Joint parameterization and fitting of stroke clusters

Overview

StrokeStrip: Joint Parameterization and Fitting of Stroke Clusters

Dave Pagurek van Mossel1, Chenxi Liu1, Nicholas Vining1,2, Mikhail Bessmeltsev3, Alla Sheffer1

1University of British Columbia, 2NVIDIA, 3Université de Montréal

@article{strokestrip,
	title = {StrokeStrip: Joint Parameterization and Fitting of Stroke Clusters},
	author = {Pagurek van Mossel, Dave and Liu, Chenxi and Vining, Nicholas and Bessmeltsev, Mikhail and Sheffer, Alla},
	year = 2021,
	journal = {ACM Transactions on Graphics},
	publisher = {ACM},
	address = {New York, NY, USA},
	volume = 40,
	number = 4,
	doi = {10.1145/3450626.3459777}
}

StrokeStrip jointly parameterizes clusters of strokes (a) that, together, represent strips following a single intended curve (b). We compute the parameterization of this strip (c) restricted to the domain of the input strokes (d), which we then use to produce the parameterized intended curve (d).

Usage

./strokestrip input.scap [...args]

Additional optional arguments:

  • --cut: If your input strokes include sharp back-and-forth turns, this flag will use the Cornucopia library to detect and cut such strokes.
  • --debug: Generate extra SVG outputs to introspect the algorithm
  • --rainbow: Generate an SVG showing parameterized strokes coloured with a rainbow gradient (default is red-to-blue)
  • --widths: Generate fitted widths along with centerlines
  • --taper: Force fitted widths to taper to 0 at endpoints

Input format

Drawings are inputted as .scap files, which encode strokes as polylines. Strokes are contained in pairs of braces { ... }. Each stroke has a unique stroke id and a cluster id shared by all strokes that colleectively make up one intended curve. Polyline samples can omit pressure by setting it to a default value of 0.

#[width]	[height]
@[thickness]
{
	#[stroke_id]	[cluster_id]
	[x1]	[y1]	[pressure1]
	[x2]	[y2]	[pressure2]
	[x3]	[y3]	[pressure3]
	[...etc]
}
[...etc]

Example .scap inputs are found in the examples/ directory.

Stroke clusters for new .scap files can be generated using the StrokeAggregator ground truth labeling program.

Development

Dependencies

Gurobi

This package relies on the Gurobi optimization library, which must be installed and licensed on your machine. If you are at a university, a free academic license can be obtained. This project was build with Gurobi 9.0; if you are using a newer version of Gurobi, update FindGUROBI.cmake to reference your installed version (e.g. change gurobi90 to gurobi91 for version 9.1.)

Eigen 3

Ensure that Eigen is installed and that its directory is included in $CMAKE_PREFIX_PATH.

Building

StrokeStrip is configured with Cmake:

mkdir build
cd build
cmake ..
make
Owner
Dave Pagurek
Programmer and digital artist. MSc from UBC CS '21, UWaterloo Software Engineering '19.
Dave Pagurek
Generate images from texts. In Russian. In PaddlePaddle

ruDALL-E PaddlePaddle ruDALL-E in PaddlePaddle. Install: pip install rudalle_paddle==0.0.1rc1 Run with free v100 on AI Studio. Original Pytorch versi

AgentMaker 20 Oct 18, 2022
A Robust Unsupervised Ensemble of Feature-Based Explanations using Restricted Boltzmann Machines

A Robust Unsupervised Ensemble of Feature-Based Explanations using Restricted Boltzmann Machines Understanding the results of deep neural networks is

Johan van den Heuvel 2 Dec 13, 2021
AdelaiDet is an open source toolbox for multiple instance-level detection and recognition tasks.

AdelaiDet is an open source toolbox for multiple instance-level detection and recognition tasks.

