4550 Repositories
Python data-framework-semantic-segmentation Libraries
Region-aware Contrastive Learning for Semantic Segmentation, ICCV 2021
Region-aware Contrastive Learning for Semantic Segmentation, ICCV 2021 Abstract Recent works have made great success in semantic segmentation by explo
The official PyTorch code for NeurIPS 2021 ML4AD Paper, "Does Thermal data make the detection systems more reliable?"
MultiModal-Collaborative (MMC) Learning Framework for integrating RGB and Thermal spectral modalities This is the official code for NeurIPS 2021 Machi
This repository contains part of the code used to make the images visible in the article "How does an AI Imagine the Universe?" published on Towards Data Science.
Generative Adversarial Network - Generating Universe This repository contains part of the code used to make the images visible in the article "How doe
Machine Learning Framework for Operating Systems - Brings ML to Linux kernel
KML: A Machine Learning Framework for Operating Systems & Storage Systems Storage systems and their OS components are designed to accommodate a wide v
Cerberus Transformer: Joint Semantic, Affordance and Attribute Parsing
Cerberus Transformer: Joint Semantic, Affordance and Attribute Parsing Paper Introduction Multi-task indoor scene understanding is widely considered a
A Python implementation of GRAIL, a generic framework to learn compact time series representations.
GRAIL A Python implementation of GRAIL, a generic framework to learn compact time series representations. Requirements Python 3.6+ numpy scipy tslearn
Cerberus Transformer: Joint Semantic, Affordance and Attribute Parsing
Cerberus Transformer: Joint Semantic, Affordance and Attribute Parsing Paper Introduction Multi-task indoor scene understanding is widely considered a
OpenMMLab Text Detection, Recognition and Understanding Toolbox
Introduction English | 简体中文 MMOCR is an open-source toolbox based on PyTorch and mmdetection for text detection, text recognition, and the correspondi
OpenMMLab Video Perception Toolbox. It supports Video Object Detection (VID), Multiple Object Tracking (MOT), Single Object Tracking (SOT), Video Instance Segmentation (VIS) with a unified framework.
English | 简体中文 Documentation: https://mmtracking.readthedocs.io/ Introduction MMTracking is an open source video perception toolbox based on PyTorch.
Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators.
Jittor: a Just-in-time(JIT) deep learning framework Quickstart | Install | Tutorial | Chinese Jittor is a high-performance deep learning framework bas
A framework that allows people to write their own Rocket League bots.
YOU PROBABLY SHOULDN'T PULL THIS REPO Bot Makers Read This! If you just want to make a bot, you don't need to be here. Instead, start with one of thes
eBay's TSV Utilities: Command line tools for large, tabular data files. Filtering, statistics, sampling, joins and more.
Command line utilities for tabular data files This is a set of command line utilities for manipulating large tabular data files. Files of numeric and
Question and answer retrieval in Turkish with BERT
trfaq Google supported this work by providing Google Cloud credit. Thank you Google for supporting the open source! 🎉 What is this? At this repo, I'm
Desafio proposto pela IGTI em seu bootcamp de Cloud Data Engineer
Desafio Modulo 4 - Cloud Data Engineer Bootcamp - IGTI Objetivos Criar infraestrutura como código Utuilizando um cluster Kubernetes na Azure Ingestão
I managed to attach the Django Framework to my Telegram Bot and set a webhook
I managed to attach the Django Framework to my Telegram Bot and set a webhook. I've been developing it from 10th of November 2021 and I want to have a basic working prototype.
Web scraped S&P 500 Data from Wikipedia using Pandas and performed Exploratory Data Analysis on the data.
Web scraped S&P 500 Data from Wikipedia using Pandas and performed Exploratory Data Analysis on the data. Then used Yahoo Finance to get the related stock data and displayed them in the form of charts.
