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
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