def __init__(self) -> None:
App.__init__(self)
#Allows access to controller class to send signals
self.Controller = Controller()
#For GPS/Mapping
self.TargetInfo = TargetInfo()
self.tp = None
self.th_drone_control = None
self.th_drone_adv_control = None
self.th_doc = None
Cache.remove('kv.image')
Cache.remove('kv.texture')
image = Image.open("Gmap/default.png")
temp = image.copy()
temp.save("Gmap/drone_path.png")
image = Image.open("images/default_score.png")
temp = image.copy()
temp.save("images/scored.png")
temp.save("images/prescored.png")
def generateGlyph(self):
global curr_prd
global curr_conf
if (curr_prd == -1):
shutil.copy("glyphNoData_crp.png", "currentGlyph.png")
else:
stemName = ['G', 'F', 'E', 'D', 'C', 'B', 'A']
# offset confidence so 0.3 is lowest then in steps of 0.1 upwards
if curr_conf < 0.3:
nameIndx = 0
else:
nameIndx = int(10.0 * (curr_conf - 0.3))
nameIndx = np.clip(nameIndx, 0, 6)
filename = '.\\VisEntGlyphs\\' + stemName[
nameIndx] + '_crp_over.png'
source_img = Image.open(filename).convert("RGBA")
draw = ImageDraw.Draw(source_img)
font = ImageFont.truetype("arial.ttf", 240)
num = str(curr_prd)
xD, yD = draw.textsize(num, font=font)
draw.text((320 - (xD / 2), 240 - (yD / 2)),
num,
fill=(255, 255, 0, 255),
font=font)
font = ImageFont.truetype("arial.ttf", 32)
txt = "High ------------- probability ------------- Low"
draw.text((20, 525), txt, fill=(51, 51, 51, 255), font=font)
source_img.save("currentGlyph.png")
def view_selected_file(self, path, filename):
try:
if filename == []:
self.root.ids._My_file_name.text = "MyFile"
self.root.ids._Usb_file_name.text = "USB"
self.root.ids._My_file_hint.text = "Select BMP File"
self.root.ids._Usb_file_hint.text = "Select BMP File"
elif (filename[0][-3:] != 'bmp'):
self.root.ids._My_file_hint.text = "Select BMP File"
self.root.ids._Usb_file_hint.text = "Select BMP File"
else:
if self.root.ids._screen_manager.current == 'myfile_screen':
self.root.ids._My_file_name.text = filename[0]
if self.root.ids._screen_manager.current == 'usb_screen':
self.root.ids._Usb_file_name.text = filename[0]
with Image.open(os.path.join(path, filename[0])) as stream:
width, height = stream.size
if self.root.ids._screen_manager.current == 'myfile_screen':
self.root.ids._My_file_size.text = '{} x {}'.format(
width, height)
if self.root.ids._screen_manager.current == 'usb_screen':
self.root.ids._Usb_file_size.text = '{} x {}'.format(
width, height)
except Exception:
print('unknow error in view_selecected_file')
def img_to_text(self):
from PIL import Image
img = Image.open(self.img_to_text_path)
text_extracted = image_to_string(img)
text_extracted = text_extracted[:-2]
self.screen.get_screen('home').ids.text_extracted.text = text_extracted
self.screen.get_screen('home').ids.text_extracted.hint_text = ''
Snackbar(text='Image to text conversion successfully done').open()
def scan():
"""This methods sets up the pi camera and scans a qr-code. The method returns either a qr-code
or False value"""
print('scan method called')
# starts the process of using the camera and scanning
# in the following procedure the pi camera is called camera
with PiCamera() as camera:
# because it's unclear whether the camera works as expected it's in a try except block
# if any problem occurs the program doesn't stop
try:
# starts a preview of the camera but not seen because of the kivy grafic framework
camera.start_preview()
# program sleeps for a second
time.sleep(1)
print('start scanning')
# if any problem occurs inside the try block, the exception block will execute
except:
print('problem with pi camera start')
# creates a file-like object for reading and writing bytes
stream = BytesIO()
# variable for the qr-code later
qr_codes = None
# Set timeout to 10 seconds
timeout = time.time() + 10
# as long as there is no qr-code in qr_codes and the timeout is not reached stay in this loop
# and try to get an qr-code
while qr_codes is None and (time.time() < timeout):
stream.seek(0)
# Start camera stream (make sure RaspberryPi camera is focused correctly
# manually adjust it, if not)
# camera captures an image from the stream
camera.capture(stream, "jpeg")
stream.seek(0)
# zbarlight scans the image stream for a specific code --> here it's a qr-code and puts it
# into the variable
qr_codes = zbarlight.scan_codes("qrcode", Image.open(stream))
# program stops for 50 milli seconds
time.sleep(0.05)
# after the loop the preview stops
camera.stop_preview()
