3066 Repositories
Python ocr-pytorch Libraries
Simple-Image-Classification - Simple Image Classification Code (PyTorch)
Simple-Image-Classification Simple Image Classification Code (PyTorch) Yechan Kim This repository contains: Python3 / Pytorch code for multi-class ima
Pytorch-3dunet - 3D U-Net model for volumetric semantic segmentation written in pytorch
pytorch-3dunet PyTorch implementation 3D U-Net and its variants: Standard 3D U-Net based on 3D U-Net: Learning Dense Volumetric Segmentation from Spar
Tianshou - An elegant PyTorch deep reinforcement learning library.
Tianshou (天授) is a reinforcement learning platform based on pure PyTorch. Unlike existing reinforcement learning libraries, which are mainly based on
AutoGluon: AutoML for Text, Image, and Tabular Data
AutoML for Text, Image, and Tabular Data AutoGluon automates machine learning tasks enabling you to easily achieve strong predictive performance in yo
NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥
NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥
PyTorch-Multi-Style-Transfer - Neural Style and MSG-Net
PyTorch-Style-Transfer This repo provides PyTorch Implementation of MSG-Net (ours) and Neural Style (Gatys et al. CVPR 2016), which has been included
KoBERT - Korean BERT pre-trained cased (KoBERT)
KoBERT KoBERT Korean BERT pre-trained cased (KoBERT) Why'?' Training Environment Requirements How to install How to use Using with PyTorch Using with
Nerf pl - NeRF (Neural Radiance Fields) and NeRF in the Wild using pytorch-lightning
nerf_pl Update: an improved NSFF implementation to handle dynamic scene is open! Update: NeRF-W (NeRF in the Wild) implementation is added to nerfw br
GestureSSD CBAM - A gesture recognition web system based on SSD and CBAM, using pytorch, flask and node.js
GestureSSD_CBAM A gesture recognition web system based on SSD and CBAM, using pytorch, flask and node.js SSD implementation is based on https://github
U-2-Net: U Square Net - Modified for paired image training of style transfer
U2-Net: U Square Net Modified for paired image training of style transfer This is an unofficial repo making use of the code which was made available b
Client - 🔥 A tool for visualizing and tracking your machine learning experiments
Weights and Biases Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to produ
A supercharged version of paperless: scan, index and archive all your physical documents
Paperless-ng Paperless (click me) is an application by Daniel Quinn and contributors that indexes your scanned documents and allows you to easily sear
Non-Attentive-Tacotron - This is Pytorch Implementation of Google's Non-attentive Tacotron.
Non-attentive Tacotron - PyTorch Implementation This is Pytorch Implementation of Google's Non-attentive Tacotron, text-to-speech system. There is som
Multi agent DDPG algorithm written in Python + Pytorch
Multi agent DDPG algorithm written in Python + Pytorch. It also includes a Jupyter notebook, Tennis.ipynb, as a showcase.
Videocaptioning.pytorch - A simple implementation of video captioning
pytorch implementation of video captioning recommend installing pytorch and pyth
Omdena-abuja-anpd - Automatic Number Plate Detection for the security of lives and properties using Computer Vision.
Omdena-abuja-anpd - Automatic Number Plate Detection for the security of lives and properties using Computer Vision.
Image-popularity-score - A novel deep regression method for image scoring.
Image-popularity-score - A novel deep regression method for image scoring.
Optimizers-visualized - Visualization of different optimizers on local minimas and saddle points.
Optimizers Visualized Visualization of how different optimizers handle mathematical functions for optimization. Contents Installation Usage Functions
🐾 Semantic segmentation of paws from cute pet images (PyTorch)
🐾 paw-segmentation 🐾 Semantic segmentation of paws from cute pet images 🐾 Semantic segmentation of paws from cute pet images (PyTorch) 🐾 Paw Segme
IDCARD-VERIFYING-SYSTEM - The "IDCARD VERIFYING SYSTEM" uses the Google's latest version of Tesseract OCR[Optical Character Recognition]
IDCARD VERIFYING SYSTEM The "IDCARD VERIFYING SYSTEM" uses the Google's latest v
Siamese-nn-semantic-text-similarity - A repository containing comprehensive Neural Networks based PyTorch implementations for the semantic text similarity task
Siamese Deep Neural Networks for Semantic Text Similarity PyTorch A repository c
Neural-fractal - Create Fractals Using Complex-Valued Neural Networks!
