Python Impelemtation of Wave Function Collapse

The goal of this repository is to create an innovative collection of solvers for the WFC algorithm. These could be energy-based or CSP(constraints solving problem)-based solvers. Contributions welcome!

Future Plans

• Speed up the current (very slow) pairwise comparison of tiles
• Update simulated annealing solver pertubation strategy
• Implement GPU slovers with Cupy or pytorch
• And, of course, add many more interesting solvers!!

Core Objects:

• TileDataset: Class for storing and transforming tiles extracted from 2D or 3D inputs
• WaveSolver, SimulatedAnnealingSolver: Classes for implementing brute force and annealing solver

Example Usage:

from wfc.wfc_tiler import TileDataset
from wfc.wfc_solver import WaveSolver, SimulatedAnnealingSolver 
import matplotlib.pyplot as plt

td_HW = TileDataset(bitcube=spiral_grey.astype(int), form='HW',  N=N, wrap_pad=True) # compare tiles
wavyHW = WaveSolver(td_HW, form='HW', output_size=(50, 50), wrap_pad=True) # initialize wave solver or simulated annealing solver
out_HW = wavyHW.solve() # solve
plt.imshow(out_HW) # plot
plt.savefig('HW_test.png') # save

Requirements

• python >= 3.9
• numpy >= 1.21
• matplotlib >= 3.5
• tqdm >= 4.64
• scipy >= 1.10
• pillow >= 9.0

Miklos Kralik miklos.a.kralik@gmail.com