (iGPU) support. NVIDIA GPU (dGPU) support.
mtomo Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation.
This repo contains implementation of different architectures for emotion recognition in conversations.
Emotion Recognition in Conversations Updates ๐ฅ ๐ฅ ๐ฅ Date Announcements 03/08/2021 ๐ ๐ We have released a new dataset M2H2: A Multimodal Multiparty
Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...
Automatic, Readable, Reusable, Extendable Machin is a reinforcement library designed for pytorch. Build status Platform Status Linux Windows Supported
A GPU-optional modular synthesizer in pytorch, 16200x faster than realtime, for audio ML researchers.
torchsynth The fastest synth in the universe. Introduction torchsynth is based upon traditional modular synthesis written in pytorch. It is GPU-option
DA2Lite is an automated model compression toolkit for PyTorch.
DA2Lite (Deep Architecture to Lite) is a toolkit to compress and accelerate deep network models. โญ Star us on GitHub โ it helps!! Frameworks & Librari
Geometric Vector Perceptrons --- a rotation-equivariant GNN for learning from biomolecular structure
Geometric Vector Perceptron Implementation of equivariant GVP-GNNs as described in Learning from Protein Structure with Geometric Vector Perceptrons b
Management of exclusive GPU access for distributed machine learning workloads
TensorHive is an open source tool for managing computing resources used by multiple users across distributed hosts. It focuses on granting
PyTorch Connectomics: segmentation toolbox for EM connectomics
Introduction The field of connectomics aims to reconstruct the wiring diagram of the brain by mapping the neural connections at the level of individua
DeepHawkeye is a library to detect unusual patterns in images using features from pretrained neural networks
English | ็ฎไฝไธญๆ Introduction DeepHawkeye is a library to detect unusual patterns in images using features from pretrained neural networks Reference Pat
Stanza: A Python NLP Library for Many Human Languages
Official Stanford NLP Python Library for Many Human Languages
Single cell current best practices tutorial case study for the paper:Luecken and Theis, "Current best practices in single-cell RNA-seq analysis: a tutorial"
Scripts for "Current best-practices in single-cell RNA-seq: a tutorial" This repository is complementary to the publication: M.D. Luecken, F.J. Theis,
A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX
Foolbox Native: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAX Foolbox is a Python li
Neural network graphs and training metrics for PyTorch, Tensorflow, and Keras.
HiddenLayer A lightweight library for neural network graphs and training metrics for PyTorch, Tensorflow, and Keras. HiddenLayer is simple, easy to ex
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website โข Key Features โข How To Use โข Docs โข
AI Toolkit for Healthcare Imaging
Medical Open Network for AI MONAI is a PyTorch-based, open-source framework for deep learning in healthcare imaging, part of PyTorch Ecosystem. Its am
A simple, fully convolutional model for real-time instance segmentation.
You Only Look At CoefficienTs โโโ โโโ โโโโโโโ โโโ โโโโโโ โโโโโโโโโโโโโโโโ โโโโ โโโโโโโโโโโโโโโโ โโโโโโโโโโโโโโโโโโโโโโโโโ โโโ
Pytorch implementation of 'Fingerprint Presentation Attack Detector Using Global-Local Model'
RTK-PAD This is an official pytorch implementation of 'Fingerprint Presentation Attack Detector Using Global-Local Model', which is accepted by IEEE T
Neural Scene Flow Fields using pytorch-lightning, with potential improvements
nsff_pl Neural Scene Flow Fields using pytorch-lightning. This repo reimplements the NSFF idea, but modifies several operations based on observation o
Deep learning for NLP crash course at ABBYY.
Deep NLP Course at ABBYY Deep learning for NLP crash course at ABBYY. Suggested textbook: Neural Network Methods in Natural Language Processing by Yoa
nlp-tutorial is a tutorial for who is studying NLP(Natural Language Processing) using Pytorch
nlp-tutorial is a tutorial for who is studying NLP(Natural Language Processing) using Pytorch. Most of the models in NLP were implemented with less than 100 lines of code.(except comments or blank lines)
Implementation EfficientDet: Scalable and Efficient Object Detection in PyTorch
Implementation EfficientDet: Scalable and Efficient Object Detection in PyTorch
PyTorch implementation of our ICCV 2021 paper Intrinsic-Extrinsic Preserved GANs for Unsupervised 3D Pose Transfer.