Neural Fractal Create Fractals Using Complex-Valued Neural Networks! Home Page Features Define Dynamical Systems Using Complex-Valued Neural Networks
SpecAugmentPyTorch - A Pytorch (support batch and channel) implementation of GoogleBrain's SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
SpecAugment An implementation of SpecAugment for Pytorch How to use Install pytorch, version=1.9.0 (new feature (torch.Tensor.take_along_dim) is used
A minimal implementation of Gaussian process regression in PyTorch
pytorch-minimal-gaussian-process In search of truth, simplicity is needed. There exist heavy-weighted libraries, but as you know, we need to go bare b
SOTA easy to use PyTorch-based DL training library
Easily train or fine-tune SOTA computer vision models from one training repository. SuperGradients Introduction Welcome to SuperGradients, a free open
“Robust Lightweight Facial Expression Recognition Network with Label Distribution Training”, AAAI 2021.
EfficientFace Zengqun Zhao, Qingshan Liu, Feng Zhou. "Robust Lightweight Facial Expression Recognition Network with Label Distribution Training". AAAI
View model summaries in PyTorch!
torchinfo (formerly torch-summary) Torchinfo provides information complementary to what is provided by print(your_model) in PyTorch, similar to Tensor
PyTorch Lightning + Hydra. A feature-rich template for rapid, scalable and reproducible ML experimentation with best practices. ⚡🔥⚡
Lightning-Hydra-Template A clean and scalable template to kickstart your deep learning project 🚀 ⚡ 🔥 Click on Use this template to initialize new re
A library for uncertainty quantification based on PyTorch
Torchuq [logo here] TorchUQ is an extensive library for uncertainty quantification (UQ) based on pytorch. TorchUQ currently supports 10 representation
The codebase for Data-driven general-purpose voice activity detection.
Data driven GPVAD Repository for the work in TASLP 2021 Voice activity detection in the wild: A data-driven approach using teacher-student training. S
PyTorch Implementation of SSTNs for hyperspectral image classifications from the IEEE T-GRS paper "Spectral-Spatial Transformer Network for Hyperspectral Image Classification: A FAS Framework."
PyTorch Implementation of SSTN for Hyperspectral Image Classification Paper links: SSTN published on IEEE T-GRS. Also, you can directly find the imple
Official PyTorch implementation of "Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble" (NeurIPS'21)
Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble This is the code for reproducing the results of the paper Uncertainty-Bas
Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data
Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data
A state-of-the-art semi-supervised method for image recognition
Mean teachers are better role models Paper ---- NIPS 2017 poster ---- NIPS 2017 spotlight slides ---- Blog post By Antti Tarvainen, Harri Valpola (The
A PyTorch-based Semi-Supervised Learning (SSL) Codebase for Pixel-wise (Pixel) Vision Tasks
PixelSSL is a PyTorch-based semi-supervised learning (SSL) codebase for pixel-wise (Pixel) vision tasks. The purpose of this project is to promote the
Learning Saliency Propagation for Semi-supervised Instance Segmentation
Learning Saliency Propagation for Semi-supervised Instance Segmentation PyTorch Implementation This repository contains: the PyTorch implementation of
Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations, CVPR 2019 (Oral)
Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations The code of: Weakly Supervised Learning of Instance Segmentation with I
Adversarial Learning for Semi-supervised Semantic Segmentation, BMVC 2018
Adversarial Learning for Semi-supervised Semantic Segmentation This repo is the pytorch implementation of the following paper: Adversarial Learning fo
PyTorch implementation of Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose
Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose Release Notes The official PyTorch implementation of Neural View S
A PyTorch implementation of Deep SAD, a deep Semi-supervised Anomaly Detection method.
