Python Image-Data-Augmentation-in-Keras Resources

SMSR Reposity for "Exploring Sparsity in Image Super-Resolution for Efficient Inference" [arXiv] Highlights Locate and skip redundant computation in S

Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch

Implementation of Analyzing and Improving the Image Quality of StyleGAN (StyleGAN 2) in PyTorch

Bringing Old Photo Back to Life (CVPR 2020 oral)

Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network)

Neural Spatio-Temporal Point Processes [arxiv] Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel Abstract. We propose a new class of parameterizations

StrayVisualizer A set of scripts to work with data collected using Stray Scanner. Usage Installing Dependencies Install dependencies with pip -r requi

Megalista Sample integration code for onboarding offline/CRM data from BigQuery as custom audiences or offline conversions in Google Ads, Google Analy

Machine learning metrics for distributed, scalable PyTorch applications.

Ralph Ralph is full-featured Asset Management, DCIM and CMDB system for data centers and back offices. Features: keep track of assets purchases and th

NetBox is an IP address management (IPAM) and data center infrastructure management (DCIM) tool. Initially conceived by the network engineering team a

S3QL S3QL is a file system that stores all its data online using storage services like Google Storage, Amazon S3, or OpenStack. S3QL effectively provi

Datasette An open source multi-tool for exploring and publishing data Datasette is a tool for exploring and publishing data. It helps people take data

Website • Docs • Blog • Twitter • Chat (Community & Support) • Tutorial • Mailing List Data Version Control or DVC is an open-source tool for data sci

Solaris Image Packaging System Introduction The image packaging system (IPS) is a software delivery system with interaction with a network repository

Patta Image Test Time Augmentation with Paddle2.0! Input | # input batch of images / / /|\ \ \ # apply

Find Jobs on LinkedIn 📔 This program finds jobs by scraping on LinkedIn 👨‍💻 Relies on User Input. Accepts: Country, City, State 📑 Data about jobs

CoTr: Efficient 3D Medical Image Segmentation by bridging CNN and Transformer This is the official pytorch implementation of the CoTr: Paper: CoTr: Ef

QPIC: Query-Based Pairwise Human-Object Interaction Detection with Image-Wide Contextual Information by Masato Tamura, Hiroki Ohashi, and Tomoaki Yosh

involution Official implementation of a neural operator as described in Involution: Inverting the Inherence of Convolution for Visual Recognition (CVP

Anycost GAN video | paper | website Anycost GANs for Interactive Image Synthesis and Editing Ji Lin, Richard Zhang, Frieder Ganz, Song Han, Jun-Yan Zh

Consistency Regularization for Adversarial Robustness Official PyTorch implementation of Consistency Regularization for Adversarial Robustness by Jiho

Data Structures and Algorithms Python INDEX 1. Resources - Books Data Structures - Reema Thareja competitiveCoding Big-O Cheat Sheet DAA Syllabus Inte

zpy: Synthetic data in Blender. Website • Install • Docs • Examples • CLI • Contribute • Licence Abstract Collecting, labeling, and cleaning data for

Aphantasia This is a text-to-image tool, part of the artwork of the same name. Based on CLIP model, with FFT parameterizer from Lucent library as a ge

Object Pose Estimation Demo This tutorial will go through the steps necessary to perform pose estimation with a UR3 robotic arm in Unity. You’ll gain

Create Django App 💛 We're a Django project starter on steroids! One-line command to create a Django app with all the dependencies auto-installed AND

ClassSR (CVPR2021) ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic Paper Authors: Xiangtao Kong, Hengyuan

Easy Few-Shot Learning Ready-to-use code and tutorial notebooks to boost your way into few-shot image classification. This repository is made for you

Rubicon Purpose Rubicon is a data science tool that captures and stores model training and execution information, like parameters and outcomes, in a r

Morph-UGATIT a morph transfer UGATIT for image translation. Introduction 中文技术文档 This is Pytorch implementation of UGATIT, paper "U-GAT-IT: Unsupervise

Data Augmentation using Pre-trained Transformer Models Code associated with the Data Augmentation using Pre-trained Transformer Models paper Code cont

