def getPep():
regex = {
"capital_letters": re.compile("[A-Z]")
}
clean = []
cont = 0
path_file = "./virus_genome/peptite/antiviral.fasta"
pathSave = "path-to/pepdata"
with open(path_file, 'r') as f:
lines = f.readlines()
for l in lines:
clean.append(l.replace("\n", ""))
for pep in clean:
# string preprocessing
if ">" in pep:
continue
if "-" in pep:
continue
if "(" in pep:
continue
if regex["capital_letters"].match(pep):
print("..." + pep)
text_to_image.encode(pep,os.path.join(pathSave,pep+".png"))
img = cv2.imread(os.path.join(pathSave,pep+".png"))
img = cv2.resize(img,(256,256))
cv2.imwrite(os.path.join(pathSave,pep+".png"), img)
def getData(nstrandsList,pathSave):
cont = 0
for s in tqdm(nstrandsList):
text_to_image.encode(s,os.path.join(pathSave,"strands_"+str(cont)+".png"))
img = cv2.imread(os.path.join(pathSave,"strands_"+str(cont)+".png"))
img = cv2.resize(img,(256,256))
cv2.imwrite(os.path.join(pathSave,"strands_"+str(cont)+".png"), img)
cont += 1
def main():
os.makedirs("multi-label-png")
os.makedirs("multi-label")
df = pd.read_csv("test-cc")
for index, row in df.iterrows():
text_to_image.encode(row["sequences"],
"multi-label-png/" + row["proteins"])
image = cv2.imread("multi-label-png/" + row["proteins"] + ".png", 0)
resizedImage = cv2.resize(image, (299, 299))
cv2.imwrite("multi-label/" + row["proteins"] + ".jpg", resizedImage)
def encrypt(request):
if request.method == 'POST':
input_value = request.POST['iptextarea']
input_value = str(input_value)
inp_conversion = Fernet(settings.ENCRYPT_KEY)
encrypt_text = inp_conversion.encrypt(input_value.encode('ascii'))
encrypted_text = base64.urlsafe_b64encode(encrypt_text).decode('ascii')
encrypted_image = text_to_image.encode(
encrypted_text, 'image.png') #converting encrypted data into image
encrypted_image = Image.open(encrypted_image) #converted
#encrypted_image = encrypted_image.resize((300,300))
image_path = 'C:/Users/Ganesh vamsi/MY PROJECTS/image-encrypt-decrypt/image_en_de/static/temp_img/image.png'
encrypted_image.save(image_path, 'PNG') #saving the image temporarly
'''
image = PIL.Image.open(image_path)
w,h=image.size
print('44444444444555555',w,h)
image.close()
'''
with open(image_path, 'rb') as image_file:
image_data = base64.b64encode(image_file.read()).decode('utf-8')
ctx = dict()
ctx['encrypted_image'] = image_data
os.remove(image_path, dir_fd=None)
sentence = 'Download the below encrypted image'
ctx['sentence'] = sentence
ctx['enalbe_disable'] = 'enabled' #output and download btn visibility
return render(request, 'encrypt.html', ctx)
return render(request, 'encrypt.html', {'enalbe_disable': 'disabled'})
def text_to_Image():
global encoded_image_path
global inputt
inputt=input("Enter text: ")
encoded_image_path = text_to_image.encode(inputt, "test")
print('This is a test print', encoded_image_path, inputt)
print('file is opend!!!!!!!!!!')
encoded_image_path = text_to_image.encode_file("../test/test.txt", "result.png")
return text_to_Image
def write_image_from_hex(hex_content, out_path): # out path including .png
text_to_image.encode(hex_content, 'images/' + out_path)
train, test = 100000, 100000
for i in range(2, 99999):
if (w_sheet.Cells(i, 1).Value == None):
break
if (w_sheet.Cells(i, 3).Value == None):
w_sheet.Cells(i, 3).Value = '0 미정' #라벨빈칸 '0 미정'으로 바꿈
st1 = w_sheet.Cells(i, 1).Value # 회사명 받기
st2 = w_sheet.Cells(i, 2).Value # 가게명 받기
st1 = str(st1)
st2 = str(st2) #스트링 형식으로
de = w_sheet.Cells(i, 3).Value # 라벨 받아오기
encoded_image_path = text_to_image.encode(
st1 + st2,
"C:\\Users\\aiia\\.atom\\python\\text_to_image_2\\test\\a_%d_%d.png" %
(test, de)) #이미지로 인코딩
img = Image.open(
"C:\\Users\\aiia\\.atom\\python\\text_to_image_2\\test\\a_%d_%d.png" %
(test, de)) # 이미지 사이즈 조절을 위해 이미지 다시 받아오기
re_img = img.resize((28, 28)) # 이미지 크기 설정
re_img.save(
"C:\\Users\\aiia\\.atom\\python\\text_to_image_2\\test\\a_%d_%d.png" %
(test, de)) # 변경된 이미지 다시 저장
test = test + 1
excel_file.Save()
excel.Quit()
def pre_img(self):
if os.path.exists(self.img_PATH):
for file in os.scandir(self.img_PATH):
os.remove(file.path)
WIDTH, HEIGHT = 28, 28
train, test = 100000, 100000
###### 등록번호 '-' 기호 지우기 ####
'''
if self.T == '영수증':
buyer = '회사등록번호'
else:
buyer = '사업자등록번호'
'''
buyer = 'NO_BIZ'
seller = 'NO_BIZ_C'
try:
buyer_raw_data = self.df[buyer].str.split('-', n=2, expand=True)
buyer_raw_data[buyer] = buyer_raw_data[0].str.cat(buyer_raw_data[1])
buyer_raw_data[buyer] = buyer_raw_data[buyer].str.cat(buyer_raw_data[2]).copy()
del (buyer_raw_data[0])
del (buyer_raw_data[1])
del (buyer_raw_data[2])
buyer_raw_data = buyer_raw_data.astype('str')
del (self.df[buyer])
self.df[buyer] = buyer_raw_data[buyer].astype('str')
except AttributeError:
print('-부호 없음')
try:
buyer_raw_data2 = self.df[seller].str.split('-', n=2, expand=True)
print('buyer_raw_data2', buyer_raw_data2)
buyer_raw_data2[seller] = buyer_raw_data2[0].str.cat(buyer_raw_data2[1])
buyer_raw_data2[seller] = buyer_raw_data2[seller].str.cat(buyer_raw_data2[2]).copy()
del (buyer_raw_data2[0])
del (buyer_raw_data2[1])
del (buyer_raw_data2[2])
buyer_raw_data2 = buyer_raw_data2.astype('str')
del (self.df['NO_BIZ_C'])
self.df['NO_BIZ_C'] = buyer_raw_data2['NO_BIZ_C'].astype('str')
###################################
except AttributeError:
print('-부호 없음')
# print(ind[0])
name = buyer
# xl = excel_PATH2 + 'total_17_18_new.xlsx'
name2 = 'NO_BIZ_C'
target = 'CD_ACCOUNT'
if self.T == '계산서' :
e_name = 'e_bill_2019_uniq.json'
elif self.T == '영수증':
e_name = 'cash_train.json'
elif self.T == '기타' :
e_name = 'etc.json'
df = comp(self.comend,self.excel_PATH, self.T, self.df, target, e_name, name, name2)
# df = comp(df,target, 'e_bill_2019_uniq.xlsx',name)
# print(len(data))
# print(df)
print(df.head())
if self.T == '영수증' or self.T == '기타':
pre_data = df.loc[:, [name,name2]].astype('str')
pre_data[name] = pre_data[name].str.replace(' ','')
pre_data[name2] = pre_data[name2].str.replace(' ','')
if self.comend == 'train':
pre_data[target] = df[target].astype('str')
else :
name = 'NM_ITEM'
pre_data = df.loc[:, [name]].astype('str')
pre_data[name] = pre_data[name].str.replace(' ', '')
if self.comend == 'train':
pre_data[target] = df[target].astype('str')
#print(pre_data.head())
if os.path.exists(self.img_PATH):
print("already eixts path")
else :
os.mkdir(self.img_PATH)
print("create path")
for i in range(len(pre_data)):
img_num = train + i
obj = pre_data.loc[i, [name]].item()
# obj += pre_data.loc[i,[name2]].item() ##name2도 이미지화 하는데 같이 고려해야 한다면
if self.comend == 'train':
c_num = pre_data.loc[i, [target]].str.split(' ', n=2, expand=True)
text2img.encode(obj, self.img_PATH + 'a_%d_%d.png' % (img_num, c_num[0]))
img = Image.open(self.img_PATH + 'a_%d_%d.png' % (img_num, c_num[0]))
resize_img = img.resize((WIDTH, HEIGHT))
resize_img.save(self.img_PATH + 'a_%d_%d.png' % (img_num, c_num[0]))
print('이미지화 : %d / %d' % (i, len(pre_data)))
else :
#c_num = pre_data.loc[i, [target]].str.split(' ', n=2, expand=True)
text2img.encode(obj, self.img_PATH + 'a_%d.png' % (img_num))
img = Image.open(self.img_PATH + 'a_%d.png' % (img_num))
resize_img = img.resize((WIDTH, HEIGHT))
resize_img.save(self.img_PATH + 'a_%d.png' % (img_num))
print('이미지화 : %d / %d' % (i, len(pre_data)))
list_notes = []
for note in notes:
note_td = note.find_all('td', valign="top")
str_note_td = str(note_td)
clean3 = re.compile('<.*?>')
clean4 = (re.sub(clean, '', str_note_td))
list_notes.append(clean4)
#pd.set_option('display.max_colwidth', 60)
df = pd.DataFrame(list_notes)
table = str.maketrans('', '', string.punctuation)
table = str.maketrans('', '', "xa0\xa0\r\n\t\t\t\t\t'")
stripped = [w.translate(table) for w in df[0]]
p = df[df[0].str.contains("2013") == True]
p = p[p[0].str.contains("B.Tech") == True]
np = p.values
dicter = p.to_string()
encoded_image_path = text_to_image.encode(dicter, "image1.png")
text, chat = get_last_chat_id_and_text(get_updates())
send_image('/home/sj/Documents/products/noteifi/test.png', chat)
send_message(
'Displaying Last {} notifications containing 2013 and B.Tech as tags'.
format(len(np)), chat)
for i in range(len(np)):
send_message(np[i], chat)
print(np[i])
time.sleep(43200)
# generate random string of 5 characters
import string
import random
import text_to_image
def id_generator(size=6, chars=string.ascii_lowercase + string.digits):
return ''.join(random.choice(chars) for _ in range(size))
# for x in range(100):
# S = id_generator(5)
# print(str(x) + '. ' + S)
S = id_generator(5)
print(S)
encoded_image_path = text_to_image.encode(S, "image.png")
print(encoded_image_path)