4550 Repositories
Python data-framework-semantic-segmentation Libraries
A general, feasible, and extensible framework for classification tasks.
Pytorch Classification A general, feasible and extensible framework for 2D image classification. Features Easy to configure (model, hyperparameters) T
This provides the R code and data to replicate results in "The USS Trustee’s risky strategy"
USSBriefs2021 This provides the R code and data to replicate results in "The USS Trustee’s risky strategy" by Neil M Davies, Jackie Grant and Chin Yan
[NeurIPS-2021] Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data
MosaicKD Code for NeurIPS-21 paper "Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data" 1. Motivation Natural images share common l
BMVC 2021 Oral: code for BI-GCN: Boundary-Aware Input-Dependent Graph Convolution for Biomedical Image Segmentation
BMVC 2021 BI-GConv: Boundary-Aware Input-Dependent Graph Convolution for Biomedical Image Segmentation Necassary Dependencies: PyTorch 1.2.0 Python 3.
Codes and Data Processing Files for our paper.
Code Scripts and Processing Files for EEG Sleep Staging Paper 1. Folder Tree ./src_preprocess (data preprocessing files for SHHS and Sleep EDF) sleepE
[NeurIPS 2021] A weak-shot object detection approach by transferring semantic similarity and mask prior.
TransMaS This repository is the official pytorch implementation of the following paper: NIPS2021 Mixed Supervised Object Detection by TransferringMask
Regularized Frank-Wolfe for Dense CRFs: Generalizing Mean Field and Beyond
CRF - Conditional Random Fields A library for dense conditional random fields (CRFs). This is the official accompanying code for the paper Regularized
Simple data balancing baselines for worst-group-accuracy benchmarks.
BalancingGroups Code to replicate the experimental results from Simple data balancing baselines achieve competitive worst-group-accuracy. Replicating
Contrastive Learning with Non-Semantic Negatives
Contrastive Learning with Non-Semantic Negatives This repository is the official implementation of Robust Contrastive Learning Using Negative Samples
Official project repository for 'Normality-Calibrated Autoencoder for Unsupervised Anomaly Detection on Data Contamination'
NCAE_UAD Official project repository of 'Normality-Calibrated Autoencoder for Unsupervised Anomaly Detection on Data Contamination' Abstract In this p
OneFlow is a performance-centered and open-source deep learning framework.
OneFlow OneFlow is a performance-centered and open-source deep learning framework. Latest News Version 0.5.0 is out! First class support for eager exe
Colossal-AI: A Unified Deep Learning System for Large-Scale Parallel Training
ColossalAI An integrated large-scale model training system with efficient parallelization techniques. arXiv: Colossal-AI: A Unified Deep Learning Syst
An execution framework for systematic strategies
WAGMI is an execution framework for systematic strategies. It is very much a work in progress, please don't expect it to work! Architecture The Django
Data visualization electromagnetic spectrum
Datenvisualisierung-Elektromagnetischen-Spektrum Anhand des Moduls matplotlib sollen die Daten des elektromagnetischen Spektrums dargestellt werden. D
A framework for feature exploration in Data Science
Beehive A framework for feature exploration in Data Science Background What do we do when we finish one episode of feature exploration in a jupyter no
Experimental proxy for dumping the unencrypted packet data from Brawl Stars (WIP)
Brawl Stars Proxy Experimental proxy for version 39.99 of Brawl Stars. It allows you to capture the packets being sent between the Brawl Stars client
DWIPrep is a robust and easy-to-use pipeline for preprocessing of diverse dMRI data.
DWIPrep: A Robust Preprocessing Pipeline for dMRI Data DWIPrep is a robust and easy-to-use pipeline for preprocessing of diverse dMRI data. The transp
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
[NeurIPS-2021] Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data
MosaicKD Code for NeurIPS-21 paper "Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data" 1. Motivation Natural images share common l
Rover is a command line interface application that allows through browse through mission data, images, metadata from the NASA Official Website
🤖 rover Rover is a command line interface application that allows through browse through mission data, images, metadata from the NASA Official Websit
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
Data, model training, and evaluation code for "PubTables-1M: Towards a universal dataset and metrics for training and evaluating table extraction models".