A hybrid SOTA solution of LiDAR panoptic segmentation with C++ implementations of point cloud clustering algorithms. ICCV21, Workshop on Traditional Computer Vision in the Age of Deep Learning
ICCVW21-TradiCV-Survey-of-LiDAR-Cluster Motivation In contrast to popular end-to-end deep learning LiDAR panoptic segmentation solutions, we propose a
The fastai book, published as Jupyter Notebooks
English / Spanish / Korean / Chinese / Bengali / Indonesian The fastai book These notebooks cover an introduction to deep learning, fastai, and PyTorc
Extension to fastai for volumetric medical data
FAIMED 3D use fastai to quickly train fully three-dimensional models on radiological data Classification from faimed3d.all import * Load data in vari
An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.
Welcome to AdaptNLP A high level framework and library for running, training, and deploying state-of-the-art Natural Language Processing (NLP) models
An Agnostic Computer Vision Framework - Pluggable to any Training Library: Fastai, Pytorch-Lightning with more to come
An Agnostic Object Detection Framework IceVision is the first agnostic computer vision framework to offer a curated collection with hundreds of high-q
Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...
Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...
This is the official PyTorch implementation for "Mesa: A Memory-saving Training Framework for Transformers".
A Memory-saving Training Framework for Transformers This is the official PyTorch implementation for Mesa: A Memory-saving Training Framework for Trans
A framework for annotating 3D meshes using the predictions of a 2D semantic segmentation model.
Semantic Meshes A framework for annotating 3D meshes using the predictions of a 2D semantic segmentation model. Paper If you find this framework usefu
The Most Efficient Temporal Difference Learning Framework for 2048
moporgic/TDL2048+ TDL2048+ is a highly optimized temporal difference (TD) learning framework for 2048. Features Many common methods related to 2048 ar
Code for NeurIPS2021 submission "A Surrogate Objective Framework for Prediction+Programming with Soft Constraints"
This repository is the code for NeurIPS 2021 submission "A Surrogate Objective Framework for Prediction+Programming with Soft Constraints". Edit 2021/
FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks
FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks Image Classification Dataset: Google Landmark, COCO, ImageNet Model: Efficient
Graph Convolutional Neural Networks with Data-driven Graph Filter (GCNN-DDGF)
Graph Convolutional Gated Recurrent Neural Network (GCGRNN) Improved from Graph Convolutional Neural Networks with Data-driven Graph Filter (GCNN-DDGF
Project5 Data processing system
Project5-Data-processing-system User just needed to copy both these file to a folder and open Project5.py using cmd or using any python ide. It is to
Epidemiology analysis package
zEpid zEpid is an epidemiology analysis package, providing easy to use tools for epidemiologists coding in Python 3.5+. The purpose of this library is
Explorative Data Analysis Guidelines
Explorative Data Analysis Get data into a usable format! Find out if the following predictive modeling phase will be successful! Combine everything in
cleanlab is the data-centric ML ops package for machine learning with noisy labels.
cleanlab is the data-centric ML ops package for machine learning with noisy labels. cleanlab cleans labels and supports finding, quantifying, and lear
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.
Kaggler is a Python package for lightweight online machine learning algorithms and utility functions for ETL and data analysis.
Kaggler is a Python package for lightweight online machine learning algorithms and utility functions for ETL and data analysis. It is distributed under the MIT License.
Skoot is a lightweight python library of machine learning transformer classes that interact with scikit-learn and pandas.
Skoot is a lightweight python library of machine learning transformer classes that interact with scikit-learn and pandas. Its objective is to ex
dirty_cat is a Python module for machine-learning on dirty categorical variables.
dirty_cat dirty_cat is a Python module for machine-learning on dirty categorical variables.
Pypeln is a simple yet powerful Python library for creating concurrent data pipelines.
Pypeln Pypeln (pronounced as "pypeline") is a simple yet powerful Python library for creating concurrent data pipelines. Main Features Simple: Pypeln
A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.
