imageutil.py

import numpy as np
from PIL import Image, ImageChops
import matplotlib.pyplot as plt
import cv2

def trim(im):
    bg = Image.new(im.mode, im.size, im.getpixel((0,0)))
    diff = ImageChops.difference(im, bg)
    diff = ImageChops.add(diff, diff, 2.0, -100)
    bbox = diff.getbbox()
    if bbox:
        return im.crop(bbox)

def readimageinput(img_path, preview=False, invert=False, size=None, as_Image=False):

    # read image as black and white
    img = cv2.imread(img_path, cv2.IMREAD_GRAYSCALE)

    # fall back option for Windows since
    # cv2 doesn't work with Unicode path
    if img is None:
        img = Image.open(img_path).convert('L')
        img = np.array(img)

    # binarisation
    ret, img = cv2.threshold(img, 0, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)


    # Change into PILLOW image to do trim and padding
    img = Image.fromarray(img)
    _img = trim(img)

    if _img is None:
        print(img_path + "is empty...")
    else:
        img = _img

    # get image size and find the longer dimension
    # we will pad in the other dimension to make 
    # a perfect square
    x,y = img.size
    max_size = max(x,y)

    # add padding border
    # max_size = int(max_size*1)

    # create a blank square image
    sqcanvas = Image.new('L', (max_size, max_size), (255))

    # since paste() use top left corner as an anchor point,
    # we want to calculate the position which will center
    # our image
    img_x = int((max_size - x)/2)
    img_y = int((max_size - y)/2)
    sqcanvas.paste(img, (img_x, img_y))
    
    img = sqcanvas


    img = np.array(img)

    # mnist dataset is white on black, this option invert the input
    # if needed to match our trained set
    if invert:
        img = 1 - img/255

    # resize image if size is specified
    if size is not None:
        img = cv2.resize(img, size)

    kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (2, 2))
    img = cv2.morphologyEx(img, cv2.MORPH_OPEN, kernel)

    # if preview, the program will be block until the
    # plot window is closed
    if preview:
        plt.imshow(img, cmap=plt.get_cmap('gray'))

    if as_Image:
        return Image.fromarray(img)

    img_width = img.shape[0]
    img_height = img.shape[1]

    # reshape the numpy array to the same format as our model
    img = img.reshape(1, 1, img_width, img_height).astype('float32')


    return img
    
if __name__ == '__main__':
    readimageinput('th_samples/ค/3-164-A4-KHO KHWAI-43.png', True, False, (128,128))
    plt.show()