2008 Repositories
Python segmentation-models Libraries
Neural-Machine-Translation - Implementation of revolutionary machine translation models
Neural Machine Translation Framework: PyTorch Repository contaning my implementa
Covid19-Forecasting - An interactive website that tracks, models and predicts COVID-19 Cases
Covid-Tracker This is an interactive website that tracks, models and predicts CO
S2s2net - Sentinel-2 Super-Resolution Segmentation Network
S2S2Net Sentinel-2 Super-Resolution Segmentation Network Getting started Install
Digitalizing-Prescription-Image - PIRDS - Prescription Image Recognition and Digitalizing System is a OCR make with Tensorflow
Digitalizing-Prescription-Image PIRDS - Prescription Image Recognition and Digit
Federated Learning - Including common test models for federated learning, like CNN, Resnet18 and lstm, controlled by different parser
Federated_Learning 💻 This projest include common test models for federated lear
Using PyTorch Perform intent classification using three different models to see which one is better for this task
Using PyTorch Perform intent classification using three different models to see which one is better for this task
icepickle is to allow a safe way to serialize and deserialize linear scikit-learn models
icepickle It's a cooler way to store simple linear models. The goal of icepickle is to allow a safe way to serialize and deserialize linear scikit-lea
SHAS: Approaching optimal Segmentation for End-to-End Speech Translation
SHAS: Approaching optimal Segmentation for End-to-End Speech Translation In this repo you can find the code of the Supervised Hybrid Audio Segmentatio
PyTorch implementation for the paper Pseudo Numerical Methods for Diffusion Models on Manifolds
Pseudo Numerical Methods for Diffusion Models on Manifolds (PNDM) This repo is the official PyTorch implementation for the paper Pseudo Numerical Meth
Code To Tune or Not To Tune? Zero-shot Models for Legal Case Entailment.
COLIEE 2021 - task 2: Legal Case Entailment This repository contains the code to reproduce NeuralMind's submissions to COLIEE 2021 presented in the pa
Source code of our work: "Benchmarking Deep Models for Salient Object Detection"
SALOD Source code of our work: "Benchmarking Deep Models for Salient Object Detection". In this works, we propose a new benchmark for SALient Object D
Code for our WACV 2022 paper "Hyper-Convolution Networks for Biomedical Image Segmentation"
Hyper-Convolution Networks for Biomedical Image Segmentation Code for our WACV 2022 paper "Hyper-Convolution Networks for Biomedical Image Segmentatio
A python package to fine-tune transformer-based models for named entity recognition (NER).
nerblackbox A python package to fine-tune transformer-based language models for named entity recognition (NER). Resources Source Code: https://github.
This is the replication package for paper submission: Towards Training Reproducible Deep Learning Models.
This is the replication package for paper submission: Towards Training Reproducible Deep Learning Models.
Convert BART models to ONNX with quantization. 3X reduction in size, and upto 3X boost in inference speed
fast-Bart Reduction of BART model size by 3X, and boost in inference speed up to 3X BART implementation of the fastT5 library (https://github.com/Ki6a
KoRean based ELECTRA pre-trained models (KR-ELECTRA) for Tensorflow and PyTorch
KoRean based ELECTRA (KR-ELECTRA) This is a release of a Korean-specific ELECTRA model with comparable or better performances developed by the Computa
A lane detection integrated Real-time Instance Segmentation based on YOLACT (You Only Look At CoefficienTs)
Real-time Instance Segmentation and Lane Detection This is a lane detection integrated Real-time Instance Segmentation based on YOLACT (You Only Look
BASH - Biomechanical Animated Skinned Human
We developed a method animating a statistical 3D human model for biomechanical analysis to increase accessibility for non-experts, like patients, athletes, or designers.
JFB: Jacobian-Free Backpropagation for Implicit Models
JFB: Jacobian-Free Backpropagation for Implicit Models
Learning Visual Words for Weakly-Supervised Semantic Segmentation
[IJCAI 2021] Learning Visual Words for Weakly-Supervised Semantic Segmentation Implementation of IJCAI 2021 paper Learning Visual Words for Weakly-Sup
Datasets and pretrained Models for StyleGAN3 ...
