Python package provinding tools for artistic interactive applications using AI

Last update: Sep 30, 2021

Overview

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

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

Python package provinding tools for artistic interactive applications using AI

Related tags

Overview

redrawing

Installation

Stages

Data and communication

Authors

Legal

Owner

ReDrawing Campinas

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Python package provinding tools for artistic interactive applications using AI

Related tags

Overview

redrawing

Installation

Stages

Data and communication

Authors

Legal

Owner

ReDrawing Campinas

RATCHET is a Medical Transformer for Chest X-ray Diagnosis and Reporting

BisQue is a web-based platform designed to provide researchers with organizational and quantitative analysis tools for 5D image data. Users can extend BisQue by implementing containerized ML workflows.

Tensorflow 2 implementations of the C-SimCLR and C-BYOL self-supervised visual representation methods from "Compressive Visual Representations" (NeurIPS 2021)

🕺Full body detection and tracking

Final project code: Implementing BicycleGAN, for CIS680 FA21 at University of Pennsylvania

This is the official implementation of the paper "Object Propagation via Inter-Frame Attentions for Temporally Stable Video Instance Segmentation".

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Exploiting a Zoo of Checkpoints for Unseen Tasks

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Code for our ACL 2021 paper - ConSERT: A Contrastive Framework for Self-Supervised Sentence Representation Transfer

The Pytorch implementation for "Video-Text Pre-training with Learned Regions"

PyTorch implementation for our AAAI 2022 Paper "Graph-wise Common Latent Factor Extraction for Unsupervised Graph Representation Learning"

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