Most possible combinations of disparity

import cv2
import numpy as np
import re

testMode = True

# Using http://vision.middlebury.edu/stereo/data/scenes2006/FullSize/zip-2views/Aloe-2views.zip
# Using http://vision.middlebury.edu/stereo/data/scenes2006/FullSize/zip-2views/Bowling1-2views.zip

datasets = [
    {
        "leftStereoImg": "./Bowling1/view1.png",
        "rightStereoImg": "./Bowling1/view5.png",
        "leftDisparityMap": "./Bowling1/disp1.png",
        "rightDisparityMap": "./Bowling1/disp5.png"
    }
    ,
    {
        "leftStereoImg": "./Aloe/view1.png",
        "rightStereoImg": "./Aloe/view5.png",
       "leftDisparityMap": "./Aloe/disp1.png",
        "rightDisparityMap": "./Aloe/disp5.png"
    }
]

datasetToUse = 0
dataset = datasets[datasetToUse]

leftStereoImg = cv2.imread(dataset["leftStereoImg"])
rightStereoImg = cv2.imread(dataset["rightStereoImg"])

[rows, columns, channels] = leftStereoImg.shape # TODO: better image shape comparison logic


def parseInputToUnderstandShiftingLogic(shiftingDescription):
    # example input:
    #   "shift leftStereoImg to the right using leftDisparityMap to get rightStereoImg"
    regexExpressions = {
        "imageToShift": r"(?![(shift)\s])\w+(?=( to the))",
        "action": r"(?![(to the)\s])\w+(?=( using))",
        "disparityMapToUse": r"(?![(using)\s])\w+(?=( to get))",
        "expectedResultingImage": r"(?![(to get)\s])\w+$"
    }
    imageToShift = re.search(regexExpressions["imageToShift"], shiftingDescription).group()
    action = re.search(regexExpressions["action"], shiftingDescription).group()
    expectedResultingImage = re.search(regexExpressions["expectedResultingImage"], shiftingDescription).group()
    disparityMapToUse = re.search(regexExpressions["disparityMapToUse"], shiftingDescription).group()
    return [imageToShift, action, expectedResultingImage, disparityMapToUse]

if testMode :
    # test1
    shiftingDescription = "shift leftStereoImg to the right using leftDisparityMap to get rightStereoImg"
    [imageToShift, action, expectedResultingImage, disparityMapToUse] = parseInputToUnderstandShiftingLogic(shiftingDescription)
    description = "Using " + disparityMapToUse + " to shift " + imageToShift + " to the " + action + " to get " + expectedResultingImage
    assert description == "Using leftDisparityMap to shift leftStereoImg to the right to get rightStereoImg"
    shiftingDescription = "shift leftStereoImg to the right using leftDisparityMap to get rightStereoImg"
    # test2
    shiftingDescription = "shift rightStereoImg to the left using leftDisparityMap to get leftStereoImg"
    [imageToShift, action, expectedResultingImage, disparityMapToUse] = parseInputToUnderstandShiftingLogic(shiftingDescription)
    description = "Using " + disparityMapToUse + " to shift " + imageToShift + " to the " + action + " to get " + expectedResultingImage
    assert description == "Using leftDisparityMap to shift rightStereoImg to the left to get leftStereoImg"

def generateShiftedImage(shiftingDescription):
    [imageToShift, action, expectedResultingImage, disparityMapToUse] = parseInputToUnderstandShiftingLogic(shiftingDescription)
    description = "Using " + disparityMapToUse + " to shift " + imageToShift + " to the " + action + " to get " + expectedResultingImage
    print(description)

    disparityMap = cv2.imread(dataset[disparityMapToUse], cv2.IMREAD_GRAYSCALE)

    shiftedImage = np.zeros([rows, columns, channels])

    imageToShiftSource = leftStereoImg if imageToShift == "leftStereoImg" else rightStereoImg
    for row in range(rows):
        for column in range(columns):
            disparityMap_point = disparityMap[row, column]
            if disparityMap_point != 0 :
                # Since we want to shift to the right, we need to move the pixels in the negative axis
                t = column - disparityMap[row,column] if action == "right" else column + disparityMap[row,column]
                if(t>=0 and t<columns):
                    for ch in range(channels):
                        shiftedImage[row,column,ch] = imageToShiftSource[row,t,ch]


    cv2.imwrite(description + ".png", shiftedImage)

def main():
    shiftingDescriptions = [
        "shift leftStereoImg to the right using leftDisparityMap to get rightStereoImg",
        "shift leftStereoImg to the right using rightDisparityMap to get rightStereoImg",
        "shift leftStereoImg to the left using leftDisparityMap to get rightStereoImg",
        "shift leftStereoImg to the left using rightDisparityMap to get rightStereoImg",
        "shift rightStereoImg to the left using leftDisparityMap to get leftStereoImg",
        "shift rightStereoImg to the left using rightDisparityMap to get leftStereoImg",
        "shift rightStereoImg to the right using leftDisparityMap to get leftStereoImg",
        "shift rightStereoImg to the right using rightDisparityMap to get leftStereoImg"
    ]
    for shiftingDescription in shiftingDescriptions:
        generateShiftedImage(shiftingDescription)
        print("done with " + shiftingDescription)

if __name__ == "__main__":
    main()