Datasets and pretrained Models for StyleGAN3 ... Dear arfiticial friend, this is a collection of artistic datasets and models that we have put togethe
SGPT: Multi-billion parameter models for semantic search
SGPT: Multi-billion parameter models for semantic search This repository contains code, results and pre-trained models for the paper SGPT: Multi-billi
Blender 3.1 Alpha (and later) PLY importer that correctly loads point clouds (and all PLY models as point clouds)
import-ply-as-verts Blender 3.1 Alpha (and later) PLY importer that correctly loads point clouds (and all PLY models as point clouds) Latest News Mand
Multi-atlas segmentation (MAS) is a promising framework for medical image segmentation
Multi-atlas segmentation (MAS) is a promising framework for medical image segmentation. Generally, MAS methods register multiple atlases, i.e., medical images with corresponding labels, to a target image;
Official code of Retinal Vessel Segmentation with Pixel-wise Adaptive Filters and Consistency Training
Official code of Retinal Vessel Segmentation with Pixel-wise Adaptive Filters and Consistency Training (ISBI 2022)
Pretrained Japanese BERT models
Pretrained Japanese BERT models This is a repository of pretrained Japanese BERT models. The models are available in Transformers by Hugging Face. Mod
The source code for Generating Training Data with Language Models: Towards Zero-Shot Language Understanding.
SuperGen The source code for Generating Training Data with Language Models: Towards Zero-Shot Language Understanding. Requirements Before running, you
Explore extreme compression for pre-trained language models
Code for paper "Exploring extreme parameter compression for pre-trained language models ICLR2022"
The pyrelational package offers a flexible workflow to enable active learning with as little change to the models and datasets as possible
pyrelational is a python active learning library developed by Relation Therapeutics for rapidly implementing active learning pipelines from data management, model development (and Bayesian approximation), to creating novel active learning strategies.
A demo project to elaborate how Machine Learn Models are deployed on production using Flask API
This is a salary prediction website developed with the help of machine learning, this makes prediction of salary on basis of few parameters like interview score, experience test score.
DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image Segmentation
DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image Segmentation By Qing Xu, Wenting Duan and Na He Requirements pytorch==1.1
Posterior temperature optimized Bayesian models for inverse problems in medical imaging
Posterior temperature optimized Bayesian models for inverse problems in medical imaging Max-Heinrich Laves*, Malte Tölle*, Alexander Schlaefer, Sandy
Code Repository for "HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound Classification and Detection"
Hierarchical Token Semantic Audio Transformer Introduction The Code Repository for "HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound
Source code for "Understanding Knowledge Integration in Language Models with Graph Convolutions"
Graph Convolution Simulator (GCS) Source code for "Understanding Knowledge Integration in Language Models with Graph Convolutions" Requirements: PyTor
Image-based Navigation in Real-World Environments via Multiple Mid-level Representations: Fusion Models Benchmark and Efficient Evaluation
Image-based Navigation in Real-World Environments via Multiple Mid-level Representations: Fusion Models Benchmark and Efficient Evaluation This reposi
Event queue (Equeue) dialect is an MLIR Dialect that models concurrent devices in terms of control and structure.
Event Queue Dialect Event queue (Equeue) dialect is an MLIR Dialect that models concurrent devices in terms of control and structure. Motivation The m
Transformers provides thousands of pretrained models to perform tasks on different modalities such as text, vision, and audio.
English | 简体中文 | 繁體中文 | 한국어 State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained models
Official code for paper "ISNet: Costless and Implicit Image Segmentation for Deep Classifiers, with Application in COVID-19 Detection"
Official code for paper "ISNet: Costless and Implicit Image Segmentation for Deep Classifiers, with Application in COVID-19 Detection". LRPDenseNet.py
Pytorch Implementation for Dilated Continuous Random Field
DilatedCRF Pytorch implementation for fully-learnable DilatedCRF. If you find my work helpful, please consider our paper: @article{Mo2022dilatedcrf,
This repository contains the implementation of the paper Contrastive Instance Association for 4D Panoptic Segmentation using Sequences of 3D LiDAR Scans
Contrastive Instance Association for 4D Panoptic Segmentation using Sequences of 3D LiDAR Scans This repository contains the implementation of the pap
Source code for EquiDock: Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking (ICLR 2022)
Source code for EquiDock: Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking (ICLR 2022) Please cite "Independent SE(3)-Equivar
This repository provides an efficient PyTorch-based library for training deep models.
