277 Repositories
Python earthquake-datasets Libraries
Implementation of the ivis algorithm as described in the paper Structure-preserving visualisation of high dimensional single-cell datasets.
Implementation of the ivis algorithm as described in the paper Structure-preserving visualisation of high dimensional single-cell datasets.
PyTorch implementation of Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets
Simple PyTorch Implementation of "Grokking" Implementation of Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets Usage Running
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
AI Fairness 360 (AIF360) The AI Fairness 360 toolkit is an extensible open-source library containg techniques developed by the research community to h
The implementation for paper Joint t-SNE for Comparable Projections of Multiple High-Dimensional Datasets.
Joint t-sne This is the implementation for paper Joint t-SNE for Comparable Projections of Multiple High-Dimensional Datasets. abstract: We present Jo
PyTorch toolkit for biomedical imaging
farabio is a minimal PyTorch toolkit for out-of-the-box deep learning support in biomedical imaging. For further information, see Wikis and Docs.
A prototype COG-based tile server for sparse Mars datasets
Mars tiler Mars Tiler is a prototype web application that serves tiles from cloud-optimized GeoTIFFs, with an emphasis on supporting planetary dataset
Sorce code and datasets for "K-BERT: Enabling Language Representation with Knowledge Graph",
K-BERT Sorce code and datasets for "K-BERT: Enabling Language Representation with Knowledge Graph", which is implemented based on the UER framework. R
PLUR is a collection of source code datasets suitable for graph-based machine learning.
PLUR (Programming-Language Understanding and Repair) is a collection of source code datasets suitable for graph-based machine learning. We provide scripts for downloading, processing, and loading the datasets. This is done by offering a unified API and data structures for all datasets.
Re-implementation of 'Grokking: Generalization beyond overfitting on small algorithmic datasets'
Re-implementation of the paper 'Grokking: Generalization beyond overfitting on small algorithmic datasets' Paper Original paper can be found here Data
Open source annotation tool for machine learning practitioners.
doccano doccano is an open source text annotation tool for humans. It provides annotation features for text classification, sequence labeling and sequ
Optimizing Deeper Transformers on Small Datasets
DT-Fixup Optimizing Deeper Transformers on Small Datasets Paper published in ACL 2021: arXiv Detailed instructions to replicate our results in the pap
Label Studio is a multi-type data labeling and annotation tool with standardized output format
Website • Docs • Twitter • Join Slack Community What is Label Studio? Label Studio is an open source data labeling tool. It lets you label data types
Automatic earthquake catalog building workflow: EQTransformer + Siamese EQTransformer + PickNet + REAL + HypoInverse
Automatic regional-scale earthquake catalog building workflow: EQTransformer + Siamese EQTransforme
DALLE-tools provided useful dataset utilities to improve you workflow with WebDatasets.
DALLE tools DALLE-tools is a github repository with useful tools to categorize, annotate or check the sanity of your datasets. Installation Just clone
Datasets, Transforms and Models specific to Computer Vision
vision Datasets, Transforms and Models specific to Computer Vision Installation First install the nightly version of OneFlow python3 -m pip install on
A benchmark dataset for emulating atmospheric radiative transfer in weather and climate models with machine learning (NeurIPS 2021 Datasets and Benchmarks Track)
ClimART - A Benchmark Dataset for Emulating Atmospheric Radiative Transfer in Weather and Climate Models Official PyTorch Implementation Using deep le
Traditional Chinese Text Recognition Dataset: Synthetic Dataset and Labeled Data
Traditional Chinese Text Recognition Dataset: Synthetic Dataset and Labeled Data Authors: Yi-Chang Chen, Yu-Chuan Chang, Yen-Cheng Chang and Yi-Ren Ye
Experimenting with computer vision techniques to generate annotated image datasets from gameplay recordings automatically.
Experimenting with computer vision techniques to generate annotated image datasets from gameplay recordings automatically. The collected data will then be used to train a deep neural network that can detect enemy player models in real time, during gameplay. Finally, a virtual input device will adjust the player's crosshair based on live detections for greater accuracy.
Veri Setinizi Yolov5 Formatına Dönüştürün
Veri Setinizi Yolov5 Formatına Dönüştürün! Bu Repo da Neler Var? Xml Formatındaki Veri Setini .Txt Formatına Çevirme Xml Formatındaki Dosyaları Silme
Metrics to evaluate quality and efficacy of synthetic datasets.
