|
1
|
|
|
#!/usr/bin/python |
|
2
|
|
|
# -*- coding: utf-8 -*- |
|
3
|
|
|
from modules.utils import caption_filter, get_image, send_image, get_param |
|
4
|
|
|
from telegram.ext import CommandHandler, MessageHandler |
|
5
|
|
|
from telegram.ext.dispatcher import run_async |
|
6
|
|
|
from sklearn.cluster import KMeans |
|
7
|
|
|
from telegram import ChatAction |
|
8
|
|
|
from PIL import Image |
|
9
|
|
|
import numpy as np |
|
10
|
|
|
import datetime |
|
11
|
|
|
import cv2 |
|
12
|
|
|
|
|
13
|
|
|
|
|
14
|
|
|
def module_init(gd): |
|
15
|
|
|
global path |
|
16
|
|
|
path = gd.config["path"] |
|
17
|
|
|
commands = gd.config["commands"] |
|
18
|
|
|
extensions = gd.config["extensions"] |
|
|
|
|
|
|
19
|
|
|
for command in commands: |
|
20
|
|
|
gd.dp.add_handler(MessageHandler(caption_filter("/"+command), palette)) |
|
21
|
|
|
gd.dp.add_handler(CommandHandler(command, palette)) |
|
22
|
|
|
|
|
23
|
|
|
|
|
24
|
|
|
@run_async |
|
25
|
|
|
def palette(bot, update): |
|
26
|
|
|
filename = datetime.datetime.now().strftime("%d%m%y-%H%M%S%f") |
|
27
|
|
|
name = filename + "-palette" |
|
28
|
|
|
colors = get_param(update, 4, 1, 10) |
|
29
|
|
|
if colors is None: |
|
30
|
|
|
return |
|
31
|
|
|
try: |
|
32
|
|
|
extension = get_image(bot, update, path, filename) |
|
33
|
|
|
except: |
|
34
|
|
|
update.message.reply_text("I can't get the image! :(") |
|
35
|
|
|
return |
|
36
|
|
|
update.message.chat.send_action(ChatAction.UPLOAD_PHOTO) |
|
37
|
|
|
start_computing(path, filename, extension, colors, "flat") |
|
38
|
|
|
send_image(update, path, name, extension) |
|
39
|
|
|
print(datetime.datetime.now(), ">>>", "palette", ">>>", update.message.from_user.username) |
|
40
|
|
|
|
|
41
|
|
|
|
|
42
|
|
|
def start_computing(path, filename, extension, colors, mode): |
|
43
|
|
|
open_path = path + filename + extension |
|
44
|
|
|
number_of_colors = colors |
|
45
|
|
|
name = filename + "-palette" |
|
46
|
|
|
save_path = path + name + extension |
|
47
|
|
|
# Load image here |
|
48
|
|
|
pil_image = Image.open(open_path).convert('RGB') |
|
49
|
|
|
original_image = np.float32(pil_image) |
|
50
|
|
|
original_image = cv2.cvtColor(original_image, cv2.COLOR_BGR2RGB) |
|
51
|
|
|
width, height = pil_image.size |
|
52
|
|
|
pil_image.thumbnail((400, 400), Image.ANTIALIAS) |
|
53
|
|
|
cv_image = np.float32(pil_image) |
|
54
|
|
|
# Reshape the image to be a list of pixels |
|
55
|
|
|
cv_image = cv_image.reshape((cv_image.shape[0] * cv_image.shape[1], 3)) |
|
56
|
|
|
# Cluster the pixel intensities |
|
57
|
|
|
clt = KMeans(n_clusters = number_of_colors, tol=0.001).fit(cv_image) |
|
58
|
|
|
# Build a histogram of clusters representing the number of pixels labeled to each color |
|
59
|
|
|
hist = centroid_histogram(clt) |
|
60
|
|
|
bar = plot_colors(hist, clt.cluster_centers_, width, height, number_of_colors, mode) |
|
61
|
|
|
bar = cv2.cvtColor(bar, cv2.COLOR_BGR2RGB) |
|
62
|
|
|
# Separating line for image + palette stacking |
|
63
|
|
|
separator = np.zeros((15, width, 3), dtype = "uint8") |
|
64
|
|
|
separator = cv2.rectangle(separator, (0, 0), (width, 15), (30,30,30), -1) |
|
65
|
|
|
# Cobmine original image, separator and color chart |
|
66
|
|
|
stacked = np.concatenate((original_image, separator, bar), axis=0) |
|
67
|
|
|
stacked = cv2.cvtColor(stacked, cv2.COLOR_BGR2RGB) |
|
68
|
|
|
stacked = Image.fromarray(stacked.astype('uint8')) |
|
69
|
|
|
stacked.save(save_path) |
|
70
|
|
|
|
|
71
|
|
|
|
|
72
|
|
|
def centroid_histogram(clt): |
|
73
|
|
|
numLabels = np.arange(0, len(np.unique(clt.labels_)) + 1) |
|
74
|
|
|
(hist, _) = np.histogram(clt.labels_, bins = numLabels) |
|
75
|
|
|
hist = hist.astype("float") |
|
76
|
|
|
hist /= hist.sum() |
|
77
|
|
|
return hist |
|
78
|
|
|
|
|
79
|
|
|
|
|
80
|
|
|
def plot_colors(hist, centroids, width, height, number_of_colors, mode): |
|
81
|
|
|
bar_height = int(height*0.2) |
|
82
|
|
|
bar = np.zeros((bar_height, width, 3), dtype = "uint8") |
|
83
|
|
|
startX = 0 |
|
84
|
|
|
for (percent, color) in zip(hist, centroids): |
|
85
|
|
|
if mode == "flat": |
|
86
|
|
|
endX = startX + (width/number_of_colors) |
|
87
|
|
|
elif mode == "percentage": |
|
88
|
|
|
endX = startX + (percent * width) |
|
89
|
|
|
cv2.rectangle(bar, (int(startX), 0), (int(endX), bar_height), color.astype("uint8").tolist(), -1) |
|
90
|
|
|
startX = endX |
|
91
|
|
|
return bar |
MadiNyan /
rikka-telegram-bot
Loading history...