# break immediately if we didn't get a qr code scan
if not qr_codes:
print('no qr code within 10 seconds')
return False
# decode the first qr_code to get the data
qr_code = qr_codes[0].decode()
return qr_code
def build(self): ikon=content[3] s = ScatterPlane(scale=.5) filename=join(imdir, 'background.png') print filename[:-1] filename2=join(imdir,content[1][:-1]) print filename2 im=Image(source=filename2,size=(1920,1090)) img=Image.open(filename2) exif_data=img._getexif(); s.add_widget(im) return s
def data_img(self): #将数据绘制在课表上
img = Image.open("form.png")
draw = ImageDraw.Draw(img)
font = ImageFont.truetype('simhei.ttf', 20)
pos_x = 265.62
pos_y = 270.9
for each in self.res:
for child in each:
draw.text((pos_x, pos_y), child, fill=(255, 0, 255), font=font)
pos_x = pos_x + 200
pos_x = 265.6
pos_y = pos_y + 220
img.save("course.png")
def circularize_img(img_fn,
width,
im=None,
do_crop=True,
bw=False,
resize=True,
circularize=True):
from PIL import Image, ImageOps, ImageDraw
from kivy.app import App
import numpy as np
log = App.get_running_app().log
#if not im:
im = Image.open(img_fn).convert('RGB')
log('??', im)
# get center
if do_crop: im = crop_square(im, width, width)
if resize: im = im.resize((width, width))
if bw:
thresh = 175
fn = lambda x: 255 if x > thresh else 0
im = im.convert('L').point(fn, mode='1').convert('RGB')
orig_color = (255, 255, 255)
replacement_color = COLOR_ICON #(255,0,0)
# img = im.convert('RGB')
data = np.array(im)
data[(data == orig_color).all(axis=-1)] = replacement_color
im = Image.fromarray(data, mode='RGB').convert('RGBA')
if circularize_img:
bigsize = (im.size[0] * 3, im.size[1] * 3)
mask = Image.new('L', bigsize, 0)
draw = ImageDraw.Draw(mask)
draw.ellipse((0, 0) + bigsize, fill=255)
mask = mask.resize(im.size, Image.ANTIALIAS)
im.putalpha(mask)
# give back bytes
log('!!', im)
output = ImageOps.fit(im, mask.size, centering=(0.5, 0.5))
imgByteArr = io.BytesIO()
output.save(imgByteArr, format='PNG')
# imgByteArr = imgByteArr.getvalue()
imgByteArr.seek(0)
return imgByteArr
def select_to(self,*args):
try:
print args[1][0]
iw = Image.open(args[1][0])
iw.save('Yellow_Rose.jpg')
gray = iw.convert('1')
gray.save('Yellow_Rose.jpg')
self.img3.source = 'Yellow_Rose.jpg'
self.img4.source = 'Yellow_Rose.jpg'
self.img.source = 'Yellow_Rose.jpg'
self.img.reload()
self.img3.reload()
self.img4.reload()
except:
pass
def text(self, selection):
if selection == []:
layout = BoxLayout(orientation="vertical", spacing=10, padding=10)
popupLabel = Label(text="No file is selected .")
print("No file is selected .")
closeButton = Button(background_normal='img\close.png',
background_down='img\close.png',
size_hint=(.38, .6),
pos_hint={"center_x": .5})
layout.add_widget(popupLabel)
layout.add_widget(closeButton)
popup = Popup(title='Error', content=layout, size_hint=(.8, .6))
popup.open()
closeButton.bind(on_press=popup.dismiss)
engine = pyttsx3.init()
if self.soundcount == 0:
engine.say("No file is selected .")
print("No file is selected .")
engine.runAndWait()
else:
print("Input Path : {}".format(selection[0]))
try:
from PIL import Image
except ImportError:
import Image
import pytesseract
pytesseract.pytesseract.tesseract_cmd = 'C:\Softwares\Tesseract-OCR\Tesseract.exe'
text = pytesseract.image_to_string(Image.open(selection[0]))
if text == "":
text = "There is no text in the image ."
layout = BoxLayout(orientation="vertical", spacing=10, padding=10)
popupLabel = Label(text=text)
closeButton = Button(background_normal='img\close.png',
background_down='img\close.png',
size_hint=(.38, .31),
pos_hint={"center_x": .5})
layout.add_widget(popupLabel)
layout.add_widget(closeButton)
popup = Popup(title='Text Recognition',
content=layout,
size_hint=(.8, .9))
popup.open()
closeButton.bind(on_press=popup.dismiss)
print(text)
engine = pyttsx3.init()
if self.soundcount == 0:
engine.say(text)
engine.runAndWait()
def uploadImage(self, instance):
Tk().withdraw(
) # we don't want a full GUI, so keep the root window from appearing
filename = askopenfilename(
) # show an "Open" dialog box and return the path to the selected file
print(filename)
transform = transforms.Compose(
[transforms.Resize(128),
transforms.ToTensor()])
image = Image.open(filename)
image_tensor = transform(image).float()
image_tensor = image_tensor.unsqueeze_(0)
output = model(image_tensor)
index = output.data.numpy().argmax()
print(location[index])
def on_touch_down(self, touch):
super(CalibrationScreen, self).on_touch_down(touch)
