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
MoCoPnet - Deformable 3D Convolution for Video Super-Resolution

Deformable 3D Convolution for Video Super-Resolution Pytorch implementation of l

Xinyi Ying 28 Dec 15, 2022
FaceOcc: A Diverse, High-quality Face Occlusion Dataset for Human Face Extraction

FaceExtraction FaceOcc: A Diverse, High-quality Face Occlusion Dataset for Human Face Extraction Occlusions often occur in face images in the wild, tr

16 Dec 14, 2022
Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices

Intro Real-time object detection and classification. Paper: version 1, version 2. Read more about YOLO (in darknet) and download weight files here. In

Trieu 6.1k Dec 30, 2022
Shitty gaze mouse controller

demo.mp4 shitty_gaze_mouse_cotroller install tensofflow, cv2 run the main.py and as it starts it will collect data so first raise your left eyebrow(bo

16 Aug 30, 2022
This repository contains the code for: RerrFact model for SciVer shared task

RerrFact This repository contains the code for: RerrFact model for SciVer shared task. Setup for Inference 1. Download SciFact database Download the S

Ashish Rana 1 May 22, 2022
The official code of Anisotropic Stroke Control for Multiple Artists Style Transfer

ASMA-GAN Anisotropic Stroke Control for Multiple Artists Style Transfer Proceedings of the 28th ACM International Conference on Multimedia The officia

Six_God 146 Nov 21, 2022
ivadomed is an integrated framework for medical image analysis with deep learning.

Repository on the collaborative IVADO medical imaging project between the Mila and NeuroPoly labs.

144 Dec 19, 2022
A tensorflow implementation of GCN-LPA

GCN-LPA This repository is the implementation of GCN-LPA (arXiv): Unifying Graph Convolutional Neural Networks and Label Propagation Hongwei Wang, Jur

Hongwei Wang 83 Nov 28, 2022
salabim - discrete event simulation in Python

Object oriented discrete event simulation and animation in Python. Includes process control features, resources, queues, monitors. statistical distrib

181 Dec 21, 2022
A hand tracking demo made with mediapipe where you can control lights with pinching your fingers and moving your hand up/down.

HandTrackingBrightnessControl A hand tracking demo made with mediapipe where you can control lights with pinching your fingers and moving your hand up

Teemu Laurila 19 Feb 12, 2022
Predicting 10 different clothing types using Xception pre-trained model.

Predicting-Clothing-Types Predicting 10 different clothing types using Xception pre-trained model from Keras library. It is reimplemented version from

AbdAssalam Ahmad 3 Dec 29, 2021
Single cell current best practices tutorial case study for the paper:Luecken and Theis, "Current best practices in single-cell RNA-seq analysis: a tutorial"

Scripts for "Current best-practices in single-cell RNA-seq: a tutorial" This repository is complementary to the publication: M.D. Luecken, F.J. Theis,

Theis Lab 968 Dec 28, 2022
Miscellaneous and lightweight network tools

Network Tools Collection of miscellaneous and lightweight network tools to simplify daily operations, administration, and troubleshooting of networks.

Nicholas Russo 22 Mar 22, 2022
a basic code repository for basic task in CV(classification,detection,segmentation)

basic_cv a basic code repository for basic task in CV(classification,detection,segmentation,tracking) classification generate dataset train predict de

1 Oct 15, 2021
Another pytorch implementation of FCN (Fully Convolutional Networks)

FCN-pytorch-easiest Trying to be the easiest FCN pytorch implementation and just in a get and use fashion Here I use a handbag semantic segmentation f

Y. Dong 158 Dec 21, 2022
Einshape: DSL-based reshaping library for JAX and other frameworks.

Einshape: DSL-based reshaping library for JAX and other frameworks. The jnp.einsum op provides a DSL-based unified interface to matmul and tensordot o

DeepMind 62 Nov 30, 2022
This repository includes the official project for the paper: TransMix: Attend to Mix for Vision Transformers.

TransMix: Attend to Mix for Vision Transformers This repository includes the official project for the paper: TransMix: Attend to Mix for Vision Transf

Jie-Neng Chen 130 Jan 01, 2023
An implementation of the methods presented in Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data.

An implementation of the methods presented in Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data.

Andrew Jesson 9 Apr 04, 2022
Swapping face using Face Mesh with TensorFlow Lite

Swapping face using Face Mesh with TensorFlow Lite

iwatake 17 Apr 26, 2022
Motion and Shape Capture from Sparse Markers

MoSh++ This repository contains the official chumpy implementation of mocap body solver used for AMASS: AMASS: Archive of Motion Capture as Surface Sh

Nima Ghorbani 135 Dec 23, 2022