Deep SAD: A Method for Deep Semi-Supervised Anomaly Detection This repository provides a PyTorch implementation of the Deep SAD method presented in ou
PyTorch implementation of the Flow Gaussian Mixture Model (FlowGMM) model from our paper
Flow Gaussian Mixture Model (FlowGMM) This repository contains a PyTorch implementation of the Flow Gaussian Mixture Model (FlowGMM) model from our pa
PyTorch implementation for Graph Contrastive Learning with Augmentations
Graph Contrastive Learning with Augmentations PyTorch implementation for Graph Contrastive Learning with Augmentations [poster] [appendix] Yuning You*
SimulLR - PyTorch Implementation of SimulLR
PyTorch Implementation of SimulLR There is an interesting work[1] about simultan
Memory-efficient optimum einsum using opt_einsum planning and PyTorch kernels.
opt-einsum-torch There have been many implementations of Einstein's summation. numpy's numpy.einsum is the least efficient one as it only runs in sing
Ecco is a python library for exploring and explaining Natural Language Processing models using interactive visualizations.
Visualize, analyze, and explore NLP language models. Ecco creates interactive visualizations directly in Jupyter notebooks explaining the behavior of Transformer-based language models (like GPT2, BERT, RoBERTA, T5, and T0).
An efficient PyTorch implementation of the evaluation metrics in recommender systems.
recsys_metrics An efficient PyTorch implementation of the evaluation metrics in recommender systems. Overview • Installation • How to use • Benchmark
PyTorch implementation of deep GRAph Contrastive rEpresentation learning (GRACE).
GRACE The official PyTorch implementation of deep GRAph Contrastive rEpresentation learning (GRACE). For a thorough resource collection of self-superv
A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling"
SelfGNN A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which will appear in Th
Pytorch implementation of the paper "COAD: Contrastive Pre-training with Adversarial Fine-tuning for Zero-shot Expert Linking."
Expert-Linking Pytorch implementation of the paper "COAD: Contrastive Pre-training with Adversarial Fine-tuning for Zero-shot Expert Linking." This is
An implementation of Deep Graph Infomax (DGI) in PyTorch
DGI Deep Graph Infomax (Veličković et al., ICLR 2019): https://arxiv.org/abs/1809.10341 Overview Here we provide an implementation of Deep Graph Infom
ncnn is a high-performance neural network inference framework optimized for the mobile platform
ncnn ncnn is a high-performance neural network inference computing framework optimized for mobile platforms. ncnn is deeply considerate about deployme
PyTorch-based framework for Deep Hedging
PFHedge: Deep Hedging in PyTorch PFHedge is a PyTorch-based framework for Deep Hedging. PFHedge Documentation Neural Network Architecture for Efficien
The official pytorch implementation of ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Bias
ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Bias Introduction | Updates | Usage | Results&Pretrained Models | Statement | Intr
Official implementation of CATs: Cost Aggregation Transformers for Visual Correspondence NeurIPS'21
CATs: Cost Aggregation Transformers for Visual Correspondence NeurIPS'21 For more information, check out the paper on [arXiv]. Training with different
Pytorch implementation of SELF-ATTENTIVE VAD, ICASSP 2021
SELF-ATTENTIVE VAD: CONTEXT-AWARE DETECTION OF VOICE FROM NOISE (ICASSP 2021) Pytorch implementation of SELF-ATTENTIVE VAD | Paper | Dataset Yong Rae
LAVT: Language-Aware Vision Transformer for Referring Image Segmentation
LAVT: Language-Aware Vision Transformer for Referring Image Segmentation Where we are ? 12.27 目前和原论文仍有1%左右得差距,但已经力压很多SOTA了 ckpt__448_epoch_25.pth mIoU
OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them to be searched
OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them to be searched or copy-pasted. ocrmypdf
Scalable and Elastic Deep Reinforcement Learning Using PyTorch. Please star. 🔥
ElegantRL “小雅”: Scalable and Elastic Deep Reinforcement Learning ElegantRL is developed for researchers and practitioners with the following advantage
Bianace Prediction Pytorch Model
Bianace Prediction Pytorch Model Main Results ETHUSDT from 2021-01-01 00:00:00 t
Highlight Translator can help you translate the words quickly and accurately.
Highlight Translator can help you translate the words quickly and accurately. By only highlighting, copying, or screenshoting the content you want to translate anywhere on your computer (ex. PDF, PPT, WORD etc.), the translated results will then be automatically displayed before you.