MMdnn MMdnn is a comprehensive and cross-framework tool to convert, visualize and diagnose deep learning (DL) models. The "MM" stands for model manage

Open Neural Network Exchange (ONNX) is an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides

Horovod Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. The goal of Horovod is to make dis

Pandas Profiling Documentation | Slack | Stack Overflow Generates profile reports from a pandas DataFrame. The pandas df.describe() function is great

pandas_summary An extension to pandas dataframes describe function. The module contains DataFrameSummary object that extend describe() with: propertie

Albumentations Albumentations is a Python library for image augmentation. Image augmentation is used in deep learning and computer vision tasks to inc

Augmentor is an image augmentation library in Python for machine learning. It aims to be a standalone library that is platform and framework independe

imgaug This python library helps you with augmenting images for your machine learning projects. It converts a set of input images into a new, much lar

scikit-image: Image processing in Python Website (including documentation): https://scikit-image.org/ Mailing list: https://mail.python.org/mailman3/l

OpenCV: Open Source Computer Vision Library Resources Homepage: https://opencv.org Courses: https://opencv.org/courses Docs: https://docs.opencv.org/m

muda A library for Musical Data Augmentation. muda package implements annotation-aware musical data augmentation, as described in the muda paper. The

Hyperparameter Optimization for Keras Talos • Key Features • Examples • Install • Support • Docs • Issues • License • Download Talos radically changes

emcee The Python ensemble sampling toolkit for affine-invariant MCMC emcee is a stable, well tested Python implementation of the affine-invariant ense

A supervised domain-agnostic framework that allows for probabilistic modelling, namely the prediction of probability distributions for individual data

InferPy: Deep Probabilistic Modeling Made Easy InferPy is a high-level API for probabilistic modeling written in Python and capable of running on top

Deep Reinforcement Learning for Keras What is it? keras-rl implements some state-of-the art deep reinforcement learning algorithms in Python and seaml

Stable Baselines Stable Baselines is a set of improved implementations of reinforcement learning algorithms based on OpenAI Baselines. You can read a

Master status: Development status: Package information: scikit-rebate This package includes a scikit-learn-compatible Python implementation of ReBATE,

BoostARoota A Fast XGBoost Feature Selection Algorithm (plus other sklearn tree-based classifiers) Why Create Another Algorithm? Automated processes l

tsfresh This repository contains the TSFRESH python package. The abbreviation stands for "Time Series Feature extraction based on scalable hypothesis

"One of the holy grails of machine learning is to automate more and more of the feature engineering process." ― Pedro Domingos, A Few Useful Things to

Prodmodel is a build system for data science pipelines. Users, testers, contributors are welcome! Motivation · Concepts · Installation · Usage · Contr

meza: A Python toolkit for processing tabular data Index Introduction | Requirements | Motivation | Hello World | Usage | Interoperability | Installat

pyjanitor pyjanitor is a Python implementation of the R package janitor, and provides a clean API for cleaning data. Why janitor? Originally a port of

BatchFlow BatchFlow helps you conveniently work with random or sequential batches of your data and define data processing and machine learning workflo

pandas-ply: functional data manipulation for pandas pandas-ply is a thin layer which makes it easier to manipulate data with pandas. In particular, it

pdpipe ˨ Easy pipelines for pandas DataFrames (learn how!). Website: https://pdpipe.github.io/pdpipe/ Documentation: https://pdpipe.github.io/pdpipe/d

What is Vaex? Vaex is a high performance Python library for lazy Out-of-Core DataFrames (similar to Pandas), to visualize and explore big tabular data

pandas API on Apache Spark Explore Koalas docs » Live notebook · Issues · Mailing list Help Thirsty Koalas Devastated by Recent Fires The Koalas proje

datatable This is a Python package for manipulating 2-dimensional tabular data structures (aka data frames). It is close in spirit to pandas or SFrame

Arctic TimeSeries and Tick store Arctic is a high performance datastore for numeric data. It supports Pandas, numpy arrays and pickled objects out-of-

pysparkling Pysparkling provides a faster, more responsive way to develop programs for PySpark. It enables code intended for Spark applications to exe