PubTables-1M This repository contains training and evaluation code for the paper "PubTables-1M: Towards a universal dataset and metrics for training a
Spatial Interpolation Toolbox is a Python-based GUI that is able to interpolate spatial data in vector format.
Spatial Interpolation Toolbox This is the home to Spatial Interpolation Toolbox, a graphical user interface (GUI) for interpolating geographic vector
Improving your data science workflows with
Make Better Defaults Author: Kjell Wooding [email protected] This is the git repo for Makefiles: One great trick for making your conda environments mo
Covid-19 Test AI (Deep Learning - NNs) Software. Accuracy is the %96.5, loss is the 0.09 :)
Covid-19 Test AI (Deep Learning - NNs) Software I developed a segmentation algorithm to understand whether Covid-19 Test Photos are positive or negati
A framework for attentive explainable deep learning on tabular data
🧠 kendrite A framework for attentive explainable deep learning on tabular data 💨 Quick start kedro run 🧱 Built upon Technology Description Links ke
Towhee is a flexible machine learning framework currently focused on computing deep learning embeddings over unstructured data.
Towhee is a flexible machine learning framework currently focused on computing deep learning embeddings over unstructured data.
Fast image augmentation library and an easy-to-use wrapper around other libraries
Albumentations Albumentations is a Python library for image augmentation. Image augmentation is used in deep learning and computer vision tasks to inc
Pytorch implementation of Cut-Thumbnail in the paper Cut-Thumbnail:A Novel Data Augmentation for Convolutional Neural Network.
Cut-Thumbnail (Accepted at ACM MULTIMEDIA 2021) Tianshu Xie, Xuan Cheng, Xiaomin Wang, Minghui Liu, Jiali Deng, Tao Zhou, Ming Liu This is the officia
Crawler do site Fundamentus.com com o uso do framework scrapy, tanto da aba detalhada como a de resumo.
Crawler do site Fundamentus.com com o uso do framework scrapy, tanto da aba detalhada como a de resumo. (Todas as infomações)
A simple alarm-clock created using Python and Kivy.
Alarm-Clock made with Python and Kivy. A simple alarm-clock created using Python and Kivy. See the time. Set a maximum of 5 alarms. Cancel alarms. Not
An example of repository data as bundles
Bundles This repository is just an example of how we can host Git bundles in a way that supports fetching data from precomputed bundles without the or
Colossal-AI: A Unified Deep Learning System for Large-Scale Parallel Training
ColossalAI An integrated large-scale model training system with efficient parallelization techniques Installation PyPI pip install colossalai Install
Cool Python features for machine learning that I used to be too afraid to use. Will be updated as I have more time / learn more.
python-is-cool A gentle guide to the Python features that I didn't know existed or was too afraid to use. This will be updated as I learn more and bec
SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data
SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data Au
dragonscales is a highly customizable asynchronous job-scheduler framework
dragonscales 🐉 dragonscales is a highly customizable asynchronous job-scheduler framework. This framework is used to scale the execution of multiple
[NeurIPS 2021] A weak-shot object detection approach by transferring semantic similarity and mask prior.
[NeurIPS 2021] A weak-shot object detection approach by transferring semantic similarity and mask prior.
Simple data balancing baselines for worst-group-accuracy benchmarks.
BalancingGroups Code to replicate the experimental results from Simple data balancing baselines achieve competitive worst-group-accuracy. Replicating
My project contrasts K-Nearest Neighbors and Random Forrest Regressors on Real World data
kNN-vs-RFR My project contrasts K-Nearest Neighbors and Random Forrest Regressors on Real World data In many areas, rental bikes have been launched to
Tool for working with Y-chromosome data from YFull and FTDNA
ycomp ycomp is a tool for working with Y-chromosome data from YFull and FTDNA. Run ycomp -h for information on how to use the program. Installation Th
K-means clustering is a method used for clustering analysis, especially in data mining and statistics.
