def run():
global appMainForm, appImagesForm
app = QtGui.QApplication(sys.argv)
appMainForm = MainWindow()
appImagesForm = ImagesSelectionForm()
appMainForm.show()
sys.exit(app.exec_())
def main():
try:
qApp = QtWidgets.QApplication(sys.argv)
aw = MainWindow()
sys.exit(qApp.exec_())
except Exception as err:
Error_handel().write(err, region='gui')
sys.exit()
"""
Entry point for application.
You may run this without a GUI by passing in the absolute path to the Template document and the Variables workbook
as command line arguments.
"""
import sys
from PyQt5.QtWidgets import QApplication
from gui.gui import MainWindow
from automation.automate import Automate
if __name__ == '__main__':
if sys.argv[1:]:
if len(sys.argv[1:]) != 2:
print('To run this without a GUI, please supply the absolute paths to the Template and Variables files '
'enclosed in quotes. For example: ')
print(r'python main.py "C:\path\to\template.docx" "C:\path\to\variables.xls"')
else:
template_file, vars_file = sys.argv[1], sys.argv[2]
automation = Automate(in_gui=False)
automation.run(template_file, vars_file)
else:
app = QApplication(sys.argv)
main = MainWindow()
main.show()
sys.exit(app.exec_())
'''
Created on Jan 13, 2014
@author: Eugene Syriani
@version: 0.2.5
This is the main BiBler module.
Execute this module from the command line to start the application.
@note: It assumes that the L{app} package has a L{statechart.BiBler_Statechart} class
and a L{UserInterface.UserInterface} class that implements L{gui.app_interface.IApplication}.
G{packagetree app, gui, utils}
'''
import wx
from gui.gui import MainWindow
from gui.controller import Controller
from app.statechart import BiBler_Statechart
from app.UserInterface import UserInterface
if __name__ == '__main__':
app = wx.App(False)
controller = Controller()
controller.bindGUI(MainWindow(controller))
controller.bindSC(BiBler_Statechart())
controller.bindApp(UserInterface())
controller.start()
app.MainLoop()
nn = NeuralNetwork()
nn.train_model()
elif start_argument == 'test':
nn = NeuralNetwork(load_existing_data=True)
# nn.test_accuracy()
nn.test_accuracy_custom()
elif start_argument == 'predict':
nn = NeuralNetwork(load_existing_data=True)
print('Ввод текстов активен (CTRL + C для выхода)')
try:
while True:
text = input('> ')
prediction = nn.predict(text)
print(f'{prediction[0]} [{prediction[1]}]')
except (KeyboardInterrupt, SystemExit):
print('До свидания!')
else:
raise InvalidStartParameter
exit(0)
app = QtWidgets.QApplication(argv)
main_window = MainWindow()
main_window.show()
exit(app.exec_())
from PyQt5 import QtGui
import qdarkstyle
import signal
signal.signal(signal.SIGINT, signal.SIG_DFL)
if __name__ == '__main__':
cfg = config.load(sys.argv[1])
try:
img_path=sys.argv[2]
except IndexError:
img_path=None
jdrc= comm.init(cfg, 'ColorTuner')
cameraCli = jdrc.getCameraClient("ColorTuner.Camera")
camera = CameraFilter(cameraCli)
app = QApplication(sys.argv)
frame = MainWindow(img_path)
frame.setCamera(camera)
frame.show()
app.setStyleSheet(qdarkstyle.load_stylesheet_pyqt5())
t2 = ThreadGUI(frame)
t2.daemon=True
t2.start()
sys.exit(app.exec_())
import sys
from gui.gui import MainWindow, Run
if __name__ == "__main__":
mainWindow = MainWindow()
sys.exit(Run(sys.argv, mainWindow))
from sensors.cameraFilter import CameraFilter
from gui.gui import MainWindow
from PyQt5.QtWidgets import QApplication
from PyQt5 import QtGui
import qdarkstyle
import signal
signal.signal(signal.SIGINT, signal.SIG_DFL)
if __name__ == '__main__':
cfg = config.load(sys.argv[1])
#starting comm
jdrc = comm.init(cfg, 'ColorTuner')
cameraCli = jdrc.getCameraClient("