8583 Repositories
Python table-detection-using-deep-learning Libraries
Simple, light-weight config handling through python data classes with to/from JSON serialization/deserialization.
Simple but maybe too simple config management through python data classes. We use it for machine learning.
One destination for all the developer's learning resources.
DevResources One destination for all the developer's learning resources. Find all of your learning resources under one roof and add your own. Live ✨ Y
PyTorch Implementation of Region Similarity Representation Learning (ReSim)
ReSim This repository provides the PyTorch implementation of Region Similarity Representation Learning (ReSim) described in this paper: @Article{xiao2
Learning Camera Localization via Dense Scene Matching, CVPR2021
This repository contains code of our CVPR 2021 paper - "Learning Camera Localization via Dense Scene Matching" by Shitao Tang, Chengzhou Tang, Rui Hua
AHA is an incident management & communication framework to provide real-time alert customers when there are active AWS event(s). For customers with AWS Organizations, customers can get aggregated active account level events of all the accounts in the Organization. Customers not using AWS Organizations still benefit alerting at the account level.
Table of Contents Introduction Architecture Configuring an Endpoint Creating a Amazon Chime Webhook URL Creating a Slack Webhook URL Creating a Micros
A complete guide to start and improve in machine learning (ML)
A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2021 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques!
Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet
Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet
It is a simple python package to play videos in the terminal using characters as pixels
It is a simple python package to play videos in the terminal using characters as pixels
Simple, fast, and parallelized symbolic regression in Python/Julia via regularized evolution and simulated annealing
Parallelized symbolic regression built on Julia, and interfaced by Python. Uses regularized evolution, simulated annealing, and gradient-free optimization.
LiuAlgoTrader is a scalable, multi-process ML-ready framework for effective algorithmic trading
LiuAlgoTrader is a scalable, multi-process ML-ready framework for effective algorithmic trading. The framework simplify development, testing, deployment, analysis and training algo trading strategies. The framework automatically analyzes trading sessions, and the analysis may be used to train predictive models.
This is the official implementation of 3D-CVF: Generating Joint Camera and LiDAR Features Using Cross-View Spatial Feature Fusion for 3D Object Detection, built on SECOND.
3D-CVF This is the official implementation of 3D-CVF: Generating Joint Camera and LiDAR Features Using Cross-View Spatial Feature Fusion for 3D Object
Bayesian Image Reconstruction using Deep Generative Models
Bayesian Image Reconstruction using Deep Generative Models R. Marinescu, D. Moyer, P. Golland For technical inquiries, please create a Github issue. F
Deep GPs built on top of TensorFlow/Keras and GPflow
GPflux Documentation | Tutorials | API reference | Slack What does GPflux do? GPflux is a toolbox dedicated to Deep Gaussian processes (DGP), the hier
Weakly supervised medical named entity classification
Trove Trove is a research framework for building weakly supervised (bio)medical named entity recognition (NER) and other entity attribute classifiers
Bayesian-Torch is a library of neural network layers and utilities extending the core of PyTorch to enable the user to perform stochastic variational inference in Bayesian deep neural networks
Bayesian-Torch is a library of neural network layers and utilities extending the core of PyTorch to enable the user to perform stochastic variational inference in Bayesian deep neural networks. Bayesian-Torch is designed to be flexible and seamless in extending a deterministic deep neural network architecture to corresponding Bayesian form by simply replacing the deterministic layers with Bayesian layers.
CS 7301: Spring 2021 Course on Advanced Topics in Optimization in Machine Learning
CS 7301: Spring 2021 Course on Advanced Topics in Optimization in Machine Learning
ELI5 is a Python package which helps to debug machine learning classifiers and explain their predictions
A library for debugging/inspecting machine learning classifiers and explaining their predictions
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
Official Implementation of Swapping Autoencoder for Deep Image Manipulation (NeurIPS 2020)
Swapping Autoencoder for Deep Image Manipulation Taesung Park, Jun-Yan Zhu, Oliver Wang, Jingwan Lu, Eli Shechtman, Alexei A. Efros, Richard Zhang UC
This repository allows you to anonymize sensitive information in images/videos. The solution is fully compatible with the DL-based training/inference solutions that we already published/will publish for Object Detection and Semantic Segmentation.