K Means Algorithm What is K Means This algorithm is an iterative algorithm that partitions the dataset according to their features into K number of pr
Homework 2: Matplotlib and Data Visualization
Homework 2: Matplotlib and Data Visualization Overview These data visualizations were created for my introductory computer science course using Python
Space Time Recurrent Memory Network - Pytorch
Space Time Recurrent Memory Network - Pytorch (wip) Implementation of Space Time Recurrent Memory Network, recurrent network competitive with attentio
PyTorch framework A simple and complete framework for PyTorch, providing a variety of data loading and simple task solutions that are easy to extend and migrate
PyTorch framework A simple and complete framework for PyTorch, providing a variety of data loading and simple task solutions that are easy to extend and migrate
Anomaly Detection Based on Hierarchical Clustering of Mobile Robot Data
We proposed a new approach to detect anomalies of mobile robot data. We investigate each data seperately with two clustering method hierarchical and k-means. There are two sub-method that we used for produce an anomaly score. Then, we merge these two score and produce merged anomaly score as a result.
MultiMix: Sparingly Supervised, Extreme Multitask Learning From Medical Images (ISBI 2021, MELBA 2021)
MultiMix This repository contains the implementation of MultiMix. Our publications for this project are listed below: "MultiMix: Sparingly Supervised,
This is a five-step framework for the development of intrusion detection systems (IDS) using machine learning (ML) considering model realization, and performance evaluation.
AB-TRAP: building invisibility shields to protect network devices The AB-TRAP framework is applicable to the development of Network Intrusion Detectio
Can we visualize a large scientific data set with a surrogate model? We're building a GAN for the Earth's Mantle Convection data set to see if we can!
EarthGAN - Earth Mantle Surrogate Modeling Can a surrogate model of the Earth’s Mantle Convection data set be built such that it can be readily run in
Nested Graph Neural Network (NGNN) is a general framework to improve a base GNN's expressive power and performance
Nested Graph Neural Networks About Nested Graph Neural Network (NGNN) is a general framework to improve a base GNN's expressive power and performance.
The implementation of the paper "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information".
The HIST framework for stock trend forecasting The implementation of the paper "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining C
The official codes for the ICCV2021 Oral presentation "Rethinking Counting and Localization in Crowds: A Purely Point-Based Framework"
P2PNet (ICCV2021 Oral Presentation) This repository contains codes for the official implementation in PyTorch of P2PNet as described in Rethinking Cou
This repo is all about different data structures and algorithms..
Data Structure and Algorithm : Want to learn data strutrues and algorithms ??? Then Stop thinking more and start to learn today. This repo will help y
A Higher-Lower web game made in Python using Flask framework.
Higher Lower Web Game Guess the random number from 0 to 9 in this web game made with Python and Flask Framework Modules that were used Random Flask In
Data visualization using matplotlib
Data visualization using matplotlib project instructions Top 5 Most Common Coffee Origins In this visualization I used data from Ankur Chavda on Kaggl
Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples
Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples This repository is the official implementation of paper [Qimera: Data-free Q
Leyna's Visualizing Data With Python
Leyna's Visualizing Data Below is information on the number of bilingual students in three school districts in Massachusetts. You will also find infor
Implementation of UNET architecture for Image Segmentation.
Semantic Segmentation using UNET This is the implementation of UNET on Carvana Image Masking Kaggle Challenge About the Dataset This dataset contains
HW_02 Data visualisation task
HW_02 Data visualisation and Matplotlib practice Instructions for HW_02 Idea for data analysis As I was brainstorming ideas and running through databa
(Py)TOD: Tensor-based Outlier Detection, A General GPU-Accelerated Framework
(Py)TOD: Tensor-based Outlier Detection, A General GPU-Accelerated Framework Background: Outlier detection (OD) is a key data mining task for identify
Light-weight network, depth estimation, knowledge distillation, real-time depth estimation, auxiliary data.
light-weight-depth-estimation Boosting Light-Weight Depth Estimation Via Knowledge Distillation, https://arxiv.org/abs/2105.06143 Junjie Hu, Chenyou F
The implementation of the paper "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information".
