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Runtime error
File size: 4,019 Bytes
88a5625 e94f1a7 88a5625 34f51ac 88a5625 34f51ac 88a5625 34f51ac 31a647f 6d7c2da ebfe974 af92acc 34f51ac 88a5625 34f51ac 88a5625 34f51ac e3abdb0 34f51ac 29eca9d 34f51ac 22cfa8c f5f2a03 34f51ac 88a5625 34f51ac e107937 22cfa8c 34f51ac 88a5625 53284c0 12cf47c 34f51ac | 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 | import base64
import gradio as gr
import cv2
import numpy as np
import pandas as pd
from PIL import Image
import hashlib
import os
import uuid as uniq
from qr import make_qr
import math
def to_bin(data):
"""Convert `data` to binary format as string"""
if isinstance(data, str):
return ''.join([ format(ord(i), "08b") for i in data ])
elif isinstance(data, bytes):
return ''.join([ format(i, "08b") for i in data ])
elif isinstance(data, np.ndarray):
return [ format(i, "08b") for i in data ]
elif isinstance(data, int) or isinstance(data, np.uint8):
return format(data, "08b")
else:
raise TypeError("Type not supported.")
def decode(image_name,txt=None):
BGRimage = cv2.imread(image_name)
image = cv2.cvtColor(BGRimage, cv2.COLOR_BGR2RGB)
#resultd = hashlib.sha256(txt.encode('utf-8')).hexdigest()
binary_data = ""
for row in image:
for pixel in row:
r, g, b = to_bin(pixel)
binary_data += r[-1]
binary_data += g[-1]
binary_data += b[-1]
all_bytes = [ binary_data[i: i+8] for i in range(0, len(binary_data), 8) ]
decoded_data = ""
for byte in all_bytes:
decoded_data += chr(int(byte, 2))
if decoded_data[-5:] == "=====":
break
p = decoded_data[:-5].split("#",1)[1].split("#",1)[0]
#if p == resultd:
this = decoded_data[:-5].split("#",1)[0].split("'",1)[1]
#base = bytes(this, 'utf-8')
#with open(f"finished_im{uniqnum}.png", "wb") as fh:
# fh.write(base64.decodebytes(bytes(this, 'utf-8')))
#fh.close
#return f"finished_im{uniqnum}.png"
return this
def encode(image_name, secret_data,txt=None):
BGRimage = cv2.imread(image_name)
image = cv2.cvtColor(BGRimage, cv2.COLOR_BGR2RGB)
n_bytes = image.shape[0] * image.shape[1] * 3 // 8
print("[*] Maximum bytes to encode:", n_bytes)
#resultp = hashlib.sha256(txt.encode('utf-8')).hexdigest()
secret_data1=secret_data
#secret_data1=f'{secret_data}#{resultp}'
while True:
if len(secret_data1) < (n_bytes):
secret_data1 = f'{secret_data1}#'
elif len(secret_data1) >= (n_bytes):
break
secret_data = secret_data1
if len(secret_data) > n_bytes:
return image_name, gr.Markdown.update("""<center><h3>Input image is too large""")
secret_data += "====="
data_index = 0
binary_secret_data = to_bin(secret_data)
data_len = len(binary_secret_data)
for row in image:
for pixel in row:
r, g, b = to_bin(pixel)
if data_index < data_len:
pixel[0] = int(r[:-1] + binary_secret_data[data_index], 2)
data_index += 1
if data_index < data_len:
pixel[1] = int(g[:-1] + binary_secret_data[data_index], 2)
data_index += 1
if data_index < data_len:
pixel[2] = int(b[:-1] + binary_secret_data[data_index], 2)
data_index += 1
if data_index >= data_len:
break
return image
def conv_im(qr_link,data):
uniqnum = uniq.uuid4()
byte_size = len(data)
print (f'bytes:{byte_size}')
data_pixels = byte_size*4
print (f'pixels:{data_pixels}')
#data_sq=data_pixels/2
data_sq = int(math.sqrt(data_pixels))
data_pad = data_sq+100
print (f'square image:{data_pad}x{data_pad}')
qr_im = make_qr(txt=qr_link)
img1 = Image.open(qr_im)
imgw = img1.size[0]
imgh = img1.size[1]
print (f'qr Size:{img1.size}')
#img1.thumbnail((imgw*4,imgh*4), Image.Resampling.LANCZOS)
img1 = img1.resize((int(data_pad),int(data_pad)), Image.Resampling.LANCZOS)
print (img1.size)
img1.save(f'tmpim{uniqnum}.png')
with open(f'tmpim{uniqnum}.png', "rb") as image_file:
encoded_string = base64.b64encode(image_file.read())
image_file.close()
im_out = encode(f'tmpim{uniqnum}.png',data)
return im_out
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