This wrapper now has async support, its basically the same except it uses asyncio
This is a python wrapper for my api api_url = "https://api.dhravya.me/" This wrapper now has async support, its basically the same except it uses asyn
unofficial pytorch implement of "Squareplus: A Softplus-Like Algebraic Rectifier"
SquarePlus (Pytorch implement) unofficial pytorch implement of "Squareplus: A Softplus-Like Algebraic Rectifier" SquarePlus Squareplus is a Softplus-L
Unofficial implementation of Google "CutPaste: Self-Supervised Learning for Anomaly Detection and Localization" in PyTorch
CutPaste CutPaste: image from paper Unofficial implementation of Google's "CutPaste: Self-Supervised Learning for Anomaly Detection and Localization"
Catbird is an open source paraphrase generation toolkit based on PyTorch.
Catbird is an open source paraphrase generation toolkit based on PyTorch. Quick Start Requirements and Installation The project is based on PyTorch 1.
The modify PyTorch version of Siam-trackers which are speed-up by TensorRT.
SiamTracker-with-TensorRT The modify PyTorch version of Siam-trackers which are speed-up by TensorRT or ONNX. [Updating...] Examples demonstrating how
🇰🇷 Text to Image in Korean
KoDALLE Utilizing pretrained language model’s token embedding layer and position embedding layer as DALLE’s text encoder. Background Training DALLE mo
Pytorch implementation of Masked Auto-Encoder
Masked Auto-Encoder (MAE) Pytorch implementation of Masked Auto-Encoder: Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, Ross Girshick
Official Pytorch Implementation of 3DV2021 paper: SAFA: Structure Aware Face Animation.
SAFA: Structure Aware Face Animation (3DV2021) Official Pytorch Implementation of 3DV2021 paper: SAFA: Structure Aware Face Animation. Getting Started
Deep Semisupervised Multiview Learning With Increasing Views (IEEE TCYB 2021, PyTorch Code)
Deep Semisupervised Multiview Learning With Increasing Views (ISVN, IEEE TCYB) Peng Hu, Xi Peng, Hongyuan Zhu, Liangli Zhen, Jie Lin, Huaibai Yan, Dez
Pytorch Implementation for (STANet+ and STANet)
Pytorch Implementation for (STANet+ and STANet) V2-Weakly Supervised Visual-Auditory Saliency Detection with Multigranularity Perception (arxiv), pdf:
PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"
SLAPS-GNN This repo contains the implementation of the model proposed in SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks
Official PyTorch Implementation of "Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs". NeurIPS 2020.
Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs This repository is the implementation of SELAR. Dasol Hwang* , Jinyoung Pa
Autoregressive Predictive Coding: An unsupervised autoregressive model for speech representation learning
Autoregressive Predictive Coding This repository contains the official implementation (in PyTorch) of Autoregressive Predictive Coding (APC) proposed
PyTorch implementation for the ICLR 2020 paper "Understanding the Limitations of Variational Mutual Information Estimators"
Smoothed Mutual Information ``Lower Bound'' Estimator PyTorch implementation for the ICLR 2020 paper Understanding the Limitations of Variational Mutu
PyTorch implementation of MoCo: Momentum Contrast for Unsupervised Visual Representation Learning
MoCo: Momentum Contrast for Unsupervised Visual Representation Learning This is a PyTorch implementation of the MoCo paper: @Article{he2019moco, aut
PyTorch implementation of SwAV (Swapping Assignments between Views)
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments This code provides a PyTorch implementation and pretrained models for SwAV
Official PyTorch implementation of the paper "Self-Supervised Relational Reasoning for Representation Learning", NeurIPS 2020 Spotlight.
Official PyTorch implementation of the paper: "Self-Supervised Relational Reasoning for Representation Learning" (2020), Patacchiola, M., and Storkey,
Official Pytorch implementation for AAAI2021 paper (RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning)
RSPNet Official Pytorch implementation for AAAI2021 paper "RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning" [Suppleme
PyTorch code for training MM-DistillNet for multimodal knowledge distillation
There is More than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking with Sound by Distilling Multimodal Knowledge MM-DistillNet is a
A tool combining EasyOCR and LaMa to automatically detect text and replace it with an inpainted background.