The HIST framework for stock trend forecasting The implementation of the paper "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining C
A simple API example in Python (Flask framework)
API-Example A simple API in Python(Flask) ✨ Features An API i guess? 💁♀️ How to use first download the main.py install python then install flask fra
An interactive interface for using OpenCV's GrabCut algorithm for image segmentation.
Interactive GrabCut An interactive interface for using OpenCV's GrabCut algorithm for image segmentation. Setup Install dependencies: pip install nump
PyTorch implementation of Memory-based semantic segmentation for off-road unstructured natural environments.
MemSeg: Memory-based semantic segmentation for off-road unstructured natural environments Introduction This repository is a PyTorch implementation of
Rick and Morty Data Visualization with python
Rick and Morty Data Visualization For this project I looked at data for the TV show Rick and Morty Number of Episodes at a Certain Location Here is th
Keir&'s Visualizing Data on Life Expectancy
Keir's Visualizing Data on Life Expectancy Below is information on life expectancy in the United States from 1900-2017. You will also find information
This is a small repository for me to implement my simply Data Visualisation skills through Python.
Data Visualisations This is a small repository for me to implement my simply Data Visualisation skills through Python. Steam Population Chart from 10/
EOD (Easy and Efficient Object Detection) is a general object detection model production framework.
EOD (Easy and Efficient Object Detection) is a general object detection model production framework.
Asterisk is a framework to generate high-quality training datasets at scale
Asterisk is a framework to generate high-quality training datasets at scale
Generate custom detailed survey paper with topic clustered sections and proper citations, from just a single query in just under 30 mins !!
Auto-Research A no-code utility to generate a detailed well-cited survey with topic clustered sections (draft paper format) and other interesting arti
Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset
Semantic Segmentation on MIT ADE20K dataset in PyTorch This is a PyTorch implementation of semantic segmentation models on MIT ADE20K scene parsing da
A Pytorch Implementation of a continuously rate adjustable learned image compression framework.
GainedVAE A Pytorch Implementation of a continuously rate adjustable learned image compression framework, Gained Variational Autoencoder(GainedVAE). N
The PyTorch implementation of DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision.
DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision The PyTorch implementation of DiscoBox: Weakly Supe
REST API with Flask and SQLAlchemy. I would rather not use it anymore.
Flask REST API Python 3.9.7 The Flask experience, without data persistence :D First, to install all dependencies: python -m pip install -r requirement
These data visualizations were created as homework for my CS40 class. I hope you enjoy!
Data Visualizations These data visualizations were created as homework for my CS40 class. I hope you enjoy! Nobel Laureates by their Country of Birth
Python IDE or notebook to generate a basic Kepler.gl data visualization
geospatial-data-analysis [readme] Use this code in your Python IDE or notebook to generate a basic Kepler.gl data visualization, without pre-configura
These data visualizations were created for my introductory computer science course using Python
Homework 2: Matplotlib and Data Visualization Overview These data visualizations were created for my introductory computer science course using Python
BloodDonors: Built using Django REST Framework for the API backend and React for the frontend
BloodDonors By Daniel Yuan, Alex Tian, Aaron Pan, Jennifer Yuan As the pandemic raged, one of the side effects was an urgent shortage of blood donatio
A script that trains a model to recognize handwritten digits using the MNIST data set.
handwritten-digits-recognition A script that trains a model to recognize handwritten digits using the MNIST data set. Then it loads external files and
Code repository for the work "Multi-Domain Incremental Learning for Semantic Segmentation", accepted at WACV 2022
Multi-Domain Incremental Learning for Semantic Segmentation This is the Pytorch implementation of our work "Multi-Domain Incremental Learning for Sema
This repository contains code and data for "On the Multimodal Person Verification Using Audio-Visual-Thermal Data"
trimodal_person_verification This repository contains the code, and preprocessed dataset featured in "A Study of Multimodal Person Verification Using
code for generating data set ES-ImageNet with corresponding training code
es-imagenet-master code for generating data set ES-ImageNet with corresponding training code dataset generator some codes of ODG algorithm The variabl
Code for the prototype tool in our paper "CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning".