An Open Source Project from the Data to AI Lab, at MIT Metrics for Synthetic Data Generation Projects Website: https://sdv.dev Documentation: https://
NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.
NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.
VGGVox models for Speaker Identification and Verification trained on the VoxCeleb (1 & 2) datasets
VGGVox models for speaker identification and verification This directory contains code to import and evaluate the speaker identification and verificat
Data imputations library to preprocess datasets with missing data
Impyute is a library of missing data imputation algorithms. This library was designed to be super lightweight, here's a sneak peak at what impyute can do.
An implementation of the largeVis algorithm for visualizing large, high-dimensional datasets, for R
largeVis This is an implementation of the largeVis algorithm described in (https://arxiv.org/abs/1602.00370). It also incorporates: A very fast algori
This toolkit provides codes to download and pre-process the SLUE datasets, train the baseline models, and evaluate SLUE tasks.
slue-toolkit We introduce Spoken Language Understanding Evaluation (SLUE) benchmark. This toolkit provides codes to download and pre-process the SLUE
Deep Learning with PyTorch made easy 🚀 !
Deep Learning with PyTorch made easy 🚀 ! Carefree? carefree-learn aims to provide CAREFREE usages for both users and developers. It also provides a c
NeurIPS 2021 Datasets and Benchmarks Track
AP-10K: A Benchmark for Animal Pose Estimation in the Wild Introduction | Updates | Overview | Download | Training Code | Key Questions | License Intr
Python: Wrangled and unpivoted gaming datasets. Tableau: created dashboards - Market Beacon and Player’s Shopping Guide.
Created two information products for GameStop. Using Python, wrangled and unpivoted datasets, and created Tableau dashboards.
Neurons Dataset API - The official dataloader and visualization tools for Neurons Datasets.
Neurons Dataset API - The official dataloader and visualization tools for Neurons Datasets. Introduction We propose our dataloader API for loading and
SHIFT15M: multiobjective large-scale fashion dataset with distributional shifts
[arXiv] The main motivation of the SHIFT15M project is to provide a dataset that contains natural dataset shifts collected from a web service IQON, wh
Learning infinite-resolution image processing with GAN and RL from unpaired image datasets, using a differentiable photo editing model.
Exposure: A White-Box Photo Post-Processing Framework ACM Transactions on Graphics (presented at SIGGRAPH 2018) Yuanming Hu1,2, Hao He1,2, Chenxi Xu1,
Code-free deep segmentation for computational pathology
NoCodeSeg: Deep segmentation made easy! This is the official repository for the manuscript "Code-free development and deployment of deep segmentation
Interactive Web App with Streamlit and Scikit-learn that applies different Classification algorithms to popular datasets
Interactive Web App with Streamlit and Scikit-learn that applies different Classification algorithms to popular datasets Datasets Used: Iris dataset,
STBP is a way to train SNN with datasets by Backward propagation.
Spiking neural network (SNN), compared with depth neural network (DNN), has faster processing speed, lower energy consumption and more biological interpretability, which is expected to approach Strong AI.
Semantic segmentation models, datasets and losses implemented in PyTorch.
Semantic Segmentation in PyTorch Semantic Segmentation in PyTorch Requirements Main Features Models Datasets Losses Learning rate schedulers Data augm
Python dataset creator to construct datasets composed of OpenFace extracted features and Shimmer3 GSR+ Sensor datas
Python dataset creator to construct datasets composed of OpenFace extracted features and Shimmer3 GSR+ Sensor datas
Code and datasets for TPAMI 2021
SkeletonNet This repository constains the codes and ShapeNetV1-Surface-Skeleton,ShapNetV1-SkeletalVolume and 2d image datasets ShapeNetRendering. Plea
ACAV100M: Automatic Curation of Large-Scale Datasets for Audio-Visual Video Representation Learning. In ICCV, 2021.
ACAV100M: Automatic Curation of Large-Scale Datasets for Audio-Visual Video Representation Learning This repository contains the code for our ICCV 202
ObjTables: Tools for creating and reusing high-quality spreadsheets
ObjTables: Tools for creating and reusing high-quality spreadsheets ObjTables is a toolkit which makes it easy to use spreadsheets (e.g., XLSX workboo
Replication Package for "An Empirical Study of the Effectiveness of an Ensemble of Stand-alone Sentiment Detection Tools for Software Engineering Datasets"
Replication Package for "An Empirical Study of the Effectiveness of an Ensemble of Stand-alone Sentiment Detection Tools for Software Engineering Data
Source code for the paper: Variance-Aware Machine Translation Test Sets (NeurIPS 2021 Datasets and Benchmarks Track)
Variance-Aware-MT-Test-Sets Variance-Aware Machine Translation Test Sets License See LICENSE. We follow the data licensing plan as the same as the WMT
Understanding the Effects of Datasets Characteristics on Offline Reinforcement Learning
Understanding the Effects of Datasets Characteristics on Offline Reinforcement Learning Kajetan Schweighofer1, Markus Hofmarcher1, Marius-Constantin D
An implementation of a discriminant function over a normal distribution to help classify datasets.