EasyLaMa (WIP) This is a tool combining EasyOCR and LaMa to automatically detect text and replace it with an inpainted background. Installation For GP
Pytorch implementation of the AAAI 2022 paper "Cross-Domain Empirical Risk Minimization for Unbiased Long-tailed Classification"
[AAAI22] Cross-Domain Empirical Risk Minimization for Unbiased Long-tailed Classification We point out the overlooked unbiasedness in long-tailed clas
Unofficial PyTorch implementation of Guided Dropout
Unofficial PyTorch implementation of Guided Dropout This is a simple implementation of Guided Dropout for research. We try to reproduce the algorithm
Scene-Text-Detection-and-Recognition (Pytorch)
Scene-Text-Detection-and-Recognition (Pytorch) Competition URL: https://tbrain.t
HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis
HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis Jungil Kong, Jaehyeon Kim, Jaekyoung Bae In our paper, we p
🚀Clone a voice in 5 seconds to generate arbitrary speech in real-time
English | 中文 Features 🌍 Chinese supported mandarin and tested with multiple datasets: aidatatang_200zh, magicdata, aishell3, data_aishell, and etc. ?
PyTorch Implementation for Deep Metric Learning Pipelines
Easily Extendable Basic Deep Metric Learning Pipeline Karsten Roth ([email protected]), Biagio Brattoli ([email protected]) When using thi
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
News December 27: v1.1.0 New loss functions: CentroidTripletLoss and VICRegLoss Mean reciprocal rank + per-class accuracies See the release notes Than
Template repository to build PyTorch projects from source on any version of PyTorch/CUDA/cuDNN.
The Ultimate PyTorch Source-Build Template Translations: 한국어 TL;DR PyTorch built from source can be x4 faster than a naïve PyTorch install. This repos
Attention for PyTorch with Linear Memory Footprint
Attention for PyTorch with Linear Memory Footprint Unofficially implements https://arxiv.org/abs/2112.05682 to get Linear Memory Cost on Attention (+
Hub is a dataset format with a simple API for creating, storing, and collaborating on AI datasets of any size.
Hub is a dataset format with a simple API for creating, storing, and collaborating on AI datasets of any size. The hub data layout enables rapid transformations and streaming of data while training models at scale. Hub is used by Google, Waymo, Red Cross, Oxford University, and Omdena.
轻量级公式 OCR 小工具:一键识别各类公式图片,并转换为 LaTeX 格式
QC-Formula | 青尘公式 OCR 介绍 轻量级开源公式 OCR 小工具:一键识别公式图片,并转换为 LaTeX 格式。 支持从 电脑本地 导入公式图片;(后续版本将支持直接从网页导入图片) 公式图片支持 .png / .jpg / .bmp,大小为 4M 以内均可; 支持印刷体及手写体,前
PyTorch implementation of Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation.
ALiBi PyTorch implementation of Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation. Quickstart Clone this reposit
*ObjDetApp* deploys a pytorch model for object detection
*ObjDetApp* deploys a pytorch model for object detection
Pytorch based library to rank predicted bounding boxes using text/image user's prompts.
pytorch_clip_bbox: Implementation of the CLIP guided bbox ranking for Object Detection. Pytorch based library to rank predicted bounding boxes using t
A human-readable PyTorch implementation of "Self-attention Does Not Need O(n^2) Memory"
memory_efficient_attention.pytorch A human-readable PyTorch implementation of "Self-attention Does Not Need O(n^2) Memory" (Rabe&Staats'21). def effic
Deploy recommendation engines with Edge Computing
RecoEdge: Bringing Recommendations to the Edge A one stop solution to build your recommendation models, train them and, deploy them in a privacy prese
The object detection pipeline is based on Ultralytics YOLOv5
AYOLOv2 The main goal of this repository is to rewrite the object detection pipeline with a better code structure for better portability and adaptabil
PyTorch Implementation of PIXOR: Real-time 3D Object Detection from Point Clouds
PIXOR: Real-time 3D Object Detection from Point Clouds This is a custom implementation of the paper from Uber ATG using PyTorch 1.0. It represents the
PyTorch implementation of the method described in the paper VoiceLoop: Voice Fitting and Synthesis via a Phonological Loop.
VoiceLoop PyTorch implementation of the method described in the paper VoiceLoop: Voice Fitting and Synthesis via a Phonological Loop. VoiceLoop is a n