XPandas (extended Pandas) implements 1D and 2D data containers for storing type-heterogeneous tabular data of any type, and encapsulates feature extra

pandas-gbq pandas-gbq is a package providing an interface to the Google BigQuery API from pandas Installation Install latest release version via conda

Blaze translates a subset of modified NumPy and Pandas-like syntax to databases and other computing systems. Blaze allows Python users a familiar inte

Pandas Profiling Documentation | Slack | Stack Overflow Generates profile reports from a pandas DataFrame. The pandas df.describe() function is great

Logging MXNet Data for Visualization in TensorBoard Overview MXBoard provides a set of APIs for logging MXNet data for visualization in TensorBoard. T

Netron is a viewer for neural network, deep learning and machine learning models. Netron supports ONNX (.onnx, .pb, .pbtxt), Keras (.h5, .keras), Tens

AI Explainability 360 (v0.2.1) The AI Explainability 360 toolkit is an open-source library that supports interpretability and explainability of datase

ELI5 ELI5 is a Python package which helps to debug machine learning classifiers and explain their predictions. It provides support for the following m

Welcome to Scikit-plot Single line functions for detailed visualizations The quickest and easiest way to go from analysis... ...to this. Scikit-plot i

Documentation | External Resources | Research Paper Shapley is a Python library for evaluating binary classifiers in a machine learning ensemble. The

HoloViews Stop plotting your data - annotate your data and let it visualize itself. HoloViews is an open-source Python library designed to make data a

fuck-coding-interviews This repository is created by an awkward programmer who always struggles with coding problems on LeetCode, even with some Easy

Algorithms and Data Structures (ands) Introduction This project was created for personal use mostly while studying for an exam (starting in the month

Algorithms in Python Implementations of a few algorithms and datastructures for fun and profit! Completed Karatsuba Multiplication Basic Sorting Rabin

Chartify Chartify is a Python library that makes it easy for data scientists to create charts. Why use Chartify? Consistent input data format: Spend l

Gluon CV Toolkit | Installation | Documentation | Tutorials | GluonCV provides implementations of the state-of-the-art (SOTA) deep learning models in

QKeras github.com/google/qkeras QKeras 0.8 highlights: Automatic quantization using QKeras; Stochastic behavior (including stochastic rouding) is disa

Welcome to Spektral Spektral is a Python library for graph deep learning, based on the Keras API and TensorFlow 2. The main goal of this project is to

Hera Train/evaluate a Keras model, get metrics streamed to a dashboard in your browser. Setting up Step 1. Plant the spy Install the package pip

Elephas: Distributed Deep Learning with Keras & Spark Elephas is an extension of Keras, which allows you to run distributed deep learning models at sc

This project is now archived. It's been fun working on it, but it's time for me to move on. Thank you for all the support and feedback over the last c

keras-contrib : Keras community contributions Keras-contrib is deprecated. Use TensorFlow Addons. The future of Keras-contrib: We're migrating to tens

Reproduce, Automate, Scale your data science. Welcome to Polyaxon, a platform for building, training, and monitoring large scale deep learning applica

Here is Poutyne. Poutyne is a simplified framework for PyTorch and handles much of the boilerplating code needed to train neural networks. Use Poutyne

torchtext This repository consists of: torchtext.datasets: The raw text iterators for common NLP datasets torchtext.data: Some basic NLP building bloc

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a

ND DIAL: Imbalanced Algorithms Minimalist Python-based implementations of algorithms for imbalanced learning. Includes deep and representational learn

imbalanced-learn imbalanced-learn is a python package offering a number of re-sampling techniques commonly used in datasets showing strong between-cla

MLBox is a powerful Automated Machine Learning python library. It provides the following features: Fast reading and distributed data preprocessing/cle

Master status: Development status: Package information: TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assista

Prophet: Automatic Forecasting Procedure Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends ar

tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn Getti

pyGAM Generalized Additive Models in Python. Documentation Official pyGAM Documentation: Read the Docs Building interpretable models with Generalized

[Due to the time taken @ uni, work + hell breaking loose in my life, since things have calmed down a bit, will continue commiting!!!] [By the way, I'm

Mlxtend (machine learning extensions) is a Python library of useful tools for the day-to-day data science tasks. Sebastian Raschka 2014-2021 Links Doc