CS4044D Machine Learning Assignment 1 By Dev Sony, B180297CS The question, report and source code can be found here. Github Repo Solution 1 Based on t
face2comics by Sxela (Alex Spirin) - face2comics datasets
This is a paired face to comics dataset, which can be used to train pix2pix or similar networks.
A non-linear, non-parametric Machine Learning method capable of modeling complex datasets
Fast Symbolic Regression Symbolic Regression is a non-linear, non-parametric Machine Learning method capable of modeling complex data sets. fastsr aim
Datasets and source code for our paper Webly Supervised Fine-Grained Recognition: Benchmark Datasets and An Approach
Introduction Datasets and source code for our paper Webly Supervised Fine-Grained Recognition: Benchmark Datasets and An Approach Datasets: WebFG-496
An unofficial personal implementation of UM-Adapt, specifically to tackle joint estimation of panoptic segmentation and depth prediction for autonomous driving datasets.
Semisupervised Multitask Learning This repository is an unofficial and slightly modified implementation of UM-Adapt[1] using PyTorch. This code primar
Python tools for querying and manipulating BIDS datasets.
PyBIDS is a Python library to centralize interactions with datasets conforming BIDS (Brain Imaging Data Structure) format.
RLDS stands for Reinforcement Learning Datasets
RLDS RLDS stands for Reinforcement Learning Datasets and it is an ecosystem of tools to store, retrieve and manipulate episodic data in the context of
[NeurIPS 2021] Well-tuned Simple Nets Excel on Tabular Datasets
[NeurIPS 2021] Well-tuned Simple Nets Excel on Tabular Datasets Introduction This repo contains the source code accompanying the paper: Well-tuned Sim
This repository has datasets containing information of Uber pickups in NYC from April 2014 to September 2014 and January to June 2015. data Analysis , virtualization and some insights are gathered here
uber-pickups-analysis Data Source: https://www.kaggle.com/fivethirtyeight/uber-pickups-in-new-york-city Information about data set The dataset contain
Active Learning demo using two small datasets
ActiveLearningDemo How to run step one put the dataset folder and use command below to split the dataset to the required structure run utils.py For ea
STS Benchmark comprises a selection of the English datasets used in the STS tasks organized in the context of SemEval between 2012 and 2017. The selection of datasets include text from image captions, news headlines and user forums.
stsb_multi_mt_en STS Benchmark comprises a selection of the English datasets used in the STS tasks organized in the context of SemEval between 2012 an
Instant search for and access to many datasets in Pyspark.
SparkDataset Provides instant access to many datasets right from Pyspark (in Spark DataFrame structure). Drop a star if you like the project. 😃 Motiv
this repository has datasets containing information of Uber pickups in NYC from April 2014 to September 2014 and January to June 2015. data Analysis , virtualization and some insights are gathered here
uber-pickups-analysis Data Source: https://www.kaggle.com/fivethirtyeight/uber-pickups-in-new-york-city Information about data set The dataset contain
A tutorial for people to run synthetic data replica's from source healthcare datasets
Synthetic-Data-Replica-for-Healthcare Description What is this? A tailored hands-on tutorial showing how to use Python to create synthetic data replic
Official Datasets and Implementation from our Paper "Video Class Agnostic Segmentation in Autonomous Driving".
Video Class Agnostic Segmentation [Method Paper] [Benchmark Paper] [Project] [Demo] Official Datasets and Implementation from our Paper "Video Class A
HW 2: Visualizing interesting datasets
HW 2: Visualizing interesting datasets Check out the project instructions here! Mean Earnings per Hour for Males and Females My first graph uses data
Asterisk is a framework to generate high-quality training datasets at scale
Asterisk is a framework to generate high-quality training datasets at scale
A dataset handling library for computer vision datasets in LOST-fromat
A dataset handling library for computer vision datasets in LOST-fromat
HM02: Visualizing Interesting Datasets
HM02: Visualizing Interesting Datasets This is a homework assignment for CSCI 40 class at Claremont McKenna College. Go to the project page to learn m
🎵 A repository for manually annotating files to create labeled acoustic datasets for machine learning.