BMW-Anonymization-Api Data privacy and individuals’ anonymity are and always have been a major concern for data-driven companies. Therefore, we design
This is a repository for a Semantic Segmentation inference API using the Gluoncv CV toolkit
BMW Semantic Segmentation GPU/CPU Inference API This is a repository for a Semantic Segmentation inference API using the Gluoncv CV toolkit. The train
FedNLP: A Benchmarking Framework for Federated Learning in Natural Language Processing
FedNLP is a research-oriented benchmarking framework for advancing federated learning (FL) in natural language processing (NLP). It uses FedML repository as the git submodule. In other words, FedNLP only focuses on adavanced models and dataset, while FedML supports various federated optimizers (e.g., FedAvg) and platforms (Distributed Computing, IoT/Mobile, Standalone).
Diffgram - Supervised Learning Data Platform
Data Annotation, Data Labeling, Annotation Tooling, Training Data for Machine Learning
Learning nonlinear operators via DeepONet
DeepONet: Learning nonlinear operators The source code for the paper Learning nonlinear operators via DeepONet based on the universal approximation th
Implementation of Perceiver, General Perception with Iterative Attention in TensorFlow
Perceiver This Python package implements Perceiver: General Perception with Iterative Attention by Andrew Jaegle in TensorFlow. This model builds on t
Official code of CVPR 2021's PLOP: Learning without Forgetting for Continual Semantic Segmentation
PLOP: Learning without Forgetting for Continual Semantic Segmentation This repository contains all of our code. It is a modified version of Cermelli e
Home Assistant custom component for viewing IP cameras RTSP stream in real time using WebRTC technology
WebRTC Camera Home Assistant custom component for viewing IP cameras RTSP stream in real time using WebRTC technology. Based on: Pion - pure Go implem
OBBDetection is a oriented object detection library, which is based on MMdetection.
OBBDetection news: We are now updating OBBDetection to new vision based on MMdetection v2.10, which has more advanced models and more efficient featur
A Pytorch implementation of the multi agent deep deterministic policy gradients (MADDPG) algorithm
Multi-Agent-Deep-Deterministic-Policy-Gradients A Pytorch implementation of the multi agent deep deterministic policy gradients(MADDPG) algorithm This
GrammarTagger — A Neural Multilingual Grammar Profiler for Language Learning
GrammarTagger — A Neural Multilingual Grammar Profiler for Language Learning GrammarTagger is an open-source toolkit for grammatical profiling for lan
Web3.py plugin for using Flashbots' bundle APIs
This library works by injecting a new module in the Web3.py instance, which allows submitting "bundles" of transactions directly to miners. This is do
NoPdb: Non-interactive Python Debugger
NoPdb: Non-interactive Python Debugger Installation: pip install nopdb Docs: https://nopdb.readthedocs.io/ NoPdb is a programmatic (non-interactive) d
MatryODShka: Real-time 6DoF Video View Synthesis using Multi-Sphere Images
Main repo for ECCV 2020 paper MatryODShka: Real-time 6DoF Video View Synthesis using Multi-Sphere Images. visual.cs.brown.edu/matryodshka
Exact Pareto Optimal solutions for preference based Multi-Objective Optimization
Exact Pareto Optimal solutions for preference based Multi-Objective Optimization
OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark
Introduction English | 简体中文 MMAction2 is an open-source toolbox for video understanding based on PyTorch. It is a part of the OpenMMLab project. The m
Visualization toolkit for neural networks in PyTorch! Demo --
FlashTorch A Python visualization toolkit, built with PyTorch, for neural networks in PyTorch. Neural networks are often described as "black box". The
PyTorch3D is FAIR's library of reusable components for deep learning with 3D data
Introduction PyTorch3D provides efficient, reusable components for 3D Computer Vision research with PyTorch. Key features include: Data structure for
Pretrained Pytorch face detection (MTCNN) and recognition (InceptionResnet) models
Face Recognition Using Pytorch Python 3.7 3.6 3.5 Status This is a repository for Inception Resnet (V1) models in pytorch, pretrained on VGGFace2 and
Tool which allow you to detect and translate text.