# Normalized position on the image.
# First get the coordinates clicked, 0, 0 starts at the bottom left of the image (determined by image_offset).
normalized_pos = [touch.x - self.image_offset[0], touch.y - self.image_offset[1]]
# Get the location clicked IN PERCENTAGE of the image's size:
normalized_pos[0] = normalized_pos[0] / self.image_dimensions[0]
normalized_pos[1] = normalized_pos[1] / self.image_dimensions[1]
# Check if image was clicked and selection in progress, basically if percentage is above 100 or below 0
# we're calculating based on 0-1 where 1 is 100%. If self.selection is -1, no selection was made and
# nothing happens.
if(self.selection == -1 or
normalized_pos[0] > 1 or normalized_pos[0] < 0 or
normalized_pos[1] > 1 or normalized_pos[1] < 0):
# Selection is not turned on OR the user clicked outside the image. Do NADA!
return
# Open the image that was clicked, we're gonna get them pesky pixels
img = Image.open('calibImage.jpg')
# The percentage times the image's width and height, where da pixel at?
img_x = normalized_pos[0] * img.width
img_y = normalized_pos[1] * img.height
# Invert the y coordinate inside the image:
img_y = img.height - img_y
# Grab color values of the clicked pixel.
r, g, b = img.getpixel((img_x, img_y))
# Depending on action, set min or max.
if self.selection == 0:
CURRENT_COLOR.set_min([b, g, r])
self.r_min = r / 255
self.g_min = g / 255
self.b_min = b / 255
if self.selection == 1:
CURRENT_COLOR.set_max([b, g, r])
self.r_max = r / 255
self.g_max = g / 255
self.b_max = b / 255
# Resets select action.
self.selection = -1
self.current_action_string = 'No action selected'
self.update_color_string()
def getImagesAndLabels(path):
imagePaths = [os.path.join(path, f) for f in os.listdir(path)]
faceSamples = []
ids = []
for imagePath in imagePaths:
PIL_img = Image.open(imagePath).convert('L') # convert it to grayscale
img_numpy = np.array(PIL_img, 'uint8')
id = int(os.path.split(imagePath)[-1].split(".")[1])
faces = detector.detectMultiScale(img_numpy)
for (x, y, w, h) in faces:
faceSamples.append(img_numpy[y:y + h, x:x + w])
ids.append(id)
return faceSamples, ids
def update_icon(self, online=True):
offline = '_offline'
if online:
offline = ''
self.icon_wid.source = 'data/icon' + offline + '.png'
try:
upload_count = len(glob.glob('offline/*.json'))
if upload_count > 0:
img = Image.open('data/icon' + offline + '.png')
draw = ImageDraw.Draw(img)
draw.ellipse((50, 65, 95, 95), fill=(165, 208, 101, 0))
font = ImageFont.truetype("data/verdanab.ttf", 24)
posx = 65
if upload_count > 9:
posx = 55
draw.text((posx, 65), str(upload_count), (255, 255, 255), font=font)
img.save('data/icon2' + offline + '.png')
self.icon_wid.source = 'data/icon2' + offline + '.png'
self.icon_wid.reload()
except:
traceback.print_exc(file=sys.stdout)
def capture(self):
# Defining a format for the captured image
camera = self.ids['camera']
timestr = time.strftime("%Y%m%d_%H%M%S")
# Saving captured image
camera.export_to_png("IMG_{}.png".format(timestr))
# Function inheriting from PIL module
# Used to crop white space out of an image
def trim(im):
bg = Image.new(im.mode, im.size, im.getpixel((0, 0)))
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
if bbox:
return im.crop(bbox)
# Trimming the captured image and replacing it with the trimmed image
im = Image.open("IMG_{}.png".format(timestr))
im = trim(im)
im.save("IMG_{}.png".format(timestr))
# Defining each popup for each disease with statically defined dynamics
def show_popup_akiec():
show = akiec()
popupWindow = Popup(title="The Results",
content=show,
size_hint=(None, None),
size=(400, 400))
popupWindow.open()
def show_popup_bcc():
show = bcc()
popupWindow = Popup(title="The Results",
content=show,
size_hint=(None, None),
