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
The official repo for OC-SORT: Observation-Centric SORT on video Multi-Object Tracking. OC-SORT is simple, online and robust to occlusion/non-linear motion.

OC-SORT Observation-Centric SORT (OC-SORT) is a pure motion-model-based multi-object tracker. It aims to improve tracking robustness in crowded scenes

Jinkun Cao 325 Jan 05, 2023
UFPR-ADMR-v2 Dataset

UFPR-ADMR-v2 Dataset The UFPR-ADMRv2 dataset contains 5,000 dial meter images obtained on-site by employees of the Energy Company of Paraná (Copel), w

Gabriel Salomon 8 Sep 29, 2022
Fashion Entity Classification

Fashion-Entity-Classification - Fashion-MNIST is a dataset of Zalando's article images—consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28x28 grays

ADITYA SHAH 1 Jan 04, 2022
OptaPlanner wrappers for Python. Currently significantly slower than OptaPlanner in Java or Kotlin.

OptaPy is an AI constraint solver for Python to optimize the Vehicle Routing Problem, Employee Rostering, Maintenance Scheduling, Task Assignment, School Timetabling, Cloud Optimization, Conference S

OptaPy 211 Jan 02, 2023
This is the official code for the paper "Tracker Meets Night: A Transformer Enhancer for UAV Tracking".

SCT This is the official code for the paper "Tracker Meets Night: A Transformer Enhancer for UAV Tracking" The spatial-channel Transformer (SCT) enhan

Intelligent Vision for Robotics in Complex Environment 27 Nov 23, 2022
A Light CNN for Deep Face Representation with Noisy Labels

A Light CNN for Deep Face Representation with Noisy Labels Citation If you use our models, please cite the following paper: @article{wulight, title=

Alfred Xiang Wu 715 Nov 05, 2022
PrimitiveNet: Primitive Instance Segmentation with Local Primitive Embedding under Adversarial Metric (ICCV 2021)

PrimitiveNet Source code for the paper: Jingwei Huang, Yanfeng Zhang, Mingwei Sun. [PrimitiveNet: Primitive Instance Segmentation with Local Primitive

Jingwei Huang 47 Dec 06, 2022
Official implementation of EdiTTS: Score-based Editing for Controllable Text-to-Speech

EdiTTS: Score-based Editing for Controllable Text-to-Speech Official implementation of EdiTTS: Score-based Editing for Controllable Text-to-Speech. Au

Neosapience 98 Dec 25, 2022
Official Code for "Constrained Mean Shift Using Distant Yet Related Neighbors for Representation Learning"

CMSF Official Code for "Constrained Mean Shift Using Distant Yet Related Neighbors for Representation Learning" Requirements Python = 3.7.6 PyTorch

4 Nov 25, 2022
Paddle implementation for "Highly Efficient Knowledge Graph Embedding Learning with Closed-Form Orthogonal Procrustes Analysis" (NAACL 2021)

ProcrustEs-KGE Paddle implementation for Highly Efficient Knowledge Graph Embedding Learning with Orthogonal Procrustes Analysis 🙈 A more detailed re

Lincedo Lab 4 Jun 09, 2021
[IROS2021] NYU-VPR: Long-Term Visual Place Recognition Benchmark with View Direction and Data Anonymization Influences

NYU-VPR This repository provides the experiment code for the paper Long-Term Visual Place Recognition Benchmark with View Direction and Data Anonymiza

Automation and Intelligence for Civil Engineering (AI4CE) Lab @ NYU 22 Sep 28, 2022
TorchOk - The toolkit for fast Deep Learning experiments in Computer Vision

TorchOk - The toolkit for fast Deep Learning experiments in Computer Vision

52 Dec 23, 2022
Sign Language Translation with Transformers (COLING'2020, ECCV'20 SLRTP Workshop)

transformer-slt This repository gathers data and code supporting the experiments in the paper Better Sign Language Translation with STMC-Transformer.

Kayo Yin 107 Dec 27, 2022
ReferFormer - Official Implementation of ReferFormer

The official implementation of the paper: Language as Queries for Referring Vide

Jonas Wu 232 Dec 29, 2022
Use stochastic processes to generate samples and use them to train a fully-connected neural network based on Keras

Use stochastic processes to generate samples and use them to train a fully-connected neural network based on Keras which will then be used to generate residuals

Federico Lopez 2 Jan 14, 2022
Naszilla is a Python library for neural architecture search (NAS)

A repository to compare many popular NAS algorithms seamlessly across three popular benchmarks (NASBench 101, 201, and 301). You can implement your ow

270 Jan 03, 2023
Our VMAgent is a platform for exploiting Reinforcement Learning (RL) on Virtual Machine (VM) scheduling tasks.

VMAgent is a platform for exploiting Reinforcement Learning (RL) on Virtual Machine (VM) scheduling tasks. VMAgent is constructed based on one month r

56 Dec 12, 2022
The source code for Adaptive Kernel Graph Neural Network at AAAI2022

AKGNN The source code for Adaptive Kernel Graph Neural Network at AAAI2022. Please cite our paper if you think our work is helpful to you: @inproceedi

11 Nov 25, 2022
Implementation of MA-Trace - a general-purpose multi-agent RL algorithm for cooperative environments.

Off-Policy Correction For Multi-Agent Reinforcement Learning This repository is the official implementation of Off-Policy Correction For Multi-Agent R

4 Aug 18, 2022
[ICLR 2021] "Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective" by Wuyang Chen, Xinyu Gong, Zhangyang Wang

Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective [PDF] Wuyang Chen, Xinyu Gong, Zhangyang Wang In ICLR 2

VITA 156 Nov 28, 2022