anopara/patch-based-texture-synthesis

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Created almost 6 years ago
Updated almost 6 years ago

anopara/patch-based-texture-synthesis

anopara

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Based on "Image Quilting for Texture Synthesis and Transfer" and "Real-Time Texture Synthesis by Patch-Based Sampling" papers

patch-based-texture-synthesis

Based on "Image Quilting for Texture Synthesis and Transfer" and "Real-Time Texture Synthesis by Patch-Based Sampling" papers

Python

Here are the libraries and their versions you will need:

Python 3.7
Jupyter Notebook (5.6.0)
Numpy (is 1.15.1)
Matplotlib (2.2.3)
Scipy (1.1.0)
Skimage (0.14.0)
scikit-learn (0.19.2)
imageio (2.4.1)
PIL (5.2.0)

To start, open the Jupyter Notebook file "Patch-based Texture Synthesis", and follow the instructions :)

Below you can see the effect of different patch sizes:

genetic-drawing

A genetic algorithm toy project for drawing

country-slice

texture-synthesis-nonparametric-sampling

Implementation of "Texture Synthesis with Non-Parametric Sampling" paper by Alexei A. Efros and Thomas K. Leung

Jupyter Notebook

multi-resolution-texture-synthesis

Based on “Fast Texture Synthesis using Tree-structured Vector Quantization” and “Multiresolution Sampling Procedure for Analysis and Synthesis of Texture Images” papers

Jupyter Notebook

presentation-houdini-vis

Houdini files of visualizations from my presentation "Place like I do! Example-based procedural placements in a dialogue system"

example-based-procedural-placement

A description and links to the Example-based Procedural Placement algorithm slides and presentation

texture-optimization

Based on "Texture optimization for example-based synthesis" by Vivek Kwatra, Irfan Essa, Aaron Bobick, and Nipun Kwatra

spectral-processing

personal tests/experiments/exercises connected with spectral mesh processing

Jupyter Notebook