Feature Engineering & Feature Selection A comprehensive guide [pdf] [markdown] for Feature Engineering and Feature Selection, with implementations and
apricot implements submodular optimization for the purpose of selecting subsets of massive data sets to train machine learning models quickly.
Please consider citing the manuscript if you use apricot in your academic work! You can find more thorough documentation here. apricot implements subm
MCML is a toolkit for semi-supervised dimensionality reduction and quantitative analysis of Multi-Class, Multi-Label data
MCML is a toolkit for semi-supervised dimensionality reduction and quantitative analysis of Multi-Class, Multi-Label data. We demonstrate its use
Dump Data from FTDI Serial Port to Binary File on MacOS
Dump Data from FTDI Serial Port to Binary File on MacOS
Testing - Instrumenting Sanic framework with Opentelemetry
sanic-otel-splunk Testing - Instrumenting Sanic framework with Opentelemetry Test with python 3.8.10, sanic 20.12.2 Step to instrument pip install -r
Python framework for AsyncAPI-documented Websocket, PubSub, and other async constructs
asyncapi-eventrouter Work in Progress Write Python code for Event-Driven Architectures! The asyncapi-eventrouter prototype library creates Websocket,
Crypto Stats and Tweets Data Pipeline using Airflow
Crypto Stats and Tweets Data Pipeline using Airflow Introduction Project Overview This project was brought upon through Udacity's nanodegree program.
Semantic Segmentation in Pytorch
PyTorch Semantic Segmentation Introduction This repository is a PyTorch implementation for semantic segmentation / scene parsing. The code is easy to
A package to predict protein inter-residue geometries from sequence data
trRosetta This package is a part of trRosetta protein structure prediction protocol developed in: Improved protein structure prediction using predicte
Complete-IoU (CIoU) Loss and Cluster-NMS for Object Detection and Instance Segmentation (YOLACT)
Complete-IoU Loss and Cluster-NMS for Improving Object Detection and Instance Segmentation. Our paper is accepted by IEEE Transactions on Cybernetics
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models. Hyperactive: is very easy to lear
68 keypoint annotations for COFW test data
68 keypoint annotations for COFW test data This repository contains manually annotated 68 keypoints for COFW test data (original annotation of CFOW da
Centralized whale instance using github actions, sourcing metadata from bigquery-public-data.
Whale Demo Instance: Bigquery Public Data This is a fully-functioning demo instance of the whale data catalog, actively scraping data from Bigquery's
Fast Fourier Transform-accelerated Interpolation-based t-SNE (FIt-SNE)
FFT-accelerated Interpolation-based t-SNE (FIt-SNE) Introduction t-Stochastic Neighborhood Embedding (t-SNE) is a highly successful method for dimensi
An interactive UMAP visualization of the MNIST data set.
Code for an interactive UMAP visualization of the MNIST data set. Demo at https://grantcuster.github.io/umap-explorer/. You can read more about the de
A high-performance topological machine learning toolbox in Python
giotto-tda is a high-performance topological machine learning toolbox in Python built on top of scikit-learn and is distributed under the G
Single-Cell Analysis in Python. Scales to 1M cells.
Scanpy – Single-Cell Analysis in Python Scanpy is a scalable toolkit for analyzing single-cell gene expression data built jointly with anndata. It inc
3D rendered visualization of the austrian monuments registry
Visualization of the Austrian Monuments Visualization of the monument landscape of the austrian monuments registry (Bundesdenkmalamt Denkmalverzeichni
Falcon: Interactive Visual Analysis for Big Data
Falcon: Interactive Visual Analysis for Big Data Crossfilter millions of records without latencies. This project is work in progress and not documente
A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Torch and Numpy.
Visdom A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Python. Overview Concepts Setup Usage API To
Complex heatmaps are efficient to visualize associations between different sources of data sets and reveal potential patterns.