An Efficient Library for Training Deep Models This repository provides an efficient PyTorch-based library for training deep models. Installation Make
Trafffic prediction analysis using hybrid models - Machine Learning
Hybrid Machine learning Model Clone the Repository Create a new Directory as assests and download the model from the below link Model Link To Start th
Tensorflow2 Keras-based Semantic Segmentation Models Implementation
Tensorflow2 Keras-based Semantic Segmentation Models Implementation
NeuralForecast is a Python library for time series forecasting with deep learning models
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.
Customers Segmentation with RFM Scores and K-means
Customer Segmentation with RFM Scores and K-means RFM Segmentation table: K-Means Clustering: Business Problem Rule-based customer segmentation machin
CT Based COVID 19 Diagnose by Image Processing and Deep Learning
This project proposed the deep learning and image processing method to undertake the diagnosis on 2D CT image and 3D CT volume.
FishNet: One Stage to Detect, Segmentation and Pose Estimation
FishNet FishNet: One Stage to Detect, Segmentation and Pose Estimation Introduction In this project, we combine target detection, instance segmentatio
Natural language processing summarizer using 3 state of the art Transformer models: BERT, GPT2, and T5
NLP-Summarizer Natural language processing summarizer using 3 state of the art Transformer models: BERT, GPT2, and T5 This project aimed to provide in
CRF-RNN for Semantic Image Segmentation - PyTorch version
This repository contains the official PyTorch implementation of the "CRF-RNN" semantic image segmentation method, published in the ICCV 2015
A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.
Probabilistic U-Net + **Update** + An improved Model (the Hierarchical Probabilistic U-Net) + LIDC crops is now available. See below. Re-implementatio
CCP dataset from Clothing Co-Parsing by Joint Image Segmentation and Labeling
Clothing Co-Parsing (CCP) Dataset Clothing Co-Parsing (CCP) dataset is a new clothing database including elaborately annotated clothing items. 2, 098
A collection of pre-trained StyleGAN2 models trained on different datasets at different resolution.
Awesome Pretrained StyleGAN2 A collection of pre-trained StyleGAN2 models trained on different datasets at different resolution. Note the readme is a
A curated list of Generative Deep Art projects, tools, artworks, and models
Generative Deep Art A curated list of Generative Deep Art projects, tools, artworks, and models Inbox Get started with making AI art in 2022 – deeplea
YOLOv7 - Framework Beyond Detection
🔥🔥🔥🔥 YOLO with Transformers and Instance Segmentation, with TensorRT acceleration! 🔥🔥🔥
Semantic Segmentation Architectures Implemented in PyTorch
pytorch-semseg Semantic Segmentation Algorithms Implemented in PyTorch This repository aims at mirroring popular semantic segmentation architectures i
Semantic Segmentation Suite in TensorFlow
Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!
Evaluation framework for testing segmentation networks in PyTorch
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
Image Segmentation and Object Detection in Pytorch Pytorch-Segmentation-Detection is a library for image segmentation and object detection with report
This project aims at providing a concise, easy-to-use, modifiable reference implementation for semantic segmentation models using PyTorch.
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 models, training/inference code, and trained weights, implemented in PyTorch
Human-Segmentation-PyTorch Human segmentation models, training/inference code, and trained weights, implemented in PyTorch. Supported networks UNet: b
Example of semantic segmentation in Keras
keras-semantic-segmentation-example Example of semantic segmentation in Keras Single class example: Generated data: random ellipse with random color o
Javascript image annotation tool based on image segmentation.