🎵 A repository for manually annotating files to create labeled acoustic datasets for machine learning.
Web app for keeping track of buildings in danger of collapsing in the event of an earthquake
Bulina Roșie 🇷🇴 Un cutremur în București nu este o situație ipotetică. Este o certitudine că acest lucru se va întâmpla. În acest context, la mai bi
Efficient Training of Visual Transformers with Small Datasets
Official codes for "Efficient Training of Visual Transformers with Small Datasets", NerIPS 2021.
Repo for "Physion: Evaluating Physical Prediction from Vision in Humans and Machines" submission to NeurIPS 2021 (Datasets & Benchmarks track)
Physion: Evaluating Physical Prediction from Vision in Humans and Machines This repo contains code and data to reproduce the results in our paper, Phy
an elegant datasets factory
rawbuilder an elegant datasets factory Free software: MIT license Documentation: https://rawbuilder.readthedocs.io. Features Schema oriented datasets
Extremely simple and fast extreme multi-class and multi-label classifiers.
napkinXC napkinXC is an extremely simple and fast library for extreme multi-class and multi-label classification, that focus of implementing various m
Code and datasets for the paper "KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction"
KnowPrompt Code and datasets for our paper "KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction" Requireme
Pytorch implementation for "Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets" (ECCV 2020 Spotlight)
Distribution-Balanced Loss [Paper] The implementation of our paper Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets (
QuakeLabeler is a Python package to create and manage your seismic training data, processes, and visualization in a single place — so you can focus on building the next big thing.
QuakeLabeler Quake Labeler was born from the need for seismologists and developers who are not AI specialists to easily, quickly, and independently bu
The "breathing k-means" algorithm with datasets and example notebooks
The Breathing K-Means Algorithm (with examples) The Breathing K-Means is an approximation algorithm for the k-means problem that (on average) is bette
Glue is a python project to link visualizations of scientific datasets across many files.
Glue Glue is a python project to link visualizations of scientific datasets across many files. Click on the image for a quick demo: Features Interacti
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
Tensor2Tensor Tensor2Tensor, or T2T for short, is a library of deep learning models and datasets designed to make deep learning more accessible and ac
The first online catalogue for Arabic NLP datasets.
Masader The first online catalogue for Arabic NLP datasets. This catalogue contains 200 datasets with more than 25 metadata annotations for each datas
Benchmark datasets, data loaders, and evaluators for graph machine learning
Overview The Open Graph Benchmark (OGB) is a collection of benchmark datasets, data loaders, and evaluators for graph machine learning. Datasets cover
Datasets accompanying the paper ConditionalQA: A Complex Reading Comprehension Dataset with Conditional Answers.
ConditionalQA Datasets accompanying the paper ConditionalQA: A Complex Reading Comprehension Dataset with Conditional Answers. Disclaimer This dataset
Python Package for DataHerb: create, search, and load datasets.
The Python Package for DataHerb A DataHerb Core Service to Create and Load Datasets.
HyperSpy is an open source Python library for the interactive analysis of multidimensional datasets
HyperSpy is an open source Python library for the interactive analysis of multidimensional datasets that can be described as multidimensional arrays o
Python suite to construct benchmark machine learning datasets from the MIMIC-III clinical database.
MIMIC-III Benchmarks Python suite to construct benchmark machine learning datasets from the MIMIC-III clinical database. Currently, the benchmark data
A set of examples around hub for creating and processing datasets
Examples for Hub - Dataset Format for AI A repository showcasing examples of using Hub Uploading Dataset Places365 Colab Tutorials Notebook Link Getti
TorchXRayVision: A library of chest X-ray datasets and models.
torchxrayvision A library for chest X-ray datasets and models. Including pre-trained models. ( 🎬 promo video about the project) Motivation: While the
A simple recipe for training and inferencing Transformer architecture for Multi-Task Learning on custom datasets. You can find two approaches for achieving this in this repo.
multitask-learning-transformers A simple recipe for training and inferencing Transformer architecture for Multi-Task Learning on custom datasets. You
C++ Implementation of PyTorch Tutorials for Everyone
C++ Implementation of PyTorch Tutorials for Everyone OS (Compiler)\LibTorch 1.9.0 macOS (clang 10.0, 11.0, 12.0) Linux (gcc 8, 9, 10, 11) Windows (msv
Create Fast and easy image datasets using reddit
Reddit-Image-Scraper Reddit Reddit is an American Social news aggregation, web content rating, and discussion website. Reddit has been devided by topi
The tool to make NLP datasets ready to use
chazutsu photo from Kaikado, traditional Japanese chazutsu maker chazutsu is the dataset downloader for NLP. import chazutsu r = chazutsu.data
TorchGeo is a PyTorch domain library, similar to torchvision, that provides datasets, transforms, samplers, and pre-trained models specific to geospatial data.
