def main(photo_file):
"""Run a text detection request on a single image"""
access_token = os.environ.get('VISION_API')
service = Service('vision', 'v1', access_token=access_token)
with open(photo_file, 'rb') as image:
base64_image = encode_image(image)
body = {
'requests': [{
'image': {
'content': base64_image,
},
'features': [{
'type': 'TEXT_DETECTION',
'maxResults': 1,
}]
}]
}
response = service.execute(body=body)
text = response['responses'][0]['textAnnotations'][0]['description']
#print('Found text: {}'.format(text))
print('Found text:')
a = text.split("\n")
b = re.sub(' +|\-|\.', '', a[len(a) - 2])
#c = re.sub('-', '', b)
print b
def main(photo_file):
"""Run a text detection request on a single image"""
access_token = os.environ.get('VISION_API')
print(access_token)
if access_token == 'None':
print("Import VISION API KEY")
service = Service('vision', 'v1', access_token=access_token)
with open(photo_file, 'rb') as image:
base64_image = encode_image(image)
body = {
'requests': [{
'image': {
'content': base64_image,
},
'features': [{
'type': 'TEXT_DETECTION',
'maxResults': 1,
}]
}]
}
response = service.execute(body=body)
print(response)
if response['responses'][0]:
text = response['responses'][0]['textAnnotations'][0]['description']
print('Found text: {}'.format(text))
else:
text = " "
file1=open("./text/pdf_to_text.txt","a")
#file1.write(text,'\n')
file1.write("{}\n".format(text))
file1.close()
print("Text File modified")
def predict():
data = {'success': False}
if request.files.getlist("images[]"):
images = request.files.getlist("images[]")
images_preprocess = []
items = []
for image in images:
item = {}
image = image.read()
image = Image.open(io.BytesIO(image))
image = utils.preprocess_image(image)
images_preprocess.append(image / 255.)
item['image'] = utils.encode_image(image)
items.append(item)
images_preprocess = np.array(images_preprocess)
predicts = model.predict(images_preprocess, steps=len(images))
predicts = np.argmax(predicts, axis=1)
for idx, predict in enumerate(predicts):
items[idx]['info'] = class_info[str(predict)]
data['success'] = True
data['data'] = items
print(data)
return json.dumps(data, ensure_ascii=False, cls=utils.NumpyEncoder)
def main(photo_file):
"""Run a text detection request on a single image"""
print "Into Main Function"
access_token = os.environ.get('VISION_API')
print access_token
service = Service('vision', 'v1', access_token=access_token)
with open(photo_file, 'rb') as image:
print "into with section"
base64_image = encode_image(image)
body = {
'requests': [{
'image': {
'content': base64_image,
},
'features': [{
'type': 'TEXT_DETECTION',
'maxResults': 1,
}]
}]
}
print "out"
response = service.execute(body=body)
print "After response"
text = response['responses'][0]['textAnnotations'][0]['description']
print "after text"
print('Found text: {}'.format(text))
def TextViz_Options(options=None):
"""
Generate the layout of the dashboard.
Optional Args:
options (list(dict)): Not relevant; here only for API compatibility.
Returns:
A Dash element or list of elements.
"""
return html.Div(children=[
html.Div(
[
html.Div([
dcc.Textarea(id="text_area"),
html.Button("Create wordcloud", id="make_wordcloud"),
],
className="three columns"),
html.Div(
[
# The graph itself
html.Img(id='wordcloud_img',
src=encode_image("default_wordcloud.png")),
],
className="seven columns")
],
className="row"),
])
def vision_from_file(image_name, photo_file):
print("Sending to Google Vision from file...")
access_token = keyring.get_password("system", "VISION_API_KEY")
service = Service('vision', 'v1', access_token=access_token)
with open(photo_file, 'rb') as image:
base64_image = encode_image(image)
body = {
'requests': [{
'image': {
'content': base64_image,
},
'features': [
{
'type': 'LABEL_DETECTION',
'maxResults': 1000,
}
]
}]
}
response = service.execute(body=body)
labels = response['responses'][0]['labelAnnotations']
for label in labels:
print(label['description'] + ": " + str(label['score']))
# print(response)
return create_json(labels, image_name)
def updateImage(self, img):
srcName = os.path.basename(img.get('src'))
if srcName in self.images:
return self.images[srcName]
testPath = self._join(srcName)
if os.path.isfile(testPath):
self.images[srcName] = utils.encode_image(testPath)
return self.images[srcName]
else:
testPath2 = sizedRE.sub('_1280.', srcName)
if os.path.isfile(testPath2):
self.images[srcName] = utils.encode_image(testPath2)
return self.images[srcName]
if os.path.isfile(testPath):
i.replaceWith(
soup.new_tag("img",
src=encode_image(testPath),
**{"width": i.get('width')}))
return None
def plot_graph_text(n_clicks, text, user_id):
"""
Currently only word cloud visualizations are supported,
from given text.