JS Segment Annotator Javascript image annotation tool based on image segmentation. Label image regions with mouse. Written in vanilla Javascript, with
Thresholding-and-masking-using-OpenCV - Image Thresholding is used for image segmentation
Image Thresholding is used for image segmentation. From a grayscale image, thresholding can be used to create binary images. In thresholding we pick a threshold T.
Sematic-Segmantation - Semantic Segmentation on MIT ADE20K dataset in PyTorch
Semantic Segmentation on MIT ADE20K dataset in PyTorch This is a PyTorch impleme
Mae segmentation - Reproduction of semantic segmentation using masked autoencoder (mae)
ADE20k Semantic segmentation with MAE Getting started Install the mmsegmentation
Real-time domain adaptation for semantic segmentation
Advanced-Machine-Learning This repository contains the code for the project Real
Machine Learning Models were applied to predict the mass of the brain based on gender, age ranges, and head size.
Brain Weight in Humans Variations of head sizes and brain weights in humans Kaggle dataset obtained from this link by Anubhab Swain. Image obtained fr
The official code repo of "HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound Classification and Detection"
Hierarchical Token Semantic Audio Transformer Introduction The Code Repository for "HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound
This is an early in-development version of training CLIP models with hivemind.
A transformer that does not hog your GPU memory This is an early in-development codebase: if you want a stable and documented hivemind codebase, look
The code uses SegFormer for Semantic Segmentation on Drone Dataset.
SegFormer_Segmentation The code uses SegFormer for Semantic Segmentation on Drone Dataset. The details for the SegFormer can be obtained from the foll
Constrained Language Models Yield Few-Shot Semantic Parsers
Constrained Language Models Yield Few-Shot Semantic Parsers This repository contains tools and instructions for reproducing the experiments in the pap
Code for You Only Cut Once: Boosting Data Augmentation with a Single Cut
You Only Cut Once (YOCO) YOCO is a simple method/strategy of performing augmenta
Supervised Sliding Window Smoothing Loss Function Based on MS-TCN for Video Segmentation
SSWS-loss_function_based_on_MS-TCN Supervised Sliding Window Smoothing Loss Function Based on MS-TCN for Video Segmentation Supervised Sliding Window
This GitHub repo consists of Code and Some results of project- Diabetes Treatment using Gold nanoparticles. These Consist of ML Models used for prediction Diabetes and further the basic theory and working of Gold nanoparticles.
GoldNanoparticles This GitHub repo consists of Code and Some results of project- Diabetes Treatment using Gold nanoparticles. These Consist of ML Mode
spaCy-wrap: For Wrapping fine-tuned transformers in spaCy pipelines
spaCy-wrap: For Wrapping fine-tuned transformers in spaCy pipelines spaCy-wrap is minimal library intended for wrapping fine-tuned transformers from t
DFFNet: An IoT-perceptive Dual Feature Fusion Network for General Real-time Semantic Segmentation
DFFNet Paper DFFNet: An IoT-perceptive Dual Feature Fusion Network for General Real-time Semantic Segmentation. Xiangyan Tang, Wenxuan Tu, Keqiu Li, J
Codes and models for the paper "Learning Unknown from Correlations: Graph Neural Network for Inter-novel-protein Interaction Prediction".
GNN_PPI Codes and models for the paper "Learning Unknown from Correlations: Graph Neural Network for Inter-novel-protein Interaction Prediction". Lear
In this workshop we will be exploring NLP state of the art transformers, with SOTA models like T5 and BERT, then build a model using HugginFace transformers framework.
Transformers are all you need In this workshop we will be exploring NLP state of the art transformers, with SOTA models like T5 and BERT, then build a
This is the source code of the 1st place solution for segmentation task (with Dice 90.32%) in 2021 CCF BDCI challenge.
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 (
Computer Vision Paper Reviews with Key Summary of paper, End to End Code Practice and Jupyter Notebook converted papers
Computer-Vision-Paper-Reviews Computer Vision Paper Reviews with Key Summary along Papers & Codes. Jonathan Choi 2021 The repository provides 100+ Pap
Deep ViT Features as Dense Visual Descriptors
dino-vit-features [paper] [project page] Official implementation of the paper "Deep ViT Features as Dense Visual Descriptors". We demonstrate the effe
Training DiffWave using variational method from Variational Diffusion Models.