TorchGeo is a PyTorch domain library, similar to torchvision, that provides datasets, transforms, samplers, and pre-trained models specific to geospatial data.
S3-plugin is a high performance PyTorch dataset library to efficiently access datasets stored in S3 buckets.
S3-plugin is a high performance PyTorch dataset library to efficiently access datasets stored in S3 buckets.
Roboflow makes managing, preprocessing, augmenting, and versioning datasets for computer vision seamless.
Roboflow makes managing, preprocessing, augmenting, and versioning datasets for computer vision seamless. This is the official Roboflow python package that interfaces with the Roboflow API.
This repository contains the official release of the model "BanglaBERT" and associated downstream finetuning code and datasets introduced in the paper titled "BanglaBERT: Combating Embedding Barrier in Multilingual Models for Low-Resource Language Understanding".
BanglaBERT This repository contains the official release of the model "BanglaBERT" and associated downstream finetuning code and datasets introduced i
This python module is an easy-to-use port of the text normalization used in the paper "Not low-resource anymore: Aligner ensembling, batch filtering, and new datasets for Bengali-English machine translation". It is intended to be used for normalizing / cleaning Bengali and English text.
normalizer This python module is an easy-to-use port of the text normalization used in the paper "Not low-resource anymore: Aligner ensembling, batch
An easy way to build PyTorch datasets. Modularly build datasets and automatically cache processed results
EasyDatas An easy way to build PyTorch datasets. Modularly build datasets and automatically cache processed results Installation pip install git+https
TorchIO is a Medical image preprocessing and augmentation toolkit for deep learning. Part of the PyTorch Ecosystem.
Medical image preprocessing and augmentation toolkit for deep learning. Part of the PyTorch Ecosystem.
OpenCVのGrabCut()を利用したセマンティックセグメンテーション向けアノテーションツール(Annotation tool using GrabCut() of OpenCV. It can be used to create datasets for semantic segmentation.)
[Japanese/English] GrabCut-Annotation-Tool GrabCut-Annotation-Tool.mp4 OpenCVのGrabCut()を利用したアノテーションツールです。 セマンティックセグメンテーション向けのデータセット作成にご使用いただけます。 ※Grab
A data annotation pipeline to generate high-quality, large-scale speech datasets with machine pre-labeling and fully manual auditing.
About This repository provides data and code for the paper: Scalable Data Annotation Pipeline for High-Quality Large Speech Datasets Development (subm
Collection of NLP model explanations and accompanying analysis tools
Thermostat is a large collection of NLP model explanations and accompanying analysis tools. Combines explainability methods from the captum library wi
The official repository for our paper "The Devil is in the Detail: Simple Tricks Improve Systematic Generalization of Transformers". We significantly improve the systematic generalization of transformer models on a variety of datasets using simple tricks and careful considerations.
Codebase for training transformers on systematic generalization datasets. The official repository for our EMNLP 2021 paper The Devil is in the Detail:
GraphGT: Machine Learning Datasets for Graph Generation and Transformation
GraphGT: Machine Learning Datasets for Graph Generation and Transformation Dataset Website | Paper Installation Using pip To install the core environm
Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)
This is a playground for pytorch beginners, which contains predefined models on popular dataset. Currently we support mnist, svhn cifar10, cifar100 st
Minimal But Practical Image Classifier Pipline Using Pytorch, Finetune on ResNet18, Got 99% Accuracy on Own Small Datasets.
PyTorch Image Classifier Updates As for many users request, I released a new version of standared pytorch immage classification example at here: http:
Simple tool/toolkit for evaluating NLG (Natural Language Generation) offering various automated metrics.
Simple tool/toolkit for evaluating NLG (Natural Language Generation) offering various automated metrics. Jury offers a smooth and easy-to-use interface. It uses datasets for underlying metric computation, and hence adding custom metric is easy as adopting datasets.Metric.