CoProtector Code for the prototype tool in our paper "CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning".
DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks
DECAF (DEbiasing CAusal Fairness) Code Author: Trent Kyono This repository contains the code used for the "DECAF: Generating Fair Synthetic Data Using
A novel pipeline framework for multi-hop complex KGQA task. About the paper title: Improving Multi-hop Embedded Knowledge Graph Question Answering by Introducing Relational Chain Reasoning
Rce-KGQA A novel pipeline framework for multi-hop complex KGQA task. This framework mainly contains two modules, answering_filtering_module and relati
Code for "AutoMTL: A Programming Framework for Automated Multi-Task Learning"
AutoMTL: A Programming Framework for Automated Multi-Task Learning This is the website for our paper "AutoMTL: A Programming Framework for Automated M
Code for the prototype tool in our paper "CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning".
CoProtector Code for the prototype tool in our paper "CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning".
Code accompanying the paper "How Tight Can PAC-Bayes be in the Small Data Regime?"
How Tight Can PAC-Bayes be in the Small Data Regime? This is the code to reproduce all experiments for the following paper: @inproceedings{Foong:2021:
A proof-of-concept CherryPy inspired Python micro framework
Varmkorv Varmkorv is a CherryPy inspired micro framework using Werkzeug. This is just a proof of concept. You are free to use it if you like, or find
Use Jax functions in Pytorch with DLPack
Use Jax functions in Pytorch with DLPack
One-Stop Destination for codes of all Data Structures & Algorithms
CodingSimplified_GK This repository is aimed at creating a One stop Destination of codes of all Data structures and Algorithms along with basic explai
Spectacular AI SDK fuses data from cameras and IMU sensors and outputs an accurate 6-degree-of-freedom pose of a device.
Spectacular AI SDK examples Spectacular AI SDK fuses data from cameras and IMU sensors (accelerometer and gyroscope) and outputs an accurate 6-degree-
Alleviating Over-segmentation Errors by Detecting Action Boundaries
Alleviating Over-segmentation Errors by Detecting Action Boundaries Forked from ASRF offical code. This repo is the a implementation of replacing orig
Video Instance Segmentation with a Propose-Reduce Paradigm (ICCV 2021)
Propose-Reduce VIS This repo contains the official implementation for the paper: Video Instance Segmentation with a Propose-Reduce Paradigm Huaijia Li
Code for Generating Disentangled Arguments with Prompts: A Simple Event Extraction Framework that Works
GDAP Code for Generating Disentangled Arguments with Prompts: A Simple Event Extraction Framework that Works Environment Python (verified: v3.8) CUDA
Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation
Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation Requirements This repository needs mmsegmentation Training To train
A LiDAR point cloud cluster for panoptic segmentation
Divide-and-Merge-LiDAR-Panoptic-Cluster A demo video of our method with semantic prior: More information will be coming soon! As a PhD student, I don'
PyTorch Code for NeurIPS 2021 paper Anti-Backdoor Learning: Training Clean Models on Poisoned Data.
Anti-Backdoor Learning PyTorch Code for NeurIPS 2021 paper Anti-Backdoor Learning: Training Clean Models on Poisoned Data. Check the unlearning effect
PyABSA - Open & Efficient for Framework for Aspect-based Sentiment Analysis
PyABSA - Open & Efficient for Framework for Aspect-based Sentiment Analysis
ARA Records Ansible and makes it easier to understand and troubleshoot.
ARA Records Ansible ARA Records Ansible and makes it easier to understand and troubleshoot. It's another recursive acronym. What it does Simple to ins