Solution to Comprevawe from VolgaCTF Quals 2017

decomprewave.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
from math import log2, ceil
import numpy as np
from skimage.io import imread, imsave
import pywt

def processData(fs, sizeW, sizeH, mode = 'symmetric'):
    coeffs = fs[:int(sizeW), :int(sizeH)]
    cA = coeffs[:int(sizeW/2), :int(sizeH/2)]
    cH = coeffs[int(sizeW/2):, :int(sizeH/2)]
    cV = coeffs[:int(sizeW/2), int(sizeH/2):]
    cD = coeffs[int(sizeW/2):, int(sizeH/2):]
    return pywt.idwt2([cA, (cH, cV, cD)], 'db2', mode)

def pad(image):
    rows, cols = image.shape
    n = 2**int(max(ceil(log2(rows)), ceil(log2(cols))))
    image_padded = np.zeros((n, n), dtype=np.float64)
    image_padded[n-rows:n, n-cols:n] = image
    return image_padded


if __name__ == '__main__':
    fs = np.load('./fs.npy')
    mode = 'smooth'
    size = 4
    threshold = 0.8

    sizeH, sizeW = fs.shape
    while size <= sizeH:
        newData = pad(processData(fs, size, size, mode=mode))
        (newX, newY) = newData.shape
        fs[:newX, :newY] = newData
        size *= 2

    fs[fs > threshold] = threshold
    fs[fs <-threshold] = -threshold
    imsave('./solution.png', fs)