Python package provinding tools for artistic interactive applications using AI

Overview

Documentation

redrawing

Python package provinding tools for artistic interactive applications using AI

Created by ReDrawing Campinas team for the OpenCV AI 2021 Competition.

Installation

python -m pip install --upgrade pip
python -m pip install redrawing

Stages

Stages are the basic processing units of the redrawing package. They receive data objects from input channels, processes them and output data in the output channels.

Examples of stages:

Stage name Use
OAK_Stage Handles a OAK camera. Can be changed using OAK_Substages, like a Body detector or a Hand gesture detector
PCR_Viewer Visualizer for image, depth and body pose data
CameraReceiver/IMUReceiver Receives data from a smarthphone
UKF_IMU UKF filter for orientation estimation using IMU data

Data and communication

All inter stage data communication occours using Data classes.

Examples of data classes:

Data class Use
BodyPose Stores body pose data (keypoints)
Image Stores image data
Depth_Map Stores depth data
IMU Stores IMU data

For exchange data with client applications, the UDP_Stage can be used, using UDP protocol with JSON converted messages. We also have client libraries for receiving and decoding data:

  • redrawing_java: client library for Java
  • ReDrawing for Processing: client library for Processing, encapsulates the redrawing_java library

Authors

Legal

Copyright (c) 2021 ReDrawing Campinas AUTHORS

Submodules in ai_models/third_models submodules may be licensed under other licenses. A copy of the respective license can be found in the submodule folder.

Made with the support of "Conselho Nacional de Desenvolvimento Científico e Tecnológico" (CNPq) of Brazil

Owner
ReDrawing Campinas
ReDrawing the way we interact with interactive compositions. We are a team of students, teachers and researchers linked to Unicamp and CTI Renato Archer
ReDrawing Campinas
Tgbox-bench - Simple TGBOX upload speed benchmark

TGBOX Benchmark This script will benchmark upload speed to TGBOX storage. Build

Non 1 Jan 09, 2022
This package implements the algorithms introduced in Smucler, Sapienza, and Rotnitzky (2020) to compute optimal adjustment sets in causal graphical models.

optimaladj: A library for computing optimal adjustment sets in causal graphical models This package implements the algorithms introduced in Smucler, S

Facundo Sapienza 6 Aug 04, 2022
Code release for the ICML 2021 paper "PixelTransformer: Sample Conditioned Signal Generation".

PixelTransformer Code release for the ICML 2021 paper "PixelTransformer: Sample Conditioned Signal Generation". Project Page Installation Please insta

Shubham Tulsiani 24 Dec 17, 2022
Lowest memory consumption and second shortest runtime in NTIRE 2022 challenge on Efficient Super-Resolution

FMEN Lowest memory consumption and second shortest runtime in NTIRE 2022 on Efficient Super-Resolution. Our paper: Fast and Memory-Efficient Network T

33 Dec 01, 2022
Out-of-Town Recommendation with Travel Intention Modeling (AAAI2021)

TrainOR_AAAI21 This is the official implementation of our AAAI'21 paper: Haoran Xin, Xinjiang Lu, Tong Xu, Hao Liu, Jingjing Gu, Dejing Dou, Hui Xiong

Jack Xin 13 Oct 19, 2022
Tensors and neural networks in Haskell

Hasktorch Hasktorch is a library for tensors and neural networks in Haskell. It is an independent open source community project which leverages the co

hasktorch 920 Jan 04, 2023
OverFeat is a Convolutional Network-based image classifier and feature extractor.

OverFeat OverFeat is a Convolutional Network-based image classifier and feature extractor. OverFeat was trained on the ImageNet dataset and participat

593 Dec 08, 2022
Libraries, tools and tasks created and used at DeepMind Robotics.

Libraries, tools and tasks created and used at DeepMind Robotics.

DeepMind 270 Nov 30, 2022
Automated detection of anomalous exoplanet transits in light curve data.

Automatically detecting anomalous exoplanet transits This repository contains the source code for the paper "Automatically detecting anomalous exoplan

1 Feb 01, 2022
Probabilistic Gradient Boosting Machines

PGBM Probabilistic Gradient Boosting Machines (PGBM) is a probabilistic gradient boosting framework in Python based on PyTorch/Numba, developed by Air

Olivier Sprangers 112 Dec 28, 2022
The code for the NeurIPS 2021 paper "A Unified View of cGANs with and without Classifiers".

Energy-based Conditional Generative Adversarial Network (ECGAN) This is the code for the NeurIPS 2021 paper "A Unified View of cGANs with and without

sianchen 22 May 28, 2022
Transformer model implemented with Pytorch

transformer-pytorch Transformer model implemented with Pytorch Attention is all you need-[Paper] Architecture Self-Attention self_attention.py class

Mingu Kang 12 Sep 03, 2022
LIVECell - A large-scale dataset for label-free live cell segmentation

LIVECell dataset This document contains instructions of how to access the data associated with the submitted manuscript "LIVECell - A large-scale data

Sartorius Corporate Research 112 Jan 07, 2023
A two-stage U-Net for high-fidelity denoising of historical recordings

A two-stage U-Net for high-fidelity denoising of historical recordings Official repository of the paper (not submitted yet): E. Moliner and V. Välimäk

Eloi Moliner Juanpere 57 Jan 05, 2023
Object detection GUI based on PaddleDetection

PP-Tracking GUI界面测试版 本项目是基于飞桨开源的实时跟踪系统PP-Tracking开发的可视化界面 在PaddlePaddle中加入pyqt进行GUI页面研发,可使得整个训练过程可视化,并通过GUI界面进行调参,模型预测,视频输出等,通过多种类型的识别,简化整体预测流程。 GUI界面

杨毓栋 68 Jan 02, 2023
Low Complexity Channel estimation with Neural Network Solutions

Interpolation-ResNet Invited paper for WSA 2021, called 'Low Complexity Channel estimation with Neural Network Solutions'. Low complexity residual con

Dianxin 10 Dec 10, 2022
Instance-conditional Knowledge Distillation for Object Detection

Instance-conditional Knowledge Distillation for Object Detection This is a MegEngine implementation of the paper "Instance-conditional Knowledge Disti

MEGVII Research 47 Nov 17, 2022
Outlier Exposure with Confidence Control for Out-of-Distribution Detection

OOD-detection-using-OECC This repository contains the essential code for the paper Outlier Exposure with Confidence Control for Out-of-Distribution De

Nazim Shaikh 64 Nov 02, 2022
DynaTune: Dynamic Tensor Program Optimization in Deep Neural Network Compilation

DynaTune: Dynamic Tensor Program Optimization in Deep Neural Network Compilation This repository is the implementation of DynaTune paper. This folder

4 Nov 02, 2022
Bayesian dessert for Lasagne

Gelato Bayesian dessert for Lasagne Recent results in Bayesian statistics for constructing robust neural networks have proved that it is one of the be

Maxim Kochurov 84 May 11, 2020