Args:
n_clicks (int): Number of button clicks.
text (str): User-provided text used to create a word cloud.
user_id (str): Session/user id.
Returns:
str: the image encoded appropriately to be set as the 'src' \
value of the `img` element
"""
if text is not None and len(text.split()) > 1:
textviz.create_wordcloud(text, user_id)
return encode_image(f"static/images/{user_id}_wordcloud.png")
else:
# invalid arguments or Dash's first pass
return encode_image("default_wordcloud.png")
def getConvFeatures(data_in, img_data):
n_batch = 100
encoder, code_size = load_encoder()
img_features = np.empty((len(data_in), code_size),
dtype=theano.config.floatX)
for i in xrange(len(data_in) / n_batch + 1):
sys.stdout.write('\r' + str(i) + '/' + str(len(data_in) / n_batch))
sys.stdout.flush() # important
start = i * n_batch
end = min((i + 1) * n_batch, len(data_in))
images = img_data[start:end]
_, img_features[start:end] = encode_image(images, encoder)
data_in = np.column_stack((img_features, data_in))
return data_in, data_in.shape[1]
def predict_one_timestep(predict_func, encoder, code_size, initials, x,
out_size, iteration):
try:
img = CvBridge().imgmsg_to_cv2(camera1_msg, "bgr8")
img = np.array(img, dtype=np.float)
img = img[0:540, 250:840]
cv2.imwrite('predictions/current_image.jpg', img,
[int(cv2.IMWRITE_JPEG_QUALITY), 80])
except (CvBridgeError) as e:
print(e)
else:
image = PIL.Image.open('predictions/current_image.jpg')
current_scene_image = pre_process_image(image)
cv2.imshow(
'Input image',
cv2.resize(np.array(current_scene_image.transpose(
(1, 2, 0)))[..., ::-1], (0, 0),
fx=4,
fy=4,
interpolation=cv2.INTER_NEAREST))
cv2.waitKey(10)
current_scene_image = np.array(current_scene_image, dtype=np.float32)
images = np.array([current_scene_image])
_, encoded_images = encode_image(images, encoder)
decoded_images = decode_image(encoded_images, encoder)
cv2.imshow(
'Reconstructed image',
cv2.resize(np.array(decoded_images[0].transpose((1, 2, 0)))[..., ::-1],
(0, 0),
fx=4,
fy=4,
interpolation=cv2.INTER_NEAREST))
cv2.waitKey(10)
x = np.concatenate([encoded_images[0], x])
newinitials = predict_func([[x]])
raw_prediction = newinitials.pop().astype(theano.config.floatX)
if single_dim_out:
predicted_values = raw_prediction[:, -1, -1].astype(
theano.config.floatX).reshape((len(raw_prediction), ))
else:
predicted_values = raw_prediction[-1,
-1, :].astype(theano.config.floatX)
layer = 0
for initial, newinitial in zip(initials, newinitials):
if iteration % layer_resolutions[layer // 2] == 0:
initial.set_value(newinitial[-1].flatten())
layer += (2 if layer_models[layer // 2] == 'mt_rnn' else 1)
layer = min([layer, len(layer_resolutions)])
return predicted_values, newinitials
def alert(names, image):
global LAST_NAMES
should_alert = False
for name in names:
if name not in LAST_NAMES:
LAST_NAMES = names
should_alert = True
break
if should_alert:
print('alerting')
timestamp = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
req = requests.post(ADD_ALERT_ROUTE,
json={
"names": names,
"image": encode_image(image),
"timestamp": timestamp
})
def add_image_slice(self, question_num, group_num, box):
"""
Adds the image slice for the question to the list of images.
Args:
question_num (int): The question number.
group_num (int): The question's group number.
box (numpy.ndarray): An ndarray representing the test box image.
