Python Minimal-Hand-pytorch Resources

Official PyTorch implementation of the paper "Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs Theory (SB-FBSDE)" which introduces a new class of deep generative models that generalizes score-based models to fully nonlinear forward and backward diffusions.

An Efficient Library for Training Deep Models This repository provides an efficient PyTorch-based library for training deep models. Installation Make

APSIPA-TER This code is the implementation of Text Emotion Recognition (TER) with linguistic features. The network model is BERT with a pretrained mod

APSIPA-SER-with-A-and-T This code is the implementation of Speech Emotion Recognition (SER) with acoustic and linguistic features. The network model i

NeuralForecast is a Python library for time series forecasting with deep learning models. It includes benchmark datasets, data-loading utilities, evaluation functions, statistical tests, univariate model benchmarks and SOTA models implemented in PyTorch and PyTorchLightning.

ssnt-loss ℹ️ This is a WIP project. the implementation is still being tested. A pure PyTorch implementation of the loss described in "Online Segment t

Classification using Deep Learning Requirements PyTorch version = 1.9.1+cu111 Python version = 3.8.10 PyTorch-Lightning version = 1.4.9 Huggingface

gramcorrector A simple tutoral for error correction task, based on Pytorch Grammatical Error Detection (sentence-level) a binary sequence-based classi

This repository contains the official PyTorch implementation of the "CRF-RNN" semantic image segmentation method, published in the ICCV 2015

Minimal performant package to asynchronously make GET requests without any dependencies other than asyncio.

Modified StyleGAN3 Repo Changes Made tied to python 3.7 syntax .jpgs instead of .pngs for training sample seeds to recreate the 1024 training grid wit

pixel_character_generator Generating retro pixel game characters with Generative Adversarial Networks. Dataset "TinyHero" included. Dataset TinyHero D

The unified machine learning framework, enabling framework-agnostic functions, layers and libraries. Contents Overview In a Nutshell Where Next? Overv

R-YOLOv4 This is a PyTorch-based R-YOLOv4 implementation which combines YOLOv4 model and loss function from R3Det for arbitrary oriented object detect

Torch Mutable Modules Use in-place and assignment operations on PyTorch module p

openseg.pytorch News 2021/09/14 MMSegmentation has supported our ISANet and refer to ISANet for more details. 2021/08/13 We have released the implemen

pytorch-semseg Semantic Segmentation Algorithms Implemented in PyTorch This repository aims at mirroring popular semantic segmentation architectures i

Evaluation framework for testing segmentation networks in PyTorch. What segmentation network to choose for next Kaggle competition? This benchmark knows the answer!

Image Segmentation and Object Detection in Pytorch Pytorch-Segmentation-Detection is a library for image segmentation and object detection with report

Semantic Segmentation on PyTorch (include FCN, PSPNet, Deeplabv3, Deeplabv3+, DANet, DenseASPP, BiSeNet, EncNet, DUNet, ICNet, ENet, OCNet, CCNet, PSANet, CGNet, ESPNet, LEDNet, DFANet)

Human-Segmentation-PyTorch Human segmentation models, training/inference code, and trained weights, implemented in PyTorch. Supported networks UNet: b

Pytorch implementation of the paper "Enhancing Content Preservation in Text Style Transfer Using Reverse Attention and Conditional Layer Normalization"

SAAVN SAAVN Code release for paper "Sound Adversarial Audio-Visual Navigation,IC

Deep High Dynamic Range Imaging Benchmark This repository is the pytorch impleme

This project proposes a camera vision based cursor control system, using hand moment captured from a webcam through a landmarks of hand by using Mideapipe module

Semantic Segmentation on MIT ADE20K dataset in PyTorch This is a PyTorch impleme

%load_ext memory_profiler Implementing Stochastic Depth/Drop Path In PyTorch DropPath is available on glasses my computer vision library! Introduction

DirectCLR DirectCLR is a simple contrastive learning model for visual representation learning. It does not require a trainable projector as SimCLR. It

Sharpened Cosine Distance PyTorch implementation of the Sharpened Cosine Distanc

traiNNer traiNNer is an open source image and video restoration (super-resolution, denoising, deblurring and others) and image to image translation to

Organic Alkalinity Sausage Machine A Python toolbox to churn out organic alkalinity calculations with minimal brain engagement. Getting started To mak

torch-max-mem This package provides decorators for memory utilization maximization with PyTorch and CUDA by starting with a maximum parameter size and

Graphene Metanode is a locally hosted node for one account and several trading pairs, which uses minimal RAM resources. It provides the necessary user stream data and order book data for trading in a format one would expect from a centralized exchange API.

BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation

LogAvgExp - Pytorch Implementation of LogAvgExp for Pytorch Install $ pip instal

Simple Transformer An implementation of the "Attention is all you need" paper without extra bells and whistles, or difficult syntax. Note: The only ex

Tutorial Repository with a minimal example for showing how to deploy training across various compute infrastructure.

spaCy-wrap: For Wrapping fine-tuned transformers in spaCy pipelines spaCy-wrap is minimal library intended for wrapping fine-tuned transformers from t

Continual Learning With Filter Atom Swapping Pytorch Implementation of Continual Learning With Filter Atom Swapping (ICLR'22 Spolight) Paper If find t

Plant Pathology 2020 FGVC7 Introduction A deep learning model pipeline for training, experimentaiton and deployment for the Kaggle Competition, Plant

1st place solution in CCF BDCI 2021 ULSEG challenge This is the source code of the 1st place solution for ultrasound image angioma segmentation task (

ruCLIP-SB RuCLIP-SB (Russian Contrastive Language–Image Pretraining SWIN-BERT) is a multimodal model for obtaining images and text similarities and re

machine-learning-with-graphs My solutions for Stanford University course CS224W: Machine Learning with Graphs Fall 2021 colabs Course materials can be

🤖 AI Awesome Project Template 👋 Template author You may want to adjust badge links in a README.md file. 💎 Installation with pip Installation is as

dino-vit-features [paper] [project page] Official implementation of the paper "Deep ViT Features as Dense Visual Descriptors". We demonstrate the effe

VRT: A Video Restoration Transformer Jingyun Liang, Jiezhang Cao, Yuchen Fan, Kai Zhang, Rakesh Ranjan, Yawei Li, Radu Timofte, Luc Van Gool Computer

NANSY: Unofficial Pytorch Implementation of Neural Analysis and Synthesis: Reconstructing Speech from Self-Supervised Representations Notice Papers' D

Gesture_recognition The training data consists of a few hundred videos categorised into one of the five classes. Each video (typically 2-3 seconds lon

Retrieval.pytorch - The code we used in [2020 DIGIX]

FedML: A Research Library and Benchmark for Federated Machine Learning 📄 https://arxiv.org/abs/2007.13518 News 2021-02-01 (Award): #NeurIPS 2020# Fed

🕸️ Iris Python Client Minimal Python client for the Iris API, built on top of Authlib and httpx. Installation pip install dioptra-iris-client Usage f

Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks. Code, based on the PyTorch framework, for reprodu

Using Self-Supervised Pretext Tasks for Active Learning - Official Pytorch Implementation Experiment Setting: CIFAR10 (downloaded and saved in ./DATA

Dual-Contrastive-Learning A PyTorch implementation for our paper "Dual Contrastive Learning: Text Classification via Label-Aware Data Augmentation". Y

Visual Representation Learning with Self-Supervised Attention for Low-Label High-Data Regime Created by Prarthana Bhattacharyya. Disclaimer: This is n

PiCO: Contrastive Label Disambiguation for Partial Label Learning This is a PyTorch implementation of ICLR 2022 paper PiCO: Contrastive Label Disambig

AttentionHTR PyTorch implementation of an end-to-end Handwritten Text Recognition (HTR) system based on attention encoder-decoder networks. Scene Text

Neural Architecture Search for Spiking Neural Networks Pytorch implementation code for [Neural Architecture Search for Spiking Neural Networks] (https

Interpretable Control Exploration and Counterfactual Explanation (ICE) on StyleGAN Which Style Makes Me Attractive? Interpretable Control Discovery an

BoxEL: Box EL++ Embedding This is the official pytorch implementation of the BoxEL for the description logic EL++. BoxEL++ is a geometric approach bas

Pearl The Parallel Evolutionary and Reinforcement Learning Library (Pearl) is a pytorch based package with the goal of being excellent for rapid proto

Trainable Bilateral Filter Layer (PyTorch) This repository contains our GPU-accelerated trainable bilateral filter layer (three spatial and one range

DocEnTR Description Pytorch implementation of the paper DocEnTr: An End-to-End Document Image Enhancement Transformer. This model is implemented on to

Ensemble Learning Priors Driven Deep Unfolding for Scalable Snapshot Compressive Imaging [PyTorch] Abstract Snapshot compressive imaging (SCI) can rec

Pytorch Implementation of Auto-Compressing Subset Pruning for Semantic Image Segmentation Introduction ACoSP is an online pruning algorithm that compr