Make Complex Heatmaps Complex heatmaps are efficient to visualize associations between different sources of data sets and reveal potential patterns. H
A set of useful perceptually uniform colormaps for plotting scientific data
Colorcet: Collection of perceptually uniform colormaps Build Status Coverage Latest dev release Latest release Docs What is it? Colorcet is a collecti
Streamlit — The fastest way to build data apps in Python
Welcome to Streamlit 👋 The fastest way to build and share data apps. Streamlit lets you turn data scripts into sharable web apps in minutes, not week
The purpose of this project is to share knowledge on how awesome Streamlit is and can be
Awesome Streamlit The fastest way to build Awesome Tools and Apps! Powered by Python! The purpose of this project is to share knowledge on how Awesome
A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Torch and Numpy.
Visdom A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Python. Overview Concepts Setup Usage API To
Select, weight and analyze complex sample data
Sample Analytics In large-scale surveys, often complex random mechanisms are used to select samples. Estimates derived from such samples must reflect
Datashader is a data rasterization pipeline for automating the process of creating meaningful representations of large amounts of data.
Datashader is a data rasterization pipeline for automating the process of creating meaningful representations of large amounts of data.
PyCaret is an open-source, low-code machine learning library in Python that automates machine learning workflows.
An open-source, low-code machine learning library in Python 🚀 Version 2.3.5 out now! Check out the release notes here. Official • Docs • Install • Tu
Visualization ideas for data science
Nuance I use Nuance to curate varied visualization thoughts during my data scientist career. It is not yet a package but a list of small ideas. Welcom
🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams
🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams
A natural language modeling framework based on PyTorch
Overview PyText is a deep-learning based NLP modeling framework built on PyTorch. PyText addresses the often-conflicting requirements of enabling rapi
Approximate Nearest Neighbor Search for Sparse Data in Python!
Approximate Nearest Neighbor Search for Sparse Data in Python! This library is well suited to finding nearest neighbors in sparse, high dimensional spaces (like text documents).
ETNA – time series forecasting framework
ETNA Time Series Library Predict your time series the easiest way Homepage | Documentation | Tutorials | Contribution Guide | Release Notes ETNA is an
Project looking into use of autoencoder for semi-supervised learning and comparing data requirements compared to supervised learning.
Project looking into use of autoencoder for semi-supervised learning and comparing data requirements compared to supervised learning.
A program that analyzes data from inertia measurement units installeed in aircraft and generates g-exceedance curves
A program that analyzes data from inertia measurement units installeed in aircraft and generates g-exceedance curves
This is the official PyTorch implementation for "Mesa: A Memory-saving Training Framework for Transformers".
Mesa: A Memory-saving Training Framework for Transformers This is the official PyTorch implementation for Mesa: A Memory-saving Training Framework for
What if home automation was homoiconic? Just transformations of data? No more YAML!
radiale what if home-automation was also homoiconic? The upper or proximal row contains three bones, to which Gegenbaur has applied the terms radiale,
Steganography Image/Data Injector.
Byte Steganography Image/Data Injector. For artists or people to inject their own print/data into their images. TODO Add more file formats to support.
Python module for data science and machine learning users.
dsnk-distributions package dsnk distribution is a Python module for data science and machine learning that was created with the goal of reducing calcu
Use Flask API to wrap Facebook data. Grab the wapper of Facebook public pages without an API key.
Facebook Scraper Use Flask API to wrap Facebook data. Grab the wapper of Facebook public pages without an API key. (Currently working 2021) Setup Befo
Python beta calculator that retrieves stock and market data and provides linear regressions.
Stock and Index Beta Calculator Python script that calculates the beta (β) of a stock against the chosen index. The script retrieves the data and resa
Lightweight library for accessing data and configuration
accsr This lightweight library contains utilities for managing, loading, uploading, opening and generally wrangling data and configurations. It was ba
🔎 Most Advanced Open Source Intelligence (OSINT) Framework for scanning IP Address, Emails, Websites, Organizations.
🔎 Most Advanced Open Source Intelligence (OSINT) Framework for scanning IP Address, Emails, Websites, Organizations.