size=(400, 400))
popupWindow.open()
def show_popup_bkl():
show = bkl()
popupWindow = Popup(title="The Results",
content=show,
size_hint=(None, None),
size=(400, 400))
popupWindow.open()
def show_popup_df():
show = df()
popupWindow = Popup(title="The Results",
content=show,
size_hint=(None, None),
size=(400, 400))
popupWindow.open()
def show_popup_mel():
show = mel()
popupWindow = Popup(title="The Results",
content=show,
size_hint=(None, None),
size=(400, 400))
popupWindow.open()
def show_popup_nv():
show = nv()
popupWindow = Popup(title="The Results",
content=show,
size_hint=(None, None),
size=(400, 400))
popupWindow.open()
def show_popup_vasc():
show = vasc()
popupWindow = Popup(title="The Results",
content=show,
size_hint=(None, None),
size=(400, 400))
popupWindow.open()
def show_popup_norm():
show = norm()
popupWindow = Popup(title="The Results",
content=show,
size_hint=(None, None),
size=(400, 400))
popupWindow.open()
def show_popup_obj():
show = obj()
popupWindow = Popup(title="The Results",
content=show,
size_hint=(None, None),
size=(400, 400))
popupWindow.open()
# Function inheriting from cv2 module
# Read the image and convert to grayscale
# Resize the image to match model's expected sizing
def prepare(filepath):
img_array = cv2.imread(filepath, cv2.IMREAD_GRAYSCALE)
new_array = cv2.resize(img_array, (28, 28))
return new_array.reshape(-1, 28, 28, 1)
# Making a dictionary for each skin disease classification
# Machine learning will assign an integer value to each classification key
key = {
"akiec": 0,
"bcc": 1,
"bkl": 2,
"df": 3,
"mel": 4,
"nv": 5,
"vasc": 6,
"norm": 7,
"obj": 8
}
key = {v: k for k, v in key.items()}
# Defining a prediction which contains numerical values based on the image we give it
prediction = cnn_model.predict(prepare("IMG_{}.png".format(timestr)))
print(prediction)
# Set of conditional statements used to display the right popup based on the machine learning prediction
if prediction[0][0] == 1:
show_popup_akiec()
print("The ml says " + key[0])
time.sleep(1)
elif prediction[0][1] == 1:
show_popup_bcc()
print("The ml says " + key[1])
time.sleep(1)
elif prediction[0][2] == 1:
show_popup_bkl()
print("The ml says " + key[2])
time.sleep(1)
elif prediction[0][3] == 1:
show_popup_df()
print("The ml says " + key[3])
time.sleep(1)
elif prediction[0][4] == 1:
show_popup_mel()
print("The ml says " + key[4])
time.sleep(1)
elif prediction[0][5] == 1:
show_popup_nv()
print("The ml says " + key[5])
time.sleep(1)
elif prediction[0][6] == 1:
show_popup_vasc()
print("The ml says " + key[6])
time.sleep(1)
elif prediction[0][7] == 1:
show_popup_norm()
print("The ml says " + key[7])
time.sleep(1)
elif prediction[0][8] == 1:
show_popup_obj()
print("The ml says " + key[8])
time.sleep(1)
def guardar_informe(self):
# GESTION DE ERRORES
global datos_introducidos
try:
self.verificar_parametros(datos_introducidos)
except ErrorEntrada as e:
self.show_popup(e.message)
return
try:
self.revisar_audio_cargado()
except ErrorEntrada as e:
self.show_popup(e.message)
return
frecuencias = [63,125,250,500,1000,1500,2000,3000,4000,6000,8000]
h,h_prima,atenuacion_h,atenuacion_h_prima = self.calcular_prt()
wbk = xlwt.Workbook(encoding='utf-8')
hoja_datos = wbk.add_sheet('1. DATOS', cell_overwrite_ok=True)
hoja_datos.protect = True
sheet = wbk.add_sheet(u'2. CALCÚLE', cell_overwrite_ok=True)
sheet.protect = True
sheet1 = wbk.add_sheet(u'3. ESCÚCHE', cell_overwrite_ok=True)
sheet1.protect = True
sheet2 = wbk.add_sheet(u'4. PREVÉNGA', cell_overwrite_ok=True)
sheet2.protect = True
alignment = xlwt.Alignment() # Create Alignment
alignment.horz = xlwt.Alignment.HORZ_CENTER
borders = xlwt.Borders() # Create Borders
borders.left = xlwt.Borders.MEDIUM
borders.right = xlwt.Borders.MEDIUM
