ascify.py

import cv2
import numpy as np
from PIL import Image, ImageDraw, ImageOps, ImageFont
import os

Characters = {
    "standard"  : "@%#*+=-:. ",
    "complex"   : "$@B%8&WM#*oahkbdpqwmZO0QLCJUYXzcvunxrjft/\|()1{}[]?-_+~<>i!lI;:,\"^`'. "
}

def get_data(mode):
    font_filename = "DejaVuSansMono"
    font = ImageFont.truetype(os.path.dirname(__file__) + "/fonts/" + font_filename + ".ttf", size=20)
    char_list = Characters[mode]
    return char_list, font

def convert(img_loc):

    (char_list, font) = get_data("complex")
    num_chars = len(char_list)
    num_cols = 300
    scale = 2
    
    image = cv2.imread(img_loc)
    image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)

    height, width, garbage = image.shape

    cell_w = width/num_cols
    cell_h = scale*cell_w
    num_rows = int(height/cell_h)

    char_width, char_height = font.getsize("A")
    out_width = char_width*num_cols
    out_height = char_height*num_rows

    out_img = Image.new("RGB", (out_width, out_height), (255,255,255))
    draw = ImageDraw.Draw(out_img)


    for i in range(int(num_rows)):
        for j in range(int(num_cols)):

            partial_image = image[  int(i*cell_h)   :   min(int((i+1)*cell_h), height),
                                    int(j*cell_w)   :   min(int((j+1)*cell_w), width),
                                                    :                                   ]

            partial_avg_color = np.sum(np.sum(partial_image, axis=0), axis=0)/(cell_h*cell_w)
            partial_avg_color = tuple(partial_avg_color.astype(np.int32).tolist())

            c = char_list[min(int((int(np.mean(partial_image))*num_chars)/255), num_chars-1)]
            
            draw.text((j*char_width, i*char_height), c, fill = partial_avg_color, font = font)


    cropped_img = out_img.getbbox()
    f_img = out_img.crop(cropped_img)

    return f_img