Unsupervised_IEPGAN This is the PyTorch implementation of our ICCV 2021 paper Intrinsic-Extrinsic Preserved GANs for Unsupervised 3D Pose Transfer. Ha
Codes for Causal Semantic Generative model (CSG), the model proposed in "Learning Causal Semantic Representation for Out-of-Distribution Prediction" (NeurIPS-21)
Learning Causal Semantic Representation for Out-of-Distribution Prediction This repository is the official implementation of "Learning Causal Semantic
PyTorch implementation of Hierarchical Multi-label Text Classification: An Attention-based Recurrent Network
hierarchical-multi-label-text-classification-pytorch Hierarchical Multi-label Text Classification: An Attention-based Recurrent Network Approach This
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features
CleanRL (Clean Implementation of RL Algorithms) CleanRL is a Deep Reinforcement Learning library that provides high-quality single-file implementation
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
Code for IntraQ, PyTorch implementation of our paper under review
IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Shot Network Quantization paper Requirements Python = 3.7.10 Pytorch == 1.7
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
Official PyTorch implementation for "Low Precision Decentralized Distributed Training with Heterogenous Data"
Low Precision Decentralized Training with Heterogenous Data Official PyTorch implementation for "Low Precision Decentralized Distributed Training with
[BMVC'21] Official PyTorch Implementation of Grounded Situation Recognition with Transformers
Grounded Situation Recognition with Transformers Paper | Model Checkpoint This is the official PyTorch implementation of Grounded Situation Recognitio
An pytorch implementation of Masked Autoencoders Are Scalable Vision Learners
An pytorch implementation of Masked Autoencoders Are Scalable Vision Learners This is a coarse version for MAE, only make the pretrain model, the fine
SSD-based Object Detection in PyTorch
SSD-based Object Detection in PyTorch ์๊ฐ๋ํ๊ต ํ๋๋ชจ๋น์ค SW ํ๋ก๊ทธ๋จ์์ ์งํํ ์ธ๊ณต์ง๋ฅ ํ๋ก์ ํธ์ ๋๋ค. Jetson nano๋ฅผ ์ด์ฉํด pre-trained network๋ฅผ fine tuning์์ผ ์ฐจ๋ ๋ฐ ์ ํธ๋ฑ ์ธ์์ ๊ตฌํํ์์ต๋๋ค
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
A PyTorch implementation of "CoAtNet: Marrying Convolution and Attention for All Data Sizes".
CoAtNet Overview This is a PyTorch implementation of CoAtNet specified in "CoAtNet: Marrying Convolution and Attention for All Data Sizes", arXiv 2021
GemNet model in PyTorch, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)
GemNet: Universal Directional Graph Neural Networks for Molecules Reference implementation in PyTorch of the geometric message passing neural network
PyTorch implementation for our NeurIPS 2021 Spotlight paper "Long Short-Term Transformer for Online Action Detection".
Long Short-Term Transformer for Online Action Detection Introduction This is a PyTorch implementation for our NeurIPS 2021 Spotlight paper "Long Short
PyTorch/TorchScript compiler for NVIDIA GPUs using TensorRT
PyTorch/TorchScript compiler for NVIDIA GPUs using TensorRT
This is a project based on retinaface face detection, including ghostnet and mobilenetv3
English | ็ฎไฝไธญๆ RetinaFace in PyTorch Chinese detailed blog๏ผhttps://zhuanlan.zhihu.com/p/379730820 Face recognition with masks is still robust---------
Official PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection? (ICCV 2021), Dennis Park*, Rares Ambrus*, Vitor Guizilini, Jie Li, and Adrien Gaidon.
DD3D: "Is Pseudo-Lidar needed for Monocular 3D Object detection?" Install // Datasets // Experiments // Models // License // Reference Full video Offi
An open source object detection toolbox based on PyTorch
MMDetection is an open source object detection toolbox based on PyTorch. It is a part of the OpenMMLab project.
PyTorch implementation of the paper: "Preference-Adaptive Meta-Learning for Cold-Start Recommendation", IJCAI, 2021.
PAML PyTorch implementation of the paper: "Preference-Adaptive Meta-Learning for Cold-Start Recommendation", IJCAI, 2021. (Continuously updating ) Int
PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners for self-supervised ViT.
MAE for Self-supervised ViT Introduction This is an unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners for self-sup
PyTorch Kafka Dataset: A definition of a dataset to get training data from Kafka.
PyTorch Kafka Dataset: A definition of a dataset to get training data from Kafka.
Pytorch implementation of Rosca, Mihaela, et al. "Variational Approaches for Auto-Encoding Generative Adversarial Networks."
alpha-GAN Unofficial pytorch implementation of Rosca, Mihaela, et al. "Variational Approaches for Auto-Encoding Generative Adversarial Networks." arXi
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