borders.top = xlwt.Borders.MEDIUM
borders.bottom = xlwt.Borders.MEDIUM
borders.left_colour = 0x40
borders.right_colour = 0x40
borders.top_colour = 0x40
borders.bottom_colour = 0x40
estilobg = xlwt.XFStyle()
pattern = xlwt.Pattern() # Create the Pattern
pattern.pattern = xlwt.Pattern.NO_PATTERN
pattern.pattern_fore_colour = xlwt.Style.colour_map['white']
# ENCABEZADOS 1 -ARIAL 13- -BOLD- -IZQUIERDA- -CON BORDES-
estilo11 = xlwt.XFStyle()
font = xlwt.Font()
font.name = 'Arial'
font.height = 260
font.bold = True
estilo11.font = font
estilo11.borders = borders
# TÍTULO -ARIAL 15- -BOLD- -CENTRADO-
estilo = xlwt.XFStyle()
font = xlwt.Font()
font.height = 300
font.bold = True
estilo.font = font
estilo.alignment = alignment
# ENCABEZADOS 2 -ARIAL 13- -BOLD- -CENTRADO- -SIN BORDES-
estilo12 = xlwt.XFStyle()
font.height = 260
font.bold = True
estilo12.font = font
estilo12.alignment = alignment
# FRECUENCIAS -ARIAL 13- -BOLD- -CENTRADO- -CON BORDES-
estilo1 = xlwt.XFStyle()
font.height = 260
font.bold = True
estilo1.font = font
estilo1.alignment = alignment
estilo1.borders = borders
# VALORES -ARIAL 13- -CENTRADO- -CON BORDES-
estilo2 = xlwt.XFStyle()
font = xlwt.Font()
font.height = 260
estilo2.font = font
estilo2.alignment = alignment
estilo2.borders = borders
# VALORES -ARIAL 13- -CENTRADO- -SIN BORDES-
estilo21 = xlwt.XFStyle()
font = xlwt.Font()
font.height = 260
estilo21.font = font
estilo21.alignment = alignment
fecha_hora = datetime.now().strftime('%d/%m/%y %H:%M')
# DATOS INTRODUCIDOS ___________________________________________________
edad= datos_introducidos.edad
sexo = datos_introducidos.sexo
tiempo_exposicion = datos_introducidos.tiempo_exposicion
nivel_exposicion = datos_introducidos.nivel_exposicion
fractil = datos_introducidos.fractil
hoja_datos.write_merge(0,4,0,13,'',estilobg)
hoja_datos.write_merge(5,9,0,5,'',estilobg)
hoja_datos.write_merge(5,9,8,13,'',estilobg)
hoja_datos.write_merge(10,11,0,13,'',estilobg)
hoja_datos.write_merge(0,0,0,13,u'INFORME SOFTWARE CALCÚLE, ESCÚCHE Y PREVÉNGA',estilo)
hoja_datos.write_merge(1,1,0,13,'Fecha: '+ fecha_hora + ' - Página 1/4',estilo12)
hoja_datos.write_merge(3,3,0,13,u'DATOS',estilo12)
hoja_datos.write(5,6,'Edad:',estilo11)
hoja_datos.write(6,6,'Sexo:',estilo11)
hoja_datos.write(7,6,u'Fráctil:',estilo11)
hoja_datos.write(8,6,u'Tiempo de Exposición:',estilo11)
hoja_datos.write(9,6,u'Nivel de Exposición:',estilo11)
hoja_datos.write(5,7,edad,estilo2)
hoja_datos.write(6,7,sexo,estilo2)
hoja_datos.write(7,7,fractil,estilo2)
hoja_datos.write(8,7,tiempo_exposicion,estilo2)
hoja_datos.write(9,7,nivel_exposicion,estilo2)
hoja_datos.col(6).width = 256*28
hoja_datos.col(7).width = 256*7
i=0
while i < 6:
hoja_datos.col(i).width = 256*6
i+=1
i=8
while i < 14:
hoja_datos.col(i).width = 256*6
i+=1
hoja_datos.write_merge(12,12,0,13,'Continúe a la página 2 >>>>', estilo21)
# hoja_datos.write_merge(12,12,0,13,'Con ɔopyleft', estilo21)
# INFORME CALCÚLE ______________________________________________________
sheet.write_merge(0,4,0,13,'',estilobg)
sheet.write_merge(5,7,0,0,'',estilobg)
sheet.write_merge(5,7,13,13,'',estilobg)
sheet.write_merge(8,35,0,13,'',estilobg)
sheet.write_merge(0,0,0,13,u'INFORME SOFTWARE CALCÚLE, ESCÚCHE Y PREVÉNGA',estilo)
sheet.write_merge(1,1,0,13,'Fecha: '+ fecha_hora + ' - >>> Página 2/4 <<<',estilo12)
sheet.write_merge(3,3,0,13,u'ESTIMACIÓN DE PÉRDIDA AUDITIVA H Y H\'',estilo12)
sheet.write(5,1,'Frec. (Hz)',estilo11)
sheet.write(6,1,'H',estilo11)
sheet.write(7,1,'H\'',estilo11)
for i,x in enumerate(frecuencias):
sheet.write(5,i+2,frecuencias[i],estilo1) # Freq
sheet.write(6,i+2,h[i],estilo2) # H
sheet.write(7,i+2,h_prima[i],estilo2) # H'
# ancho columnas
sheet.col(0).width = 256*7 # una pulgada