Text detection and recognition This repository contains tool which allow to detect region with text and translate it one by one. Description Two pretr
Open Source Differentiable Computer Vision Library for PyTorch
Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer
A medical imaging framework for Pytorch
Welcome to MedicalTorch MedicalTorch is an open-source framework for PyTorch, implementing an extensive set of loaders, pre-processors and datasets fo
Sandbox for training deep learning networks
Deep learning networks This repo is used to research convolutional networks primarily for computer vision tasks. For this purpose, the repo contains (
Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.
Faster R-CNN and Mask R-CNN in PyTorch 1.0 maskrcnn-benchmark has been deprecated. Please see detectron2, which includes implementations for all model
A PyTorch-Based Framework for Deep Learning in Computer Vision
TorchCV: A PyTorch-Based Framework for Deep Learning in Computer Vision @misc{you2019torchcv, author = {Ansheng You and Xiangtai Li and Zhen Zhu a
Image augmentation library in Python for machine learning.
Augmentor is an image augmentation library in Python for machine learning. It aims to be a standalone library that is platform and framework independe
Detectorch - detectron for PyTorch
Detectorch - detectron for PyTorch (Disclaimer: this is work in progress and does not feature all the functionalities of detectron. Currently only inf
Fine-tune pretrained Convolutional Neural Networks with PyTorch
Fine-tune pretrained Convolutional Neural Networks with PyTorch. Features Gives access to the most popular CNN architectures pretrained on ImageNet. A
PyTorch for Semantic Segmentation
PyTorch for Semantic Segmentation This repository contains some models for semantic segmentation and the pipeline of training and testing models, impl
:fire: 2D and 3D Face alignment library build using pytorch
Face Recognition Detect facial landmarks from Python using the world's most accurate face alignment network, capable of detecting points in both 2D an
Quickly comparing your image classification models with the state-of-the-art models (such as DenseNet, ResNet, ...)
Image Classification Project Killer in PyTorch This repo is designed for those who want to start their experiments two days before the deadline and ki
A Pythonic introduction to methods for scaling your data science and machine learning work to larger datasets and larger models, using the tools and APIs you know and love from the PyData stack (such as numpy, pandas, and scikit-learn).
This tutorial's purpose is to introduce Pythonistas to methods for scaling their data science and machine learning work to larger datasets and larger models, using the tools and APIs they know and love from the PyData stack (such as numpy, pandas, and scikit-learn).
xitorch: differentiable scientific computing library
xitorch is a PyTorch-based library of differentiable functions and functionals that can be widely used in scientific computing applications as well as deep learning.
This project is a loose implementation of paper "Algorithmic Financial Trading with Deep Convolutional Neural Networks: Time Series to Image Conversion Approach"
Stock Market Buy/Sell/Hold prediction Using convolutional Neural Network This repo is an attempt to implement the research paper titled "Algorithmic F
TransNet V2: Shot Boundary Detection Neural Network
TransNet V2: Shot Boundary Detection Neural Network This repository contains code for TransNet V2: An effective deep network architecture for fast sho
The implementation of "Bootstrapping Semantic Segmentation with Regional Contrast".
ReCo - Regional Contrast This repository contains the source code of ReCo and baselines from the paper, Bootstrapping Semantic Segmentation with Regio
QA-GNN: Question Answering using Language Models and Knowledge Graphs
QA-GNN: Question Answering using Language Models and Knowledge Graphs This repo provides the source code & data of our paper: QA-GNN: Reasoning with L
Try out deep learning models online on Google Colab
Try out deep learning models online on Google Colab
Devkit for 3D -- Some utils for 3D object detection based on Numpy and Pytorch
D3D Devkit for 3D: Some utils for 3D object detection and tracking based on Numpy and Pytorch Please consider siting my work if you find this library
U^2-Net - Portrait matting This repository explores possibilities of using the original u^2-net model for portrait matting.
U^2-Net - Portrait matting This repository explores possibilities of using the original u^2-net model for portrait matting.
Provided is code that demonstrates the training and evaluation of the work presented in the paper: "On the Detection of Digital Face Manipulation" published in CVPR 2020.
