Implémentation en pyhton de l'article Depixelizing pixel art de Johannes Kopf et Dani Lischinski

Overview

Projet INF8801A - Session A21

Groupe A :

  • Mathis Lamidey, @Ithyx
  • Hugo Vandenbroucke-Menu, @thehyouz

Notre projet consistait à ré-implémenter en parti l'article "Depixelizing Pixel Art" de Johannes Kopf et Dani Lischinski. Disponible ici : https://johanneskopf.de/publications/pixelart/paper/pixel.pdf

Les images utilisées proviennent du dataset de l'article. Disponible ici : http://johanneskopf.de/publications/pixelart/supplementary/multi_comparison.html

Notre implémentation est en Python et il est possible de la lancer depuis le fichier main.ipynb.

Pipeline et exemple

pipeline

Pour un exemple détaillé de résultats, voir les images dans le dossier output.

Requis

L'ensemble des librairies nécessaire sont décrites dans le fichier requirements.txt. Pour les installer, utiliser pip install -r requirements.txt. Pour la bonne exécution du script, assurez-vous que le dossier output existe bien.

Utilisation

Notre code est présenté sous forme d'un jupyter notebook qui fait les appels de fonctions nécessaire pour traiter les images. Nous fournissons nos images de test dans le dossier data, et lors de l'exécution du notebook, en plus des images affichées directement dans le notebook, une copie sera sauvegardée dans le dossier output si vous changez le paramètre saveFig des signatures de fonction d'affichage (en utilisant les variables globales en haut du notebook). Nous vous encourageons à tester de changer l'image en entrée du programme, en modifiant le chemin dans la cellule "Step 1", mais notez que l'algorithme ne marche bien que sur des images de pixel art en basse résolution. Si vous essayez avec une image de trop grande taille, vous risquer un temps d'exécution très long.

Owner
TableauBits
TableauBits
[PAMI 2020] Show, Match and Segment: Joint Weakly Supervised Learning of Semantic Matching and Object Co-segmentation

Show, Match and Segment: Joint Weakly Supervised Learning of Semantic Matching and Object Co-segmentation This repository contains the source code for

Yun-Chun Chen 60 Nov 25, 2022
Template repository to build PyTorch projects from source on any version of PyTorch/CUDA/cuDNN.

The Ultimate PyTorch Source-Build Template Translations: 한국어 TL;DR PyTorch built from source can be x4 faster than a naïve PyTorch install. This repos

Joonhyung Lee/이준형 651 Dec 12, 2022
Functional TensorFlow Implementation of Singular Value Decomposition for paper Fast Graph Learning

tf-fsvd TensorFlow Implementation of Functional Singular Value Decomposition for paper Fast Graph Learning with Unique Optimal Solutions Cite If you f

Sami Abu-El-Haija 14 Nov 25, 2021
A SAT-based sudoku solver

SAT Sudoku solver A SAT-based Sudoku solver made in the context of a small project in the "Logic Problem Solving" class in the first year at the Polyt

Alexandre Malfreyt 5 Apr 15, 2022
Code for "Continuous-Time Meta-Learning with Forward Mode Differentiation" (ICLR 2022)

Continuous-Time Meta-Learning with Forward Mode Differentiation ICLR 2022 (Spotlight) - Installation - Example - Citation This repository contains the

Tristan Deleu 25 Oct 20, 2022
A curated list of Generative Deep Art projects, tools, artworks, and models

Generative Deep Art A curated list of Generative Deep Art projects, tools, artworks, and models Inbox Get started with making AI art in 2022 – deeplea

Filipe Calegario 251 Jan 03, 2023
DilatedNet in Keras for image segmentation

Keras implementation of DilatedNet for semantic segmentation A native Keras implementation of semantic segmentation according to Multi-Scale Context A

303 Mar 15, 2022
It's like Shape Editor in Maya but works with skeletons (transforms).

Skeleposer What is Skeleposer? Briefly, it's like Shape Editor in Maya, but works with transforms and joints. It can be used to make complex facial ri

Alexander Zagoruyko 1 Nov 11, 2022
Nightmare-Writeup - Writeup for the Nightmare CTF Challenge from 2022 DiceCTF

Nightmare: One Byte to ROP // Alternate Solution TLDR: One byte write, no leak.

1 Feb 17, 2022
Deep Learning to Create StepMania SM FIles

StepCOVNet Running Audio to SM File Generator Currently only produces .txt files. Use SMDataTools to convert .txt to .sm python stepmania_note_generat

Chimezie Iwuanyanwu 8 Jan 08, 2023
Official Pytorch implementation of 6DRepNet: 6D Rotation representation for unconstrained head pose estimation.

6D Rotation Representation for Unconstrained Head Pose Estimation (Pytorch) Paper Thorsten Hempel and Ahmed A. Abdelrahman and Ayoub Al-Hamadi, "6D Ro

Thorsten Hempel 284 Dec 23, 2022
This repository is an implementation of our NeurIPS 2021 paper (Stylized Dialogue Generation with Multi-Pass Dual Learning) in PyTorch.

MPDL---TODO This repository is an implementation of our NeurIPS 2021 paper (Stylized Dialogue Generation with Multi-Pass Dual Learning) in PyTorch. Ci

CodebaseLi 3 Nov 27, 2022
Detecting drunk people through thermal images using Deep Learning (CNN)

Drunk Detection CNN Detecting drunk people through thermal images using Deep Learning (CNN) Dataset We used thermal images provided by Electronics Lab

Giacomo Ferretti 3 Oct 27, 2022
"SOLQ: Segmenting Objects by Learning Queries", SOLQ is an end-to-end instance segmentation framework with Transformer.

SOLQ: Segmenting Objects by Learning Queries This repository is an official implementation of the paper SOLQ: Segmenting Objects by Learning Queries.

MEGVII Research 179 Jan 02, 2023
End-to-end speech secognition toolkit

End-to-end speech secognition toolkit This is an E2E ASR toolkit modified from Espnet1 (version 0.9.9). This is the official implementation of paper:

Jinchuan Tian 147 Dec 28, 2022
TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale.

TorchMultimodal (Alpha Release) Introduction TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale.

Meta Research 663 Jan 06, 2023
Cupytorch - A small framework mimics PyTorch using CuPy or NumPy

CuPyTorch CuPyTorch是一个小型PyTorch,名字来源于: 不同于已有的几个使用NumPy实现PyTorch的开源项目,本项目通过CuPy支持

Xingkai Yu 23 Aug 17, 2022
Existing Literature about Machine Unlearning

Machine Unlearning Papers 2021 Brophy and Lowd. Machine Unlearning for Random Forests. In ICML 2021. Bourtoule et al. Machine Unlearning. In IEEE Symp

Jonathan Brophy 213 Jan 08, 2023
Torch code for our CVPR 2018 paper "Residual Dense Network for Image Super-Resolution" (Spotlight)

Residual Dense Network for Image Super-Resolution This repository is for RDN introduced in the following paper Yulun Zhang, Yapeng Tian, Yu Kong, Bine

Yulun Zhang 494 Dec 30, 2022
Asterisk is a framework to generate high-quality training datasets at scale

Asterisk is a framework to generate high-quality training datasets at scale

Mona Nashaat 44 Apr 25, 2022