sheet.col(1).width = 256*13 # 256 * Nro caracteres
sheet.col(2).width = 256*6
sheet.col(3).width = 256*6
sheet.col(4).width = 256*6
i=5
while i < 14:
sheet.col(i).width = 256*7
i+=1
ancho = 605
alto = 454
imagen = Image.open(os.path.join('images', 'H_y_Hprima_octavs.png')).resize((ancho,alto),Image.ANTIALIAS).convert('RGB').save(os.path.join('images', 'H_y_Hprima_octavs.bmp'))
sheet.insert_bitmap(os.path.join('images', 'H_y_Hprima_octavs.bmp'),9,1)
# INFORME ESCÚCHE __________________________________________________________________
sheet1.write_merge(0,39,0,13,'',estilobg)
sheet1.write_merge(0,0,0,13,u'INFORME SOFTWARE CALCÚLE, ESCÚCHE Y PREVÉNGA',estilo)
sheet1.write_merge(1,1,0,13,'Fecha: '+ fecha_hora + ' - >>> Página 3/4 <<<',estilo12)
global directorio_audio
audio_seleccionado= directorio_audio
sheet1.write_merge(3,3,0,13,'Audio: '+ os.path.basename(audio_seleccionado),estilo21)
sheet1.write_merge(5,5,0,13,u'FORMA DE ONDA',estilo12)
sheet1.write_merge(12,12,0,13,u'ESPÉCTRO',estilo12)
alto1= 95
ancho1= 296 + 100
imagen1 = Image.open(os.path.join('images', 'forma_de_onda.png')).resize((ancho1,alto1),Image.ANTIALIAS).convert('RGB').save(os.path.join('images', 'forma_de_onda.bmp'))
sheet1.insert_bitmap(os.path.join('images', 'forma_de_onda.bmp'),6,3)
ancho11= ancho + 165
imagen11 = Image.open(os.path.join('images', 'espectros.png')).resize((ancho11,alto),Image.ANTIALIAS).convert('RGB').save(os.path.join('images', 'espectros.bmp'))
sheet1.insert_bitmap(os.path.join('images', 'espectros.bmp') ,13,1)
sheet1.col(0).width = 256*7 # una pulgada
sheet1.col(1).width = 256*13 # 256 * Nro caracteres
sheet1.col(2).width = 256*6
sheet1.col(3).width = 256*6
sheet1.col(4).width = 256*6
i=5
while i < 14:
sheet1.col(i).width = 256*7
i+=1
# INFORME PREVÉNGA _______________________________________________________________
sheet2.write_merge(0,4,0,13,'',estilobg)
sheet2.write_merge(5,7,0,0,'',estilobg)
sheet2.write_merge(5,7,13,13,'',estilobg)
sheet2.write_merge(8,39,0,13,'',estilobg)
sheet2.write_merge(0,0,0,13,u'INFORME SOFTWARE CALCÚLE, ESCÚCHE Y PREVÉNGA',estilo)
sheet2.write_merge(1,1,0,13,'Fecha: '+ fecha_hora + ' - >>> Página 4/4 <<<',estilo12)
sheet2.write_merge(3,3,0,13,u'ATENUACIÓN PROTECTORES AUDITIVOS',estilo12)
sheet2.write(5,1,'Frec. (Hz)',estilo11)
sheet2.write(6,1,'At. EPI',estilo11)
sheet2.write(7,1,'At. Est. H\'',estilo11)
protector_auditivo= self.spinner_prt.text
sheet2.write_merge(9,9,0,6,u'Protector Auditivo: '+ protector_auditivo,estilo21)
for i,x in enumerate(frecuencias):
sheet2.write(5,i+2,frecuencias[i],estilo1)
sheet2.write(6,i+2,atenuacion_h[i],estilo2)
sheet2.write(7,i+2,atenuacion_h_prima[i],estilo2)
sheet2.col(0).width = 256*7 # una pulgada
sheet2.col(1).width = 256*13 # 256 * Nro caracteres
sheet2.col(2).width = 256*6
sheet2.col(3).width = 256*6
sheet2.col(4).width = 256*6
i=5
while i < 14:
sheet2.col(i).width = 256*7
i+=1
ancho2= 76
alto2= 76
imagen2 = Image.open(os.path.join('images', 'grafica_protectores.png')).resize((ancho,alto),Image.ANTIALIAS).convert('RGB').save(os.path.join('images', 'grafica_protectores.bmp'))
sheet2.insert_bitmap(os.path.join('images', 'grafica_protectores.bmp'),13,1)
imagen_protector= self.imagen_prt_epi.source
imagen22 = Image.open(imagen_protector).resize((ancho2,alto2),Image.ANTIALIAS).convert('RGB').save(os.path.join('images', 'protector_seleccionado.bmp'))
sheet2.insert_bitmap(os.path.join('images', 'protector_seleccionado.bmp') ,9,11)
wbk.save('Informe_CEP.xls')
os.system('start excel.exe "Informe_CEP.xls"')
def load_gif(self, *args) -> None:
image = Image.open("images/loading.png")
temp = image.copy()
temp.save("Gmap/drone_path.png")
def btn(self):
try:
im = Image.open(self.path) # open selected image
pix = im.load() #load
