s0urceBOT/imgGrey.py

#!/usr/bin/env python3

from PIL import Image

import sys, os, json, argparse

class imgGrey():
    """
    Uses Grey scaling to tell what is black and white or grey in an image
    """

    def __init__(self, on='X', off=' ', intensity=64):
        """
        Here is where you set stuff like ON, OFF and INTENSITY
        """
        self.ON = on
        self.OFF = off
        self.INTENSITY = intensity

    def img_point(self, pix, x, y):
        """
        img_point, returns a pixel of an image,
        given the x and y on the image.
        """
        return pix[x, y]

    def img_avg(self, pix, x, y):
        """
        img_avg, returns the average brightness 0-255,
        given pixel, and the x and y on the image calls img_point,
        to get the individual rgb values to calculate,
        brightness. (Grey scale)
        """
        rgb = self.img_point(pix, x,y)
        #if(im.mode == 'P'):
        #    rgb = pal[rgb*3:(rgb+1)*3]

        #if(im.mode == 'I'):
        #    return rgb >> 8

        return int( ( rgb[0] + rgb[1] + rgb[2] ) / 3 )

    def is_set(self, pix, x, y):
        """
        is_set, returns True or False of calculating,
        the brightness of the given point on a image,
        compared to given intensity.
        
        True means the brightness at the given x and y,
        is Less Than which means its dark.
        
        False means the brightness at the given x and y,
        is Greater Than which means its bright. (Grey Scale)
        """
        avg = self.img_avg(pix, x,y)
        return (avg < self.INTENSITY)

    def scan_img(self, pix, size):
        """
        scan_img, looks at a image and looks for dark pixels,
        if it is a dark pixel record the number and resize the,
        returned values to show where the most dark pixels on the,
        image are located. (Grey Scale)
        
        given pixel, and image size.
        returns start x, y and end x, y and total number of dark pixels.
        """
        total = 0
        sx = size[0]; ex = 0
        sy = size[1]; ey = 0

        for y in range( 0,size[1] ):
            for x in range( 0,size[0] ):
                pnt_is = self.is_set(pix, x,y)
                if (pnt_is):
                    total += 1
                    if x < sx:
                        sx = x
                    if x > ex:
                        ex = x
                    if y < sy:
                        sy = y
                    if y > ey:
                        ey = y

        #print (sx,ex,sy,ey)
        # give us a little border to work with
        if sx > 0:
            sx -= 1
        if ex < size[0]:
            ex += 1

        if sy > 0:
            sy -= 1
        if ey < size[1]:
            ey += 1

        #print (sx,ex,sy,ey)
        return(sx,sy,ex,ey,total)

    def output_image(self, pix, size):
        """
        For the size of the area we have reduced down to where the majority of dark pixels,
        are located, store all that into a list and return the list.
        
        given pixel for function passing.
        returns multiple strings in a list that are edited to use characters to represent,
        the dark and light pixels of the image. (Grey Scale)
        """
        result = []
        ex = size[0]; sx = 0
        ey = size[1]; sy = 0
        for y in range(sy,ey):
            s = ''
            for x in range(sx,ex):
                if self.is_set(pix, x,y):
                    s += self.ON
                else:
                    s += self.OFF
            result.append(s)

        return result

    def run(self, fname):
        """
        run, represents a single execution of components to the image,
        those components do the following...

        We open and load the image, and get it's size,
        then we scan_img for dark and light pixels, <-- This narrows the image down to just the majority of dark pixels
        then from that we output the image line by line onto the screen after it has been output_image d into list form,
        Where we ask the user what the word is, and after that we save all that to a file in the data directory.
        """
        
        if not os.path.exists(fname):
            raise FileNotFoundError("Could not find '{0}'".format(fname))

        print(f"Loading: {fname}")
        im = Image.open(fname)
        pix = im.load()
        size = im.size
        pal = im.getpalette()
        print(f"Size: {size[0]} x {size[1]}")

        sx = 0; ex = size[0]
        sy = 0; ey = size[1]
        total = 0

        sx, sy, ex, ey, total = self.scan_img(pix, size)
        print(f"Chars within ({sx}, {sy}) - ({ex}, {ey}) total {total} pixels")

        img_s = self.output_image(pix, size)
        for l in img_s:
            print(l)

        word = input('Word: ')
        return word

if __name__ == '__main__':
    imgTest = imgGrey()
    imgTest.run('test.png')