"""
im = self.get_image_slice(question_num, group_num, box)
encoded_im = utils.encode_image(im)
# Display image to screen if program runnning in debug mode.
if self.debug_mode:
cv.imshow('', im)
cv.waitKey()
self.images.append(encoded_im)
def main(photo_file):
"""Run a label request on a single image"""
access_token = os.environ.get('VISION_API')
service = Service('vision', 'v1', access_token=access_token)
with open(photo_file, 'rb') as image:
base64_image = encode_image(image)
body = {
'requests': [{
'image': {
'content': base64_image,
},
'features': [{
'type': 'LABEL_DETECTION',
'maxResults': 1,
}]
}]
}
response = service.execute(body=body)
label = response['responses'][0]['labelAnnotations'][0]['description']
print('Found label: {}'.format(label))
def main(photo_file):
"""Run a face detection request on a single image"""
access_token = os.environ.get('VISION_API')
service = Service('vision', 'v1', access_token=access_token)
with open(photo_file, 'rb') as image:
base64_image = encode_image(image)
body = {
'requests': [{
'image': {
'content': base64_image,
},
'features': [{
'type': 'FACE_DETECTION',
'maxResults': 1,
}]
}]
}
response = service.execute(body=body)
faces = response['responses'][0]['faceAnnotations']
print('Found faces: {}'.format(faces))
def main(photo_file):
"""Run a text detection request on a single image"""
access_token = 'AIzaSyAX6XocQFCDJK3EJcp4ZdfAx06hrYzhU-I'
service = Service('vision', 'v1', access_token=access_token)
with open(photo_file, 'rb') as image:
base64_image = encode_image(image)
body = {
'requests': [{
'image': {
'content': base64_image,
},
'features': [{
'type': 'TEXT_DETECTION',
'maxResults': 1,
}]
}]
}
response = service.execute(body=body)
print response
text = response['responses'][0]['textAnnotations'][0]['description']
print('Found text: {}'.format(text))
def get_text(image_file):
"""Run a text detection request on a single image"""
access_token = google_vision_api_key
if access_token == "None":
print("set VISION API KEY in config.ini")
sys.exit()
service = Service("vision", "v1", access_token=access_token)
with open(image_file, "rb") as image:
base64_image = encode_image(image)
body = {
"requests": [{
"image": {
"content": base64_image
},
"features": [{
"type": "TEXT_DETECTION",
"maxResults": 1
}],
}]
}
response = service.execute(body=body)
#print(response)
if "error" in response:
print(response["error"]["message"])
sys.exit()
if response["responses"][0]:
text = response["responses"][0]["textAnnotations"][0][
"description"]
# print('Found text: {}'.format(text))
else:
text = " "
return text
from server import app
from utils import encode_image, r
import sd_material_ui
import visdcc
import uuid
import pickle
import pandas as pd
import os
static_dir = os.path.dirname(__file__)
SideBar = [
html.Img(id="app_logo",
src=encode_image(os.path.join(static_dir,
"assets/images/y2d.png"))),
html.Br(),
visdcc.Run_js(id='theme_javascript'),
html.Div(html.A('Dark/Light theme'),
id="dark_theme",
n_clicks=0,
className="nav_item"),
# Collapsible button with external links
html.Div(html.A([
html.Span('External links'),
html.I(className="fa fa-caret-down", id="external_links_caret"),
]),
id='button_collapse',
n_clicks=0,
className="nav_item"),
def create_hotels():
create_hotel(
dict(
slug="la-bamba-de-areco",
name="La Bamba de Areco",
photo=encode_image("assets/images/la-bamba-de-areco.jpg"),
description=
"La Bamba de Areco está ubicada en San Antonio de Areco, en el corazón de "
"la pampa. Es una de las estancias más antiguas de la Argentina, "
"recientemente restaurada para ofrecer a sus huéspedes todo el confort y "
"esplendor colonial.",
availabilityFrom=current_time(),
availabilityTo=current_time() + 864000000, # 10 days
rooms=11,
city="Buenos Aires",
country="Argentina",
price=4))
create_hotel(
dict(
slug="sainte-jeanne",
name="Sainte Jeanne Boutique & Spa",