# Obtaining the RGB matrices
r = []
g = []
b = []
for i in range(im.size[0]):
r.append([]) # [ [] ]
g.append([]) # [ [] ]
b.append([]) # [ [] ]
for j in range(im.size[1]):
rgbPerPixel = pix[i, j]
r[i].append(rgbPerPixel[0]) # add red values
g[i].append(rgbPerPixel[1]) # add green values
b[i].append(rgbPerPixel[2]) # add blue values
m = im.size[0] # width, row
n = im.size[1] # height, column
# Vectors Kr and Kc
alpha = int(self.secr) # checkbox selection
#if low alpha=4, medium alpha=6, high alpha=8
# converted Row&Column into an one-dimensional array
# len(kr) = number of image's rows, len(kc) = number of image's cols
Kr = [randint(0,
pow(2, alpha) - 1)
for i in range(m)] # random int between 0,2^alpha -1
Kc = [randint(0,
pow(2, alpha) - 1) for i in range(n)
] #default alpha=8 -> (0, 256 - 1) for max security
ITER_MAX = 1
#print('Vector Kr : ', Kr)
#print('Vector Kc : ', Kc)
'''
#keep inform about the image in txt for decrypt later
f = open('keys.txt', 'w+')
f.write('Vector Kr : \n')
for a in Kr:
f.write(str(a) + '\n')
f.write('Vector Kc : \n')
for a in Kc:
f.write(str(a) + '\n')
f.write('ITER_MAX : \n')
f.write(str(ITER_MAX) + '\n')
'''
for iterations in range(ITER_MAX):
# For each row
for i in range(m):
rTotalSum = sum(r[i]) # sum all red pixels
gTotalSum = sum(g[i]) # #sum all green pixels
bTotalSum = sum(b[i]) # #sum all blue pixels
rModulus = rTotalSum % 2 # mod(2)
gModulus = gTotalSum % 2 # mod(2)
bModulus = bTotalSum % 2 # mod(2)
if (rModulus == 0): # if divided by 2
# Kr[i] values come first from the last in r array
r[i] = numpy.roll(
r[i], Kr[i]
) #'r' rolling with 'Kr[i]' shift, shifting Kr[i] places
else: # not leaves a remainder of 0
# Kr[i] values go last from the first in r array
r[i] = numpy.roll(
r[i], -Kr[i]) #'r' rolling with ' -Kr[i]' shift
if (gModulus == 0): # leaves a remainder of 0
g[i] = numpy.roll(g[i], Kr[i])
else:
g[i] = numpy.roll(g[i], -Kr[i])
if (bModulus == 0): # mod(2) == 0
b[i] = numpy.roll(b[i], Kr[i])
else:
b[i] = numpy.roll(b[i], -Kr[i])
# For each column
for i in range(n):
rTotalSum = 0
gTotalSum = 0
bTotalSum = 0
for j in range(m):
rTotalSum += r[j][i] #r[row][column]
gTotalSum += g[j][i] #g[row][column]
bTotalSum += b[j][i] #b[row][column]
rModulus = rTotalSum % 2 #mod(2)
gModulus = gTotalSum % 2
bModulus = bTotalSum % 2
# almost doing same things with rows
if (rModulus == 0): #leaves a remainder of 0
upshift(r, i, Kc[i]) #'r' rolling with ' -Kr[i]' shift
else:
downshift(r, i,
Kc[i]) #'r' rolling with ' Kr[i]' shift
if (gModulus == 0): # if divided by 2
upshift(g, i, Kc[i])
else:
downshift(g, i, Kc[i]) # shifting Kr[i] places
if (bModulus == 0):
upshift(b, i, Kc[i]) #'b' rolling with ' -Kr[i]' shift
else:
downshift(b, i, Kc[i])
# For each row
for i in range(m):
for j in range(n):
if (i % 2 == 1): #if not divided by 2
# XOR(^)
r[i][j] = r[i][j] ^ Kc[
j] # rolled(shifted) red values XOR random column values
g[i][j] = g[i][j] ^ Kc[
j] # rolled green values XOR random column values
b[i][j] = b[i][j] ^ Kc[
j] # rolled blue values XOR random column values
else:
# rotate180 means reversed
r[i][j] = r[i][j] ^ rotate180(
Kc[j]) # rotate column values by 180
g[i][j] = g[i][j] ^ rotate180(
Kc[j]) # reversed column values
b[i][j] = b[i][j] ^ rotate180(
Kc[j]
) # rolled blue values XOR reversed rand column values
# For each column
for j in range(n):
for i in range(m):
if (j % 2 == 0):
r[i][j] = r[i][j] ^ Kr[
i] # rolled(shifted) red values XOR random row values
g[i][j] = g[i][j] ^ Kr[
i] # rolled green values XOR random row values
b[i][j] = b[i][j] ^ Kr[
i] # rolled blue values XOR random row values
else:
r[i][j] = r[i][j] ^ rotate180(
Kr[i]
) # rolled red values XOR reversed rand row values
g[i][j] = g[i][j] ^ rotate180(
Kr[i]
