A simple image/video to Desmos graph converter run locally

Overview

Desmos Bezier Renderer

A simple image/video to Desmos graph converter run locally

Sample

Result

Setup

Install dependencies

apt update
apt install git python3-dev python3-pip build-essential libagg-dev libpotrace-dev pkg-config

Clone repository

git clone [email protected]:kevinjycui/DesmosBezierRenderer.git
cd DesmosBezierRenderer

Install requirements

python3 -m venv env
. env/bin/activate
pip3 install -r requirements.txt

Create a directory called frames and add images named frame%d.png where %d represents the frame-number starting from 1. To render just a single image, add a single image named frame1.png in the directory. Works best with 360p to 480p resolution (may have to lower the resolution further with more complex frames).

You can change the DYNAMIC_BLOCK, BLOCK_SIZE, and MAX_EXPR_PER_BLOCK constants in backend.py to change the number of expressions the backend will send to the frontend per call (too much will cause a memory error, too little could kill the backend with too many requests). This only really matters if you are rendering a video.

mkdir frames
...

Run backend (This may take a while depending on the size and complexity of the frames). Should eventually show that the server is running on localhost:5000.

python3 backend.py

Load index.html into a web browser and run init() in the developer console. The image should start rendering or the video should start playing at a slow rate.

Owner
Kevin JY Cui
McGill University, B.Sc. Computer Science. Software Development. Sometimes known as Junferno on the internet
Kevin JY Cui
A Python library for unevenly-spaced time series analysis

traces A Python library for unevenly-spaced time series analysis. Why? Taking measurements at irregular intervals is common, but most tools are primar

Datascope Analytics 516 Dec 29, 2022
Sign-to-Speech for Sign Language Understanding: A case study of Nigerian Sign Language

Sign-to-Speech for Sign Language Understanding: A case study of Nigerian Sign Language This repository contains the code, model, and deployment config

16 Oct 23, 2022
Scalable training for dense retrieval models.

Scalable implementation of dense retrieval. Training on cluster By default it trains locally: PYTHONPATH=.:$PYTHONPATH python dpr_scale/main.py traine

Facebook Research 90 Dec 28, 2022
This repository contains the accompanying code for Deep Virtual Markers for Articulated 3D Shapes, ICCV'21

Deep Virtual Markers This repository contains the accompanying code for Deep Virtual Markers for Articulated 3D Shapes, ICCV'21 Getting Started Get sa

KimHyomin 45 Oct 07, 2022
Package for working with hypernetworks in PyTorch.

Package for working with hypernetworks in PyTorch.

Christian Henning 71 Jan 05, 2023
TensorFlow tutorials and best practices.

Effective TensorFlow 2 Table of Contents Part I: TensorFlow 2 Fundamentals TensorFlow 2 Basics Broadcasting the good and the ugly Take advantage of th

Vahid Kazemi 8.7k Dec 31, 2022
LibFewShot: A Comprehensive Library for Few-shot Learning.

LibFewShot Make few-shot learning easy. Supported Methods Meta MAML(ICML'17) ANIL(ICLR'20) R2D2(ICLR'19) Versa(NeurIPS'18) LEO(ICLR'19) MTL(CVPR'19) M

<a href=[email protected]&L"> 603 Jan 05, 2023
A Pytorch Implementation of Source Data-free Domain Adaptation for a Faster R-CNN

A Pytorch Implementation of Source Data-free Domain Adaptation for a Faster R-CNN Please follow Faster R-CNN and DAF to complete the environment confi

2 Jan 12, 2022
A web porting for NVlabs' StyleGAN2, to facilitate exploring all kinds characteristic of StyleGAN networks

This project is a web porting for NVlabs' StyleGAN2, to facilitate exploring all kinds characteristic of StyleGAN networks. Thanks for NVlabs' excelle

K.L. 150 Dec 15, 2022
Unsupervised Representation Learning by Invariance Propagation

Unsupervised Learning by Invariance Propagation This repository is the official implementation of Unsupervised Learning by Invariance Propagation. Pre

FengWang 15 Jul 06, 2022
HistoSeg : Quick attention with multi-loss function for multi-structure segmentation in digital histology images

HistoSeg : Quick attention with multi-loss function for multi-structure segmentation in digital histology images Histological Image Segmentation This

Saad Wazir 11 Dec 16, 2022
A Fast Sequence Transducer Implementation with PyTorch Bindings

transducer A Fast Sequence Transducer Implementation with PyTorch Bindings. The corresponding publication is Sequence Transduction with Recurrent Neur

Awni Hannun 184 Dec 18, 2022
The datasets and code of ACL 2021 paper "Aspect-Category-Opinion-Sentiment Quadruple Extraction with Implicit Aspects and Opinions".

Aspect-Category-Opinion-Sentiment (ACOS) Quadruple Extraction This repo contains the data sets and source code of our paper: Aspect-Category-Opinion-S

NUSTM 144 Jan 02, 2023
Alternatives to Deep Neural Networks for Function Approximations in Finance

Alternatives to Deep Neural Networks for Function Approximations in Finance Code companion repo Overview This is a repository of Python code to go wit

15 Dec 17, 2022
Fully Convlutional Neural Networks for state-of-the-art time series classification

Deep Learning for Time Series Classification As the simplest type of time series data, univariate time series provides a reasonably good starting poin

Stephen 572 Dec 23, 2022
SAT: 2D Semantics Assisted Training for 3D Visual Grounding, ICCV 2021 (Oral)

SAT: 2D Semantics Assisted Training for 3D Visual Grounding SAT: 2D Semantics Assisted Training for 3D Visual Grounding by Zhengyuan Yang, Songyang Zh

Zhengyuan Yang 22 Nov 30, 2022
JFB: Jacobian-Free Backpropagation for Implicit Models

JFB: Jacobian-Free Backpropagation for Implicit Models

Typal Research 28 Dec 11, 2022
LieTransformer: Equivariant Self-Attention for Lie Groups

LieTransformer This repository contains the implementation of the LieTransformer used for experiments in the paper LieTransformer: Equivariant Self-At

OxCSML (Oxford Computational Statistics and Machine Learning) 50 Dec 28, 2022
Finite-temperature variational Monte Carlo calculation of uniform electron gas using neural canonical transformation.

CoulombGas This code implements the neural canonical transformation approach to the thermodynamic properties of uniform electron gas. Building on JAX,

FermiFlow 9 Mar 03, 2022
High-fidelity 3D Model Compression based on Key Spheres

High-fidelity 3D Model Compression based on Key Spheres This repository contains the implementation of the paper: Yuanzhan Li, Yuqi Liu, Yujie Lu, Siy

5 Oct 11, 2022