FFD Source Code Provided is code that demonstrates the training and evaluation of the work presented in the paper: "On the Detection of Digital Face M
Categorical Depth Distribution Network for Monocular 3D Object Detection
CaDDN CaDDN is a monocular-based 3D object detection method. This repository is based off of [OpenPCDet]. Categorical Depth Distribution Network for M
Plato: A New Framework for Federated Learning Research
a new software framework to facilitate scalable federated learning research.
TTS is a library for advanced Text-to-Speech generation.
TTS is a library for advanced Text-to-Speech generation. It's built on the latest research, was designed to achieve the best trade-off among ease-of-training, speed and quality. TTS comes with pretrained models, tools for measuring dataset quality and already used in 20+ languages for products and research projects.
MMDetection3D is an open source object detection toolbox based on PyTorch
MMDetection3D is an open source object detection toolbox based on PyTorch, towards the next-generation platform for general 3D detection. It is a part of the OpenMMLab project developed by MMLab.
SLIDE : In Defense of Smart Algorithms over Hardware Acceleration for Large-Scale Deep Learning Systems
The SLIDE package contains the source code for reproducing the main experiments in this paper. Dataset The Datasets can be downloaded in Amazon-
Proto-RL: Reinforcement Learning with Prototypical Representations
Proto-RL: Reinforcement Learning with Prototypical Representations This is a PyTorch implementation of Proto-RL from Reinforcement Learning with Proto
Implementation of Cross Transformer for spatially-aware few-shot transfer, in Pytorch
Cross Transformers - Pytorch (wip) Implementation of Cross Transformer for spatially-aware few-shot transfer, in Pytorch Install $ pip install cross-t
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Object Detection and Instance Segmentation.
Swin Transformer for Object Detection This repo contains the supported code and configuration files to reproduce object detection results of Swin Tran
CondenseNet V2: Sparse Feature Reactivation for Deep Networks
CondenseNetV2 This repository is the official Pytorch implementation for "CondenseNet V2: Sparse Feature Reactivation for Deep Networks" paper by Le Y
DLFlow is a deep learning framework.
DLFlow是一套深度学习pipeline,它结合了Spark的大规模特征处理能力和Tensorflow模型构建能力。利用DLFlow可以快速处理原始特征、训练模型并进行大规模分布式预测,十分适合离线环境下的生产任务。利用DLFlow,用户只需专注于模型开发,而无需关心原始特征处理、pipeline构建、生产部署等工作。
Code for HLA-Face: Joint High-Low Adaptation for Low Light Face Detection (CVPR21)
HLA-Face: Joint High-Low Adaptation for Low Light Face Detection The official PyTorch implementation for HLA-Face: Joint High-Low Adaptation for Low L
Official PyTorch implementation of Synergies Between Affordance and Geometry: 6-DoF Grasp Detection via Implicit Representations
Synergies Between Affordance and Geometry: 6-DoF Grasp Detection via Implicit Representations Zhenyu Jiang, Yifeng Zhu, Maxwell Svetlik, Kuan Fang, Yu
Reactjs web app written entirely in python, using transcrypt compiler.
Reactjs web app written entirely in python, using transcrypt compiler.
Real-world Anomaly Detection in Surveillance Videos- pytorch Re-implementation
Real world Anomaly Detection in Surveillance Videos : Pytorch RE-Implementation This repository is a re-implementation of "Real-world Anomaly Detectio
Multi-Scale Aligned Distillation for Low-Resolution Detection (CVPR2021)
MSAD Multi-Scale Aligned Distillation for Low-Resolution Detection Lu Qi*, Jason Kuen*, Jiuxiang Gu, Zhe Lin, Yi Wang, Yukang Chen, Yanwei Li, Jiaya J
QueryDet: Cascaded Sparse Query for Accelerating High-Resolution SmallObject Detection
QueryDet-PyTorch This repository is the official implementation of our paper: QueryDet: Cascaded Sparse Query for Accelerating High-Resolution Small O
Quantum Machine Learning
The Machine Learning package simply contains sample datasets at present. It has some classification algorithms such as QSVM and VQC (Variational Quantum Classifier), where this data can be used for experiments, and there is also QGAN (Quantum Generative Adversarial Network) algorithm.
Newt - a Gaussian process library in JAX.