) # rolled green values XOR reversed rand row values
b[i][j] = b[i][j] ^ rotate180(
Kr[i]
) # rolled blue values XOR image's reversed rand row values
for i in range(m):
for j in range(n):
pix[i, j] = (r[i][j], g[i][j], b[i][j]) # piece together
encrypted_image_path = 'encrypted_images/' + str(self.tail_name[1])
im.save(encrypted_image_path) # encrypted image
self.encr_image.source = encrypted_image_path # shows encrypted image
except:
pass
def next_image(self, *largs): # whatever = None):
print "Showing next image"
global iCurrentIndex
global iShownLength
if (iCurrentIndex == (iShownLength - 1)) or (iShownLength == 0):
strRandom = random.choice(self.photos)
EventLoop.window.title = str(len(self.photos)) + '/' + str(intCount) + ' Loading:' + strRandom
try:
#comment out the exception to try loading by setting image source
raise Exception("Processing with PIL")
img.source = strRandom
except Exception:
try:
global strCache
global bBuildCache
global strFileName
strCached = ""
strFileName = os.path.basename(strRandom)
if (os.path.isdir(strCache)) and (os.path.isfile(strCache + strFileName)):
strCached = strCache + strFileName
elif (os.path.isdir(strCache)) and (bBuildCache == True):
print "Adding image to cache..."
from PIL import Image
im = Image.open(strRandom)
imgWidth, imgHeight = im.size
bResized = False
#wndWidth, wndHeight =
if imgHeight > sngHeight:
bResized = True
sngChange = sngHeight / imgHeight
imgHeight = int(sngHeight)
imgWidth = int(imgWidth * sngChange)
if imgWidth > sngWidth:
bResized = True
sngChange = sngWidth / imgWidth
imgWidth = int(sngWidth)
imgHeight = int(imgHeight * sngChange)
szNew = imgWidth, imgHeight
#if bResized:
#set to true to save all images to the cache
if True:
im=im.resize(szNew, Image.ANTIALIAS)
if not (strCache == ""):
if not os.path.exists(strCache):
os.makedirs(strCache)
strCached = strCache + os.path.basename(strRandom)
if (not os.path.isfile(strCached)):
try:
im.save(strCached)
except Exception as e:
print "save cache file problem: " + e.message
strCached = ""
else:
print "save cache file found"
#else:
# im.save(strTemp)
if not strCached == "":
#img.source = strCached
try:
self.shown.remove(strCached)
except:
print "error removing image from cache"
self.shown.append(strCached)
iShownLength = len(self.shown)
iCurrentIndex = iShownLength - 1
else:
#img.source = strRandom
try:
self.shown.append(strRandom)
except:
print "error removing image from cache"
self.shown.append(strRandom)
iShownLength = len(self.shown)
iCurrentIndex = iShownLength - 1
#img.reload()
except Exception as e:
print "Error(" + e.message + ") loading image " + strRandom
#continue with the logic
self.photos.remove(strRandom)
if len(self.photos) < 1:
self.photos = glob.glob(strDir + "*.jpg")
#global bReschedule
else:
iCurrentIndex += 1
self.show_current_image()
# Create our spotify object with permissions
spotifyObject = spotipy.Spotify(auth=token)
devices = spotifyObject.devices()
deviceID = devices['devices'][0]['id']
# Current track information
track = spotifyObject.current_user_playing_track()
if track != None:
artist = track['item']['artists'][0]['name']
playing = track['item']['name']
#define image
################################################################################
link = (track['item']['album']['images'][0]['url'])
response = requests.get(link)
img = Image.open(BytesIO(response.content))
img.thumbnail((300, 300))
img.save("img1.jpg")
#Create kivy GUI
################################################################################
class MainWindow(Screen, Widget):
def __init__(self, **kwargs):
super(Screen, self).__init__(**kwargs)
img.load()
self.image = 'img1.jpg'
self.track = playing
self.artist = artist
def on_touch_move(Widget, touch):
volume = int(Widget.value)