Adelaide Intelligent Machines (AIM) Group 3k Jan 02, 2023
Weighted QMIX: Expanding Monotonic Value Function Factorisation

This repo contains the cleaned-up code that was used in "Weighted QMIX: Expanding Monotonic Value Function Factorisation"

whirl 82 Dec 29, 2022
Pairwise learning neural link prediction for ogb link prediction

Pairwise Learning for Neural Link Prediction for OGB (PLNLP-OGB) This repository provides evaluation codes of PLNLP for OGB link property prediction t

Zhitao WANG 31 Oct 10, 2022
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening Introduction This is an implementation of the model used for breast

757 Dec 30, 2022
mbrl-lib is a toolbox for facilitating development of Model-Based Reinforcement Learning algorithms.

mbrl-lib is a toolbox for facilitating development of Model-Based Reinforcement Learning algorithms. It provides easily interchangeable modeling and planning components, and a set of utility function

Facebook Research 724 Jan 04, 2023
T-LOAM: Truncated Least Squares Lidar-only Odometry and Mapping in Real-Time

T-LOAM: Truncated Least Squares Lidar-only Odometry and Mapping in Real-Time The first Lidar-only odometry framework with high performance based on tr

Pengwei Zhou 183 Dec 01, 2022
💛 Code and Dataset for our EMNLP 2021 paper: "Perspective-taking and Pragmatics for Generating Empathetic Responses Focused on Emotion Causes"

Perspective-taking and Pragmatics for Generating Empathetic Responses Focused on Emotion Causes Official PyTorch implementation and EmoCause evaluatio

Hyunwoo Kim 51 Jan 06, 2023
Unofficial implementation of the ImageNet, CIFAR 10 and SVHN Augmentation Policies learned by AutoAugment using pillow

AutoAugment - Learning Augmentation Policies from Data Unofficial implementation of the ImageNet, CIFAR10 and SVHN Augmentation Policies learned by Au

Philip Popien 1.3k Jan 02, 2023
Using image super resolution models with vapoursynth and speeding them up with TensorRT

vs-RealEsrganAnime-tensorrt-docker Using image super resolution models with vapoursynth and speeding them up with TensorRT. Also a docker image since

4 Aug 23, 2022
Neurons Dataset API - The official dataloader and visualization tools for Neurons Datasets.

Neurons Dataset API - The official dataloader and visualization tools for Neurons Datasets. Introduction We propose our dataloader API for loading and

1 Nov 19, 2021
Python-kafka-reset-consumergroup-offset-example - Python Kafka reset consumergroup offset example

Python Kafka reset consumergroup offset example This is a simple example of how

Willi Carlsen 1 Feb 16, 2022
Official Implementation of "LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks"

LUNAR Official Implementation of "LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks" Adam Goodge, Bryan Hooi, Ng See Kiong and

Adam Goodge 25 Dec 28, 2022
Towards the D-Optimal Online Experiment Design for Recommender Selection (KDD 2021)

Towards the D-Optimal Online Experiment Design for Recommender Selection (KDD 2021) Contact 0 Jan 11, 2022

Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression

Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression YOLOv5 with alpha-IoU losses implemented in PyTorch. Example r

Jacobi(Jiabo He) 147 Dec 05, 2022
Chinese license plate recognition

AgentCLPR 简介 一个基于 ONNXRuntime、AgentOCR 和 License-Plate-Detector 项目开发的中国车牌检测识别系统。 车牌识别效果 支持多种车牌的检测和识别(其中单层车牌识别效果较好): 单层车牌: [[[[373, 282], [69, 284],

AgentMaker 26 Dec 25, 2022
Implementation of Convolutional LSTM in PyTorch.

ConvLSTM_pytorch This file contains the implementation of Convolutional LSTM in PyTorch made by me and DavideA. We started from this implementation an

Andrea Palazzi 1.3k Dec 29, 2022
Image data augmentation scheduler for albumentations transforms

albu_scheduler Scheduler for albumentations transforms based on PyTorch schedulers interface Usage TransformMultiStepScheduler import albumentations a

19 Aug 04, 2021
Final Project for the CS238: Decision Making Under Uncertainty course at Stanford University in Autumn '21.

Final Project for the CS238: Decision Making Under Uncertainty course at Stanford University in Autumn '21. We optimized wind turbine placement in a wind farm, subject to wake effects, using Q-learni

Manasi Sharma 2 Sep 27, 2022