photo=encode_image("assets/images/sainte-jeanne.jpg"),
description=
"Sainte Jeanne Hotel Boutique & Spa está ubicado en el corazón de Los Troncos, "
"un barrio residencial y elegante de Mar del Plata. El lujo, el confort y la "
"pasión por los detalles dan personalidad a esta cálida propuesta.",
availabilityFrom=current_time() + 864000000, # 10 days,
availabilityTo=current_time() + 1296000000, # 15 days
rooms=23,
city="Mar del Plata",
country="Argentina",
price=2))
create_hotel(
dict(
slug="entre-cielos",
name="Entre Cielos",
photo=encode_image("assets/images/entre-cielos.jpg"),
description=
"Ubicado en una de las regiones vitivinícolas más grandes de América Latina, "
"Entre Cielos fue pensado y construido en un campo de 8 hectáreas rodeado de "
"viñedos malbec y una imponente vista de la Cordillera de Los Andes.",
availabilityFrom=current_time() + 432000000, # 5 days
availabilityTo=current_time() + 1296000000, # 15 days
rooms=16,
city="Mendoza",
country="Argentina",
price=4))
create_hotel(
dict(
slug="huacalera",
name="Hotel Huacalera",
photo=encode_image("assets/images/huacalera.jpg"),
description=
"Esta casona neocolonial, construida en la década de 1940, está ubicada en el "
"corazón de la Quebrada de Humahuaca, un extenso valle rodeado de imponentes "
"cadenas montañosas, recorrido por el Río Grande y declarado Patrimonio de la "
"Humanidad en 2003.",
availabilityFrom=current_time() + 1728000000, # 20 days
availabilityTo=current_time() + 2592000000, # 30 days
rooms=32,
city="Jujuy",
country="Argentina",
price=1))
create_hotel(
dict(
slug="merced-del-alto",
name="La Merced del Alto",
photo=encode_image("assets/images/merced-del-alto.jpg"),
description=
"Al pie del Nevado de Cachi, La Merced del Alto se destaca sobre el "
"pintoresco valle rodeado de cerros, ríos y arroyos. Dominando sobre lo alto, "
"el hotel y sus imponentes vistas invitan a explorar los Valle Calchaquíes o "
"simplemente a disfrutar de la paz del lugar.",
availabilityFrom=current_time(),
availabilityTo=current_time() + 432000000, # 5 days
rooms=14,
city="Salta",
country="Argentina",
price=2))
create_hotel(
dict(
slug="azur-real",
name="Azur Real Hotel",
photo=encode_image("assets/images/azur-real.jpg"),
description=
"La exclusividad rodeada de historia. Azur Real Hotel Boutique está ubicado en "
"el corazón de la zona comercial y el centro histórico de Córdoba, "
"dentro de uno de los principales circuitos culturales y turísticos de la "
"ciudad.",
availabilityFrom=current_time() + 1296000000, # 15 days
availabilityTo=current_time() + 2592000000, # 30 days
rooms=16,
city="Córdoba",
country="Argentina",
price=1))
create_hotel(
dict(
slug="rincon-del-socorro",
name="Rincón del Socorro",
photo=encode_image("assets/images/rincon-del-socorro.jpg"),
description=
"Rincón del Socorro es una estancia ubicada en la reserva natural de los "
"Esteros del Iberá, un santuario de vida silvestre, donde la Fundación "
"Conservation Land Trust decidió desarrollar un ambicioso proyecto de "
"recuperación y conservación.",
availabilityFrom=current_time() + 432000000, # 5 days
availabilityTo=current_time() + 1296000000, # 15 days
rooms=11,
city="Corrientes",
country="Argentina",
price=2))
create_hotel(
dict(
slug="luma-casa-de-montana",
name="Luma Casa de Montaña",
photo=encode_image("assets/images/luma-casa-de-montana.jpg"),
description=
"Emplazada en un entorno natural a orillas del lago Nahuel Huapi y con "
"la imponente imagen de la Cordillera de Los Andes, Luma Casa de Montaña "
"se presenta majestuosa pero a la vez simple y hogareña: un lugar "
"diferente, atemporal y mágico.",
availabilityFrom=current_time(),
availabilityTo=current_time() + 1296000000, # 15 days
rooms=8,
city="Villa La Angostura",
country="Argentina",
price=2))
create_hotel(
dict(
slug="casa-turquesa",
name="Casa Turquesa",
photo=encode_image("assets/images/casa-turquesa.jpg"),
description=