Variational DiffWave Training DiffWave using variational method from Variational Diffusion Models. Quick Start python train_distributed.py discrete_10
Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners
DART Implementation for ICLR2022 paper Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners. Environment [email protected] Use pi
BaseCls BaseCls 是一个基于 MegEngine 的预训练模型库,帮助大家挑选或训练出更适合自己科研或者业务的模型结构
BaseCls BaseCls 是一个基于 MegEngine 的预训练模型库,帮助大家挑选或训练出更适合自己科研或者业务的模型结构。 文档地址:https://basecls.readthedocs.io 安装 安装环境 BaseCls 需要 Python = 3.6。 BaseCls 依赖 M
This is the code repository for the paper A hierarchical semantic segmentation framework for computer-vision-based bridge column damage detection
Bridge-damage-segmentation This is the code repository for the paper A hierarchical semantic segmentation framework for computer-vision-based bridge c
Goal of the project : Detecting Temporal Boundaries in Sign Language videos
MVA RecVis course final project : Goal of the project : Detecting Temporal Boundaries in Sign Language videos. Sign language automatic indexing is an
NaturalCC is a sequence modeling toolkit that allows researchers and developers to train custom models
NaturalCC NaturalCC is a sequence modeling toolkit that allows researchers and developers to train custom models for many software engineering tasks,
smc.covid is an R package related to the paper A sequential Monte Carlo approach to estimate a time varying reproduction number in infectious disease models: the COVID-19 case by Storvik et al
smc.covid smc.covid is an R package related to the paper A sequential Monte Carlo approach to estimate a time varying reproduction number in infectiou
An Approach to Explore Logistic Regression Models
User-centered Regression An Approach to Explore Logistic Regression Models This tool applies the potential of Attribute-RadViz in identifying correlat
This repository contains the code for TABS, a 3D CNN-Transformer hybrid automated brain tissue segmentation algorithm using T1w structural MRI scans
This repository contains the code for TABS, a 3D CNN-Transformer hybrid automated brain tissue segmentation algorithm using T1w structural MRI scans. TABS relies on a Res-Unet backbone, with a Vision Transformer embedded between the encoder and decoder layers.
SegTransVAE: Hybrid CNN - Transformer with Regularization for medical image segmentation
SegTransVAE: Hybrid CNN - Transformer with Regularization for medical image segmentation This repo is the official implementation for SegTransVAE. Seg
The open-source and free to use Python package miseval was developed to establish a standardized medical image segmentation evaluation procedure
miseval: a metric library for Medical Image Segmentation EVALuation The open-source and free to use Python package miseval was developed to establish
Python code for the paper How to scale hyperparameters for quickshift image segmentation
How to scale hyperparameters for quickshift image segmentation Python code for the paper How to scale hyperparameters for quickshift image segmentatio
Official repository for the paper "On Evaluation Metrics for Graph Generative Models"
On Evaluation Metrics for Graph Generative Models Authors: Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham Taylor This is the offic
This is the source code for the experiments related to the paper Unsupervised Audio Source Separation Using Differentiable Parametric Source Models
Unsupervised Audio Source Separation Using Differentiable Parametric Source Models This is the source code for the experiments related to the paper Un
coldcuts is an R package to automatically generate and plot segmentation drawings in R
coldcuts coldcuts is an R package that allows you to draw and plot automatically segmentations from 3D voxel arrays. The name is inspired by one of It
Do Neural Networks for Segmentation Understand Insideness?
This is part of the code to reproduce the results of the paper Do Neural Networks for Segmentation Understand Insideness? [pdf] by K. Villalobos (*),
Pytorch Implementation of Auto-Compressing Subset Pruning for Semantic Image Segmentation
Pytorch Implementation of Auto-Compressing Subset Pruning for Semantic Image Segmentation Introduction ACoSP is an online pruning algorithm that compr
PyTorch implementation of our paper How robust are discriminatively trained zero-shot learning models?
How robust are discriminatively trained zero-shot learning models? This repository contains the PyTorch implementation of our paper How robust are dis