Python Optimal-power-flow Resources

This repo has code and notes for whole home electrical power monitoring using a Raspberry Pi and CircuitSetup modules. Beyond just collecting data, it

Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation Implementation for our paper, submitted to NeurIPS 2021 (also chec

Microsoft365_devicePhish Abusing Microsoft 365 OAuth Authorization Flow for Phishing Attack This is a simple proof-of-concept script that allows an at

LOC-FLOW is an “hands-free” earthquake location workflow to process continuous seismic records: from raw waveforms to well located earthquakes with magnitude calculations. The package assembles several popular routines for sequential earthquake location refinements, suitable for catalog building ranging from local to regional scales.

Based on Yolo's low-power, ultra-lightweight universal target detection algorithm, the parameter is only 250k, and the speed of the smart phone mobile terminal can reach ~300fps+

PyTorch Lightning Optical Flow models, scripts, and pretrained weights.

Dewarping Document Image By Displacement Flow Estimation with Fully Convolutional Network

A Python library for differentiable optimal control on accelerators.

vboxpower VirtualBox Power Driver for MAAS (Metal as a Service) A way to manage the power of VirtualBox virtual machines via the MAAS webhook driver.

RIFE RIFE: Real-Time Intermediate Flow Estimation for Video Frame Interpolation Ported from https://github.com/hzwer/arXiv2020-RIFE Dependencies NumPy

torch_DE_solver Combines power of torch, numerical methods and math overall to conquer and solve ALL {O,P}DEs There are three examples to provide a li

flownet2-pytorch Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks. Multiple GPU training is supported, a

Deep Learning for Physical Processes: Integrating Prior Scientific Knowledge: Official Pytorch implementation of ICLR 2018 paper Deep Learning for Phy

WaveGlow: a Flow-based Generative Network for Speech Synthesis Ryan Prenger, Rafael Valle, and Bryan Catanzaro In our recent paper, we propose WaveGlo

WaveGlow A PyTorch implementation of the WaveGlow: A Flow-based Generative Network for Speech Synthesis Quick Start: Install requirements: pip install

This is a Pytorch implementation of Janai, J., Güney, F., Ranjan, A., Black, M. and Geiger, A., Unsupervised Learning of Multi-Frame Optical Flow with

Raspberry Pi 1U Server There are server colocation providers that allow hosting a 1U server for as low as $30/month, but there's a catch: There are re

The Power of Scale for Parameter-Efficient Prompt Tuning Implementation of soft embeddings from https://arxiv.org/abs/2104.08691v1 using Pytorch and H

ManhattanSLAM Authors: Raza Yunus, Yanyan Li and Federico Tombari ManhattanSLAM is a real-time SLAM library for RGB-D cameras that computes the camera

Dewarping Document Image By Displacement Flow Estimation with Fully Convolutional Network

glow-pytorch PyTorch implementation of Glow, Generative Flow with Invertible 1x1 Convolutions

Draw like Bob Ross using the power of Neural Networks! (+ Pytorch) Learning Process Visualization Getting started Install dependecies Requires python3

**Codebase and data are uploaded in progress. ** VOLT(-py) is a vocabulary learning codebase that allows researchers and developers to automaticaly ge

Box is a text-based visual programming language inspired by Unreal Engine blueprint function graphs. $ cat factorial.box ┌─ƒ(Factorial)───┐

Cross-platform CLI and Python drivers for AIO liquid coolers and other devices

Custom component to calculate estimated power consumption of lights and other appliances. Provides easy configuration to get virtual power consumption sensors in Home Assistant for all your devices which don't have a build in power meter.

LibTraffic is a unified, flexible and comprehensive traffic prediction library, which provides researchers with a credibly experimental tool and a convenient development framework. Our library is implemented based on PyTorch, and includes all the necessary steps or components related to traffic prediction into a systematic pipeline.

MODeflattener deobfuscates control flow flattened functions obfuscated by OLLVM using Miasm.

Orkestra The elegance of Airflow + the power of AWS

FastFlowNet: A Lightweight Network for Fast Optical Flow Estimation The official PyTorch implementation of FastFlowNet (ICRA 2021). Authors: Lingtong

Learning Optical Flow from a Few Matches This repository contains the source code for our paper: Learning Optical Flow from a Few Matches CVPR 2021 Sh

MaskFlownet-Pytorch Unofficial PyTorch implementation of MaskFlownet (https://github.com/microsoft/MaskFlownet). Tested with: PyTorch 1.5.0 CUDA 10.1

JupyterLite is a JupyterLab distribution that runs entirely in the browser built from the ground-up using JupyterLab components and extensions.