Newt __ \/_ (' \`\ _\, \ \\/ /`\/\ \\ \ \\
PyTorch reimplementation of the paper Involution: Inverting the Inherence of Convolution for Visual Recognition [CVPR 2021].
Involution: Inverting the Inherence of Convolution for Visual Recognition Unofficial PyTorch reimplementation of the paper Involution: Inverting the I
Elliot is a comprehensive recommendation framework that analyzes the recommendation problem from the researcher's perspective.
Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation
POT : Python Optimal Transport
This open source Python library provide several solvers for optimization problems related to Optimal Transport for signal, image processing and machine learning.
Object Detection and Multi-Object Tracking
Object Detection and Multi-Object Tracking
Using deep actor-critic model to learn best strategies in pair trading
Deep-Reinforcement-Learning-in-Stock-Trading Using deep actor-critic model to learn best strategies in pair trading Abstract Partially observed Markov
Deep Reinforcement Learning based Trading Agent for Bitcoin
Deep Trading Agent Deep Reinforcement Learning based Trading Agent for Bitcoin using DeepSense Network for Q function approximation. For complete deta
Reinforcement Learning for finance
Reinforcement Learning for Finance We apply reinforcement learning for stock trading. Fetch Data Example import utils # fetch symbols from yahoo fina
Reinforcement Learning for Automated Trading
Reinforcement Learning for Automated Trading This thesis has been realized for the obtention of the Master's in Mathematical Engineering at the Polite
PGPortfolio: Policy Gradient Portfolio, the source code of "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem"(https://arxiv.org/pdf/1706.10059.pdf).
This is the original implementation of our paper, A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem (arXiv:1706.1
:boar: :bear: Deep Learning based Python Library for Stock Market Prediction and Modelling
bulbea "Deep Learning based Python Library for Stock Market Prediction and Modelling." Table of Contents Installation Usage Documentation Dependencies
Learning to trade under the reinforcement learning framework
Trading Using Q-Learning In this project, I will present an adaptive learning model to trade a single stock under the reinforcement learning framework
Using multidimensional LSTM neural networks to create a forecast for Bitcoin price
Multidimensional LSTM BitCoin Time Series Using multidimensional LSTM neural networks to create a forecast for Bitcoin price. For notes around this co
Algorithmic Trading using RNN
Deep-Trading This an implementation adapted from Rachnog Neural networks for algorithmic trading. Part One — Simple time series forecasting and this c
Algorithmic trading with deep learning experiments
Deep-Trading Algorithmic trading with deep learning experiments. Now released part one - simple time series forecasting. I plan to implement more soph
This project uses reinforcement learning on stock market and agent tries to learn trading. The goal is to check if the agent can learn to read tape. The project is dedicated to hero in life great Jesse Livermore.
Reinforcement-trading This project uses Reinforcement learning on stock market and agent tries to learn trading. The goal is to check if the agent can
A resource for learning about deep learning techniques from regression to LSTM and Reinforcement Learning using financial data and the fitness functions of algorithmic trading
A tour through tensorflow with financial data I present several models ranging in complexity from simple regression to LSTM and policy networks. The s
This project provides a stock market environment using OpenGym with Deep Q-learning and Policy Gradient.
Stock Trading Market OpenAI Gym Environment with Deep Reinforcement Learning using Keras Overview This project provides a general environment for stoc
Predict stock movement with Machine Learning and Deep Learning algorithms
Project Overview Stock market movement prediction using LSTM Deep Neural Networks and machine learning algorithms Software and Library Requirements Th
Reinforcement Learning for Portfolio Management
qtrader Reinforcement Learning for Portfolio Management Why Reinforcement Learning? Learns the optimal action, rather than models the market. Adaptive
Technical experimentations to beat the stock market using deep learning :chart_with_upwards_trend:
DeepStock Technical experimentations to beat the stock market using deep learning. Experimentations Deep Learning Stock Prediction with Daily News Hea
Use deep learning, genetic programming and other methods to predict stock and market movements
StockPredictions Use classic tricks, neural networks, deep learning, genetic programming and other methods to predict stock and market movements. Both
High frequency AI based algorithmic trading module.
Flow Flow is a high frequency algorithmic trading module that uses machine learning to self regulate and self optimize for maximum return. The current