app.py

from pybrain.tools.shortcuts import buildNetwork
from pybrain.tools.xml import NetworkWriter
from pybrain.tools.xml import NetworkReader
from pybrain.datasets import SupervisedDataSet
from pybrain.supervised.trainers import BackpropTrainer

import cv2
import numpy as np

net = buildNetwork(921600, 12, 921600)
ds = SupervisedDataSet(921600, 921600)
trainer = BackpropTrainer(net, ds)

imageArray = []
for it in range(1,51):
	imageArray.append(str(it) + '.jpg')

print imageArray
for image in imageArray:
    outputImage = image
    resultImage = 'result.jpg'
    inputImage = 'input.jpg'
    otherImage = 'other.jpg'
    #LOAD IMAGE FILES
    imgIn = cv2.imread(inputImage)
    imgOut = cv2.imread(outputImage)
    imgResult = cv2.imread(resultImage)
    imgOther = cv2.imread(otherImage)
    #BIT ARRAYS FOR EACH IMAGE
    imagebitsInput = []
    imagebitsOutput = []
    imagebitsOther = []
    #CONVERT INPUT TO GRAYSCALE
    gray_in = cv2.cvtColor(imgIn, cv2.COLOR_BGR2GRAY)
    gray_out = cv2.cvtColor(imgOut, cv2.COLOR_BGR2GRAY)
    gray_other = cv2.cvtColor(imgOther, cv2.COLOR_BGR2GRAY)
    #FILL BIT ARRAYS
    for row in gray_in:
        for pixel in row:
            imagebitsInput.append(pixel)
    for row in gray_out:
        for pixel in row:
            imagebitsOutput.append(pixel)
    for row in gray_other:
        for pixel in row:
            imagebitsOther.append(pixel)
    ds.addSample(imagebitsInput, imagebitsOutput)

trainer.trainEpochs(epochs=4)

imagebitsFinal = net.activate(imagebitsOther)

for it in range(720): #y
	for it2 in range(1280): #x
		imgResult[it][it2] = imagebitsFinal[(1280*it)+it2]

cv2.imwrite('result.jpg', imgResult)
print 'Images in training set: '
print len(ds)