Detectron2 for Document Layout Analysis
Detectron2 trained on PubLayNet dataset This repo contains the training configurations, code and trained models trained on PubLayNet dataset using Det
BErt-like Neurophysiological Data Representation
BENDR BErt-like Neurophysiological Data Representation This repository contains the source code for reproducing, or extending the BERT-like self-super
Boundary-preserving Mask R-CNN (ECCV 2020)
BMaskR-CNN This code is developed on Detectron2 Boundary-preserving Mask R-CNN ECCV 2020 Tianheng Cheng, Xinggang Wang, Lichao Huang, Wenyu Liu Video
SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data (AAAI 2021)
SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data (AAAI 2021) PyTorch implementation of SnapMix | paper Method Overview Cite
The pure and clear PyTorch Distributed Training Framework.
The pure and clear PyTorch Distributed Training Framework. Introduction Requirements and Usage Dependency Dataset Basic Usage Slurm Cluster Usage Base
ClearML - Auto-Magical Suite of tools to streamline your ML workflow. Experiment Manager, MLOps and Data-Management
ClearML - Auto-Magical Suite of tools to streamline your ML workflow Experiment Manager, MLOps and Data-Management ClearML Formerly known as Allegro T
Scheme for training and applying a label propagation framework
Factorisation-based Image Labelling Overview This is a scheme for training and applying the factorisation-based image labelling (FIL) framework. Some
The code for Bi-Mix: Bidirectional Mixing for Domain Adaptive Nighttime Semantic Segmentation
BiMix The code for Bi-Mix: Bidirectional Mixing for Domain Adaptive Nighttime Semantic Segmentation arxiv Framework: visualization results: Requiremen
Rainbow DQN implementation that outperforms the paper's results on 40% of games using 20x less data 🌈
Rainbow 🌈 An implementation of Rainbow DQN which outperforms the paper's (Hessel et al. 2017) results on 40% of tested games while using 20x less dat
ClevrTex: A Texture-Rich Benchmark for Unsupervised Multi-Object Segmentation
ClevrTex This repository contains dataset generation code for ClevrTex benchmark from paper: ClevrTex: A Texture-Rich Benchmark for Unsupervised Multi
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
Python package for missing-data imputation with deep learning
MIDASpy Overview MIDASpy is a Python package for multiply imputing missing data using deep learning methods. The MIDASpy algorithm offers significant
Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...
Automatic, Readable, Reusable, Extendable Machin is a reinforcement library designed for pytorch. Build status Platform Status Linux Windows Supported
A keras-based real-time model for medical image segmentation (CFPNet-M)
CFPNet-M: A Light-Weight Encoder-Decoder Based Network for Multimodal Biomedical Image Real-Time Segmentation This repository contains the implementat
PyTorch Connectomics: segmentation toolbox for EM connectomics
Introduction The field of connectomics aims to reconstruct the wiring diagram of the brain by mapping the neural connections at the level of individua
Create a database, insert data and easily select it with Sqlite
sqliteBasics create a database, insert data and easily select it with Sqlite Watch on YouTube a step by step tutorial explaining this code: https://yo
Knowledge Distillation Toolbox for Semantic Segmentation
SegDistill: Toolbox for Knowledge Distillation on Semantic Segmentation Networks This repo contains the supported code and configuration files for Seg
A Python package to process & model ChEMBL data.
insilico: A Python package to process & model ChEMBL data. ChEMBL is a manually curated chemical database of bioactive molecules with drug-like proper
An open source utility for creating publication quality LaTex figures generated from OpenFOAM data files.
foamTEX An open source utility for creating publication quality LaTex figures generated from OpenFOAM data files. Explore the docs » Report Bug · Requ
Data Applications Project
DBMS project- Hotel Franchise Data and application project By TEAM Kurukunda Bhargavi Pamulapati Pallavi Greeshma Amaraneni What is this project about