Flow-to-depth (FDNet) video-depth-estimation This is the implementation of paper Video Depth Estimation by Fusing Flow-to-Depth Proposals Jiaxin Xie,

Expressive Power of Invariant and Equivaraint Graph Neural Networks In this repository, we show how to use powerful GNN (2-FGNN) to solve a graph alig

PV-RAFT This repository contains the PyTorch implementation for paper "PV-RAFT: Point-Voxel Correlation Fields for Scene Flow Estimation of Point Clou

Conversations are not Flat: Modeling the Intrinsic Information Flow between Dialogue Utterances This repository contains the code and pre-trained mode

Self-Supervised Multi-Frame Monocular Scene Flow 3D visualization of estimated depth and scene flow (overlayed with input image) from temporally conse

Optex An implementation of Optimal Textures: Fast and Robust Texture Synthesis and Style Transfer through Optimal Transport for TU Delft CS4240. You c

It selects the best indexing parameters to achieve the highest recalls given memory and query speed constraints.

Just Go with the Flow: Self-Supervised Scene Flow Estimation Code release for the paper Just Go with the Flow: Self-Supervised Scene Flow Estimation,

Exact Pareto Optimal solutions for preference based Multi-Objective Optimization

AutoOED is an optimal experiment design platform powered with automated machine learning to accelerate the discovery of optimal solutions. Our platform solves multi-objective optimization problems and automatically guides the design of experiment to be evaluated.

This open source Python library provide several solvers for optimization problems related to Optimal Transport for signal, image processing and machine learning.

Depthstillation Demo code for "Learning optical flow from still images", CVPR 2021. [Project page] - [Paper] - [Supplementary] This code is provided t

OTA: Optimal Transport Assignment for Object Detection This project provides an implementation for our CVPR2021 paper "OTA: Optimal Transport Assignme

FilterPy - Kalman filters and other optimal and non-optimal estimation filters in Python. NOTE: Imminent drop of support of Python 2.7, 3.4. See secti

FFB6D This is the official source code for the CVPR2021 Oral work, FFB6D: A Full Flow Biderectional Fusion Network for 6D Pose Estimation. (Arxiv) Tab

FLAVR is a fast, flow-free frame interpolation method capable of single shot multi-frame prediction. It uses a customized encoder decoder architecture with spatio-temporal convolutions and channel gating to capture and interpolate complex motion trajectories between frames to generate realistic high frame rate videos. This repository contains original source code for the paper accepted to CVPR 2021.

UnRigidFlow This is the official PyTorch implementation of UnRigidFlow (IJCAI2019). Here are two sample results (~10MB gif for each) of our unsupervis

POT: Python Optimal Transport This open source Python library provide several solvers for optimization problems related to Optimal Transport for signa

Neural Scene Flow Fields PyTorch implementation of paper "Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes", CVPR 20

Navier-Stokes-numerical-solution-using-Python- Python script for Linear, Non-Linear Convection, Burger’s & Poisson Equation in 1D & 2D, 1D D

Weakly Supervised Learning of Rigid 3D Scene Flow This repository provides code and data to train and evaluate a weakly supervised method for rigid 3D

Project DeepSpeech DeepSpeech is an open-source Speech-To-Text engine, using a model trained by machine learning techniques based on Baidu's Deep Spee

rigidmask Code for "Learning to Segment Rigid Motions from Two Frames". ** This is a partial release with inference and evaluation code.

Neural Tangents ICLR 2020 Video | Paper | Quickstart | Install guide | Reference docs | Release notes Overview Neural Tangents is a high-level neural

This project is no longer maintained March 2020 Update: Please go see the amazing Pysa tutorial that should get you up to speed finding security vulne

Pyre is a performant type checker for Python compliant with PEP 484. Pyre can analyze codebases with millions of lines of code incrementally – providi

A free and open-source chess improvement app that combines the power of Lichess and Anki. Chessli Project Activity & Issue Tracking PyPI Build & Healt

C2F-FWN data/code repository of "C2F-FWN: Coarse-to-Fine Flow Warping Network for Spatial-Temporal Consistent Motion Transfer" (https://arxiv.org/abs/

Ucto for Python This is a Python binding to the tokeniser Ucto. Tokenisation is one of the first step in almost any Natural Language Processing task,

Documentation: https://raamana.github.io/neuropredict/ News As of v0.6, neuropredict now supports regression applications i.e. predicting continuous t

Pyre is a performant type checker for Python compliant with PEP 484. Pyre can analyze codebases with millions of lines of code incrementally – providi