File size: 5,043 Bytes
21ac65e
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
'''
Refer to https://huggingface.co/spaces/dt/ascii-art/blob/main/app.py
'''

# Python code to convert an image to ASCII image.
import sys, random, argparse
import numpy as np
import math
import base64
from PIL import Image, ImageFont, ImageDraw
from moviepy.editor import *
from tqdm.auto import tqdm

import gradio as gr

# 70 levels of gray
gscale1 = "$@B%8&WM#*oahkbdpqwmZO0QLCJUYXzcvunxrjft/\|()1{}[]?-_+~<>i!lI;:,\"^`'. "
 
# 10 levels of gray
gscale2 = '@%#*+=-:. '

font = ImageFont.load_default()
 
def getAverageL(image):
 
    """
    Given PIL Image, return average value of grayscale value
    """
    # get image as numpy array
    im = np.array(image)
    # get shape
    w,h = im.shape
 
    # get average
    return np.average(im.reshape(w*h))
 
def covertImageToAscii(input_img, cols, scale, moreLevels):
    """
    Given Image and dims (rows, cols) returns an m*n list of Images
    """
    # declare globals
    global gscale1, gscale2
 
    # open image and convert to grayscale
    image = input_img.convert('L')
 
    # store dimensions
    # store dimensions
    W, H = image.size[0], image.size[1]
 
    # compute width of tile
    w = W/cols
 
    # compute tile height based on aspect ratio and scale
    h = w/scale
 
    # compute number of rows
    rows = int(H/h)
 
    # check if image size is too small
    if cols > W or rows > H:
        print("Image too small for specified cols!")
        exit(0)
 
    # ascii image is a list of character strings
    aimg = []
    # generate list of dimensions
    for j in range(rows):
        y1 = int(j*h)
        y2 = int((j+1)*h)
 
        # correct last tile
        if j == rows-1:
            y2 = H
 
        # append an empty string
        aimg.append("")
 
        for i in range(cols):
 
            # crop image to tile
            x1 = int(i*w)
            x2 = int((i+1)*w)
 
            # correct last tile
            if i == cols-1:
                x2 = W
 
            # crop image to extract tile
            img = image.crop((x1, y1, x2, y2))
 
            # get average luminance
            avg = int(getAverageL(img))
 
            # look up ascii char
            if moreLevels:
                gsval = gscale1[int((avg*69)/255)]
            else:
                gsval = gscale2[int((avg*9)/255)]
 
            # append ascii char to string
            aimg[j] += gsval
     
    # return txt image
    return aimg


def colorizeTextImage(input_img, text_img):
    input_img = np.asarray(input_img)
    input_img = input_img.reshape((
        input_img.shape[0]//11, 
        11, 
        input_img.shape[1]//6, 
        6,
        3
    ))
    input_img = np.float32(input_img)
    text_img = np.asarray(text_img)
    text_img = text_img.reshape((
        input_img.shape[0], 
        11, 
        input_img.shape[2], 
        6, 
        3
    ))
    alpha = np.float32(text_img)[...,:1] / 255
    alpha[alpha < 0.125] = 0
    alpha[alpha >= 0.125] = 1
    out_img = input_img * alpha
    out_colors = out_img.sum((1,3), keepdims=True) / (alpha.sum((1,3), keepdims=True) + 1e-12)
    out_img = out_colors * alpha
    out_img = out_img.reshape((
        out_img.shape[0] * out_img.shape[1],
        out_img.shape[2] * out_img.shape[3],
        3
    ))
    out_img = np.clip(out_img, 0, 255)
    out_img = np.uint8(out_img)

    return out_img
 

def sepia(input_img, no_colors=False):
    input_img = Image.fromarray(input_img).convert('RGB')
    aimg = covertImageToAscii(input_img, 200, 6/11, True)
    blank_image = Image.new(mode="RGB", size=(len(aimg[0])*6, len(aimg)*11), color=(0, 0, 0))

    my_image = blank_image.copy()
    image_editable = ImageDraw.Draw(my_image)
    
    image_editable.text((0, 0), "\n".join(aimg), (255, 255, 255), font=font, spacing=0)
    if no_colors:
        return np.asarray(my_image)

    input_img_resize = input_img.resize((len(aimg[0])*6, len(aimg)*11), Image.BICUBIC)
    w, h = input_img.size
    scale = 200 * 6 / w
    w = 200 * 6
    h = int(round(h*scale))
    input_img = input_img.resize((200 * 6, h), Image.BICUBIC)
    input_img_resize.paste(input_img, (0, 0, w, h))
    input_img = input_img_resize

    my_image = colorizeTextImage(input_img, my_image)

    return my_image


def sepia_video(video_file, no_colors=False):
    clip = VideoFileClip(video_file)
    audioclip = clip.audio
    frames = int(clip.fps * clip.duration)
    imgs = []
    for i in tqdm(range(frames)):
        imgs.append(sepia(clip.get_frame(i/clip.fps), no_colors))
    video = ImageSequenceClip(imgs, fps=clip.fps)
    video = video.set_audio(audioclip)
    video.write_videofile("out.mp4", fps=clip.fps)

    return "out.mp4"

iface = gr.Interface(sepia_video, 
                     [gr.Video(format=None), gr.Checkbox(label="No Colors")], 
                     "video",
                     title = "Colorful ASCII Art",
                     description = "Convert an image to colorful ASCII art based on ascii character density. Click the first output text to download the generated svg.")

iface.launch()