"Casa Turquesa es una histórica mansión del siglo XVIII que recrea el encanto "
"típico de Paraty, una de las herencias coloniales más bellas de Brasil, "
"declarada Patrimonio Mundial de la Humanidad por la UNESCO.",
availabilityFrom=current_time(),
availabilityTo=current_time() + 432000000, # 5 days
rooms=9,
city="Río de Janeiro",
country="Brasil",
price=3))
create_hotel(
dict(
slug="vila-da-santa",
name="Vila Da Santa",
photo=encode_image("assets/images/vila-da-santa.jpg"),
description=
"Esta casa de pescadores fue renovada con elegancia, pero sin descuidar su "
"espíritu original. Se abre a un gran patio central con dos piscinas de diseño, "
"una de ellas climatizada.",
availabilityFrom=current_time() + 864000000, # 10 days
availabilityTo=current_time() + 1296000000, # 15 days
rooms=19,
city="Buzios",
country="Brasil",
price=3))
create_hotel(
dict(
slug="uxua-casa",
name="UXUA Casa Hotel & Spa",
photo=encode_image("assets/images/uxua-casa.jpg"),
description=
"UXUA Casa Hotel & Spa es un hotel boutique cinco estrellas reconocido "
"mundialmente por su incomparable belleza tropical, el maravilloso bar con "
"vista al mar, el galardonado restaurante, un gimnasio totalmente equipado y el "
"inigualable spa Almescar que ofrece innovadores tratamientos con ingredientes "
"extraídos de la selva.",
availabilityFrom=current_time(),
availabilityTo=current_time() + 864000000, # 10 days
rooms=11,
city="Bahía",
country="Brasil",
price=4))
create_hotel(
dict(
slug="ponta-dos-ganchos",
name="Ponta dos Ganchos",
photo=encode_image("assets/images/ponta-dos-ganchos.jpg"),
description=
"Ubicado a pasos de San Pablo, Río de Janeiro, e incluso Buenos Aires, "
"en una península privada y rodeado por un pintoresco pueblo de pescadores, "
"se encuentra Ponta dos Ganchos, uno de los resorts de playa más exclusivos "
"del sur de Brasil.",
availabilityFrom=current_time() + 432000000, # 5 days
availabilityTo=current_time() + 864000000, # 10 days
rooms=25,
city="Santa Catarina",
country="Brasil",
price=4))
create_hotel(
dict(
slug="alto-atacama",
name="Alto Atacama",
photo=encode_image("assets/images/alto-atacama.jpg"),
description=
"Alto Atacama Desert Lodge & Spa es un distinguido refugio ubicado a los pies "
"del Pukará de Quitor en el imponente desierto de Atacama al norte de Chile.",
availabilityFrom=current_time(),
availabilityTo=current_time() + 864000000, # 10 days
rooms=42,
city="San Pedro de Atacama",
country="Chile",
price=4))
create_hotel(
dict(
slug="tierra-patagonia",
name="Tierra Patagonia",
photo=encode_image("assets/images/tierra-patagonia.jpg"),
description=
"Tierra Patagonia Hotel & Spa es un lujoso hotel boutique ubicado en la "
"Patagonia chilena a orillas del lago Sarmiento, envuelto en el "
"extraordinario escenario natural de Torres del Paine, un parque nacional "
"rodeado de montañas, cascadas, glaciares, lagos y peñascos, "
"declarado Reserva de la Biosfera por la UNESCO en 1978.",
availabilityFrom=current_time() + 2592000000, # 30 days
availabilityTo=current_time() + 3456000000, # 40 days
rooms=40,
city="Torres del Paine",
country="Chile",
price=4))
create_hotel(
dict(
slug="vira-vira",
name="Vira Vira",
photo=encode_image("assets/images/vira-vira.jpg"),
description=
"Hotel Hacienda Vira Vira Relais & Chateaux se encuentra en una ubicación "
"privilegiada, muy cerca de Pucón, Chile. Su impresionante parque nativo de 23 "
"hectáreas a orillas del río Liucura ofrece"
" un oasis único de paz y tranquilidad.",
availabilityFrom=current_time() + 864000000, # 10 days
availabilityTo=current_time() + 1728000000, # 20 days
rooms=21,
city="Pucón",
country="Chile",
price=4))
create_hotel(
dict(
slug="vik-chile",
name="Vik Chile",
photo=encode_image("assets/images/vik-chile.jpg"),
description=
"Vik Chile es una hacienda moderna y sofisticada en donde confluyen el arte y el "
"diseño de vanguardia, una ubicación sin igual, fabulosos escenarios naturales, "