How robust are discriminatively trained zero-shot learning models? This repository contains the PyTorch implementation of our paper How robust are dis

Pgnet There's a improved version compared with the publication in Tgrs with the modification in the deduction of the PDIN block: https://arxiv.org/abs

Beyond ImageNet Attack: Towards Crafting Adversarial Examples for Black-box Domains (ICLR'2022) This is the Pytorch code for our paper Beyond ImageNet

Semantic Segmentation Easy to use and customizable SOTA Semantic Segmentation models with abundant datasets in PyTorch Features Applicable to followin

Interaction Grounded Learning This repository contains a simple PyTorch implementation of the ideas presented in the paper Interaction Grounded Learni

Masked Autoencoders in PyTorch A simple, unofficial implementation of MAE (Masked Autoencoders are Scalable Vision Learners) using pytorch-lightning.

引言 感谢苏神带来的模型，原文地址：https://spaces.ac.cn/archives/8877 如何运行 对应模型EfficientGlobalPoi

On Out-of-distribution Detection with Energy-based Models This repository contains the code for the experiments conducted in the paper On Out-of-distr

PyTorch META-DATASET (Few-shot classification benchmark) This repo contains a PyTorch implementation of meta-dataset and a unified implementation of s

PyTorch IPFS Dataset IPFSDataset(Dataset) See the jupyter notepad to see how it works and how it interacts with a standard pytorch DataLoader You need

LSHFM.detection This is the PyTorch source code for Distilling Knowledge by Mimicking Features. And this project contains code for object detection wi

Emotion AI This is a Deep Leaning API for classifying emotions from human face and human audios. Starting the server To start the server first you nee

Vit-ImageClassification Introduction This project uses ViT to perform image clas

f-BRS: Rethinking Backpropagating Refinement for Interactive Segmentation [Paper] [PyTorch] [MXNet] [Video] This repository provides code for training

XRDidentifier Pytorch implementation of XRD spectral identification from COD database. Details will be explained in the paper to be submitted to NeurI

swin-transformer-ocr ocr with swin-transformer Overview Simple and understandable swin-transformer OCR project. The model in this repository heavily r

ResViT Official Pytorch Implementation of Residual Vision Transformers(ResViT) which is described in the following paper: Onat Dalmaz and Mahmut Yurt

Pyramid Transformer Net (PTNet) Project | Paper Pytorch implementation of PTNet for high-resolution and longitudinal infant MRI synthesis. PTNet: A Hi

Raster Vision is an open source Python framework for building computer vision models on satellite, aerial, and other large imagery sets (including obl

Natural Posterior Network This repository provides the official implementation o

A Memory Tracer For PyTorch OOM is a nightmare for PyTorch users. However, most

HashGrid Encoder (WIP) A pytorch implementation of the HashGrid Encoder from ins

SGPA: Structure-Guided Prior Adaptation for Category-Level 6D Object Pose Estimation This is the PyTorch implemention of ICCV'21 paper SGPA: Structure

These scripts use the Google mediapipe hand tracking solution in combination with a webcam in order to send game instructions to a racing game. It features 2 methods of control

ChatBot-Pytorch A GPT-2 ChatBot implemented using Pytorch and Huggingface-transf

ESGD-M - A stochastic non-convex second order optimizer, suitable for training deep learning models, for PyTorch

Attention Probe: Vision Transformer Distillation in the Wild Jiahao Wang, Mingdeng Cao, Shuwei Shi, Baoyuan Wu, Yujiu Yang In ICASSP 2022 This code is

ImageNet 1K Bounding Boxes For some experiments, you might wanna pass only the background of imagenet images vs passing only the foreground. Here, I'v

Minimal Async KuCoin REST API + WebSocket using trio Coded by π ([email protected] TG: @pipad) 22 January 2022 KuCoin needs an async Python client This cod

sequitur sequitur is a library that lets you create and train an autoencoder for sequential data in just two lines of code. It implements three differ

TGS Salt Identification Challenge This is an open solution to the TGS Salt Identification Challenge. Note Unfortunately, we can no longer provide supp

Airbus Ship Detection Challenge This is an open solution to the Airbus Ship Detection Challenge. Our goals We are building entirely open solution to t

Value Retrieval with Arbitrary Queries for Form-like Documents Introduction Pytorch Implementation of Value Retrieval with Arbitrary Queries for Form-

Pre-trained models based on TensorLayerX. TensorLayerX is a multi-backend AI fra

Fast Forward Computer Vision: train models at a fraction of the cost with accele