converter.py

import cv2  
from PIL import Image, ImageFilter


def imageprepare(argv):
    """
    This function returns the pixel values.
    The imput is a png file location.
    """
    im = Image.open(argv).convert('L')
    width = float(im.size[0])
    height = float(im.size[1])
    newImage = Image.new('L', (28, 28), (255))  # creates white canvas of 28x28 pixels

    if width > height:  # check which dimension is bigger
        # Width is bigger. Width becomes 20 pixels
        kwidth = 20
        nheight = int(round((float(kwidth) / width * height), 0))  # resize height according to ratio width
        if (nheight == 0):  # rare case but minimum is 1 pixel
            nheight = 1
            # resize and sharpen
        img = im.resize((kwidth, nheight), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)
        wleft = int(round(((28 - kwidth) / 2), 0))
        wtop = int(round(((28 - nheight) / 2), 0))  # calculate horizontal position
        newImage.paste(img, (6, wtop))  # paste resized image on white canvas
    else:
        # Height is bigger. Heigth becomes 20 pixels.
        kheight = 20
        nwidth = int(round((float(kheight) / height * width), 0))  # resize width according to ratio height
        if (nwidth == 0):  # rare case but minimum is 1 pixel
            nwidth = 1
            # resize and sharpen
        img = im.resize((nwidth, kheight), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)
        wtop = int(round(((28 - kheight) / 2), 0))
        wleft = int(round(((28 - nwidth) / 2), 0))  # caculate vertical pozition
        newImage.paste(img, (wleft, wtop))  # paste resized image on white canvas

    # newImage.save("sample.png

    tv = list(newImage.getdata())  # get pixel values

    # normalize pixels to 0 and 1. 0 is pure white, 1 is pure black.
    tva = [(255 - x) for x in tv]
    return tva

#x=imageprepare('./pic94.png')#file path here
#print(len(x))# mnist IMAGES are 28x28=784 pixels