"servicio personalizado y una cuidada atención por el medioambiente.",
availabilityFrom=current_time() + 432000000, # 5 days
availabilityTo=current_time() + 1728000000, # 20 days
rooms=22,
city="Millahue",
country="Chile",
price=4))
create_hotel(
dict(
slug="casa-higueras",
name="Casa Higueras",
photo=encode_image("assets/images/casa-higueras.jpg"),
description=
"Ubicada en el corazón del Cerro Alegre, frente a la imponente bahía de "
"Valparaíso, se encuentra Casa Higueras, el primer hotel boutique y de diseño "
"del puerto.",
availabilityFrom=current_time() + 432000000, # 5 days
availabilityTo=current_time() + 1296000000, # 15 days
rooms=20,
city="Valparaíso",
country="Chile",
price=4))
create_hotel(
dict(
slug="campo-tinto",
name="Campo Tinto",
photo=encode_image("assets/images/campo-tinto.jpg"),
description=
"Campo Tinto es una chacra de 25 hectáreas ubicada en el corazón de San Roque, "
"en medio del ondulante Carmelo, una zona de chacras, viñedos, bodegas y "
"frutales, con mucha historia y un ritmo de vida tranquilo y natural.",
availabilityFrom=current_time() + 2160000000, # 25 days
availabilityTo=current_time() + 2592000000, # 30 days
rooms=4,
city="Colonia",
country="Uruguay",
price=1))
def main1():
directory = askopenfile()
filename = directory.name
W = 500
H = 600
tex.delete(1.0, END)
tex.insert(tk.END, filename)
if (".png" in filename or ".jpg" in filename or ".pdf" in filename):
if (".pdf" in filename):
images = convert_from_path(filename)
im1 = images[0]
im1.save('jpg1.jpg')
img = cv2.imread('jpg1.jpg')
filename = 'jpg1.jpg'
else:
img = cv2.imread(filename)
im1 = cv2.resize(img, (W, H))
im1 = cv2.cvtColor(im1, cv2.COLOR_BGR2RGB)
im1 = Image.fromarray(im1)
im1 = ImageTk.PhotoImage(im1)
panelA = Label(image=im1)
panelA.image = im1
panelA.place(x=10, y=50)
canvas = tk.Canvas(window, width=W, height=H)
canvas.create_image(0, 0, image=im1, anchor=NW)
canvas.place(x=10, y=50)
"""Run a text detection request on a single image"""
# os.environ['VISION_API'] = 'F:/Mycompleted task/OCR/vendornam/key.json'
access_token = 'AIzaSyDMTvUK6Mlr_BWwwjJ3eFVxhGDKixlFgjQ'
service = Service('vision', 'v1', access_token=access_token)
with open(filename, 'rb') as image:
base64_image = encode_image(image)
body = {
'requests': [{
'image': {
'content': base64_image,
},
'features': [{
'type': 'TEXT_DETECTION',
'maxResults': 1,
}]
}]
}
response = service.execute(body=body)
res = response['responses'][0]['textAnnotations']
invoice_num = find_invoice_number(res)
invoice_dat = invoice_date(res)
invoice_total = Totla_amount(res)
invoice_name, index = vendorname(res)
invoice_address = vendor_address(res, invoice_name, index)
items = item_find(res)
outtext.delete(1.0, END)
result = "Vendor name: " + invoice_name + '\n'
result += "Vendor address: " + invoice_address + '\n'
result += "Invoice number: " + invoice_num + '\n'
result += "Invoice Date: " + invoice_dat + '\n'
if (len(items) != 0):
for t in range(len(items)):
result += "item" + str(t + 1) + ": " + items[t] + '\n'
result += "Total Amount: " + invoice_total + '\n'
outtext.insert(tk.END, result)
print("invoice_num: " + invoice_num)
print("invoice_date: " + invoice_dat)
print("invoice_total: " + invoice_total)
print("invoice_name: " + invoice_name)
print("invoice_address: " + invoice_address)
if os.path.exists('jpg1.jpg'):
os.remove("jpg1.jpg")
"pairplot": "Pair-plot (matplotlib)"
}
buttons = []
for graph_type in available_graphs.keys():
img_name = "static/images/graph_images/" + graph_type + ".png"
buttons.append(
html.Div([
html.P(available_graphs[graph_type],
style={
"marginBottom": "0",
"textAlign": "center"
}),
html.Button(
[html.Img(src=encode_image(img_name), height=45, width=45)],
id=graph_type,
style={
"margin": "10px",
"height": "60px",
"width": "70px"
})
],
style={
"display": "inline-block",
"margin": "10px"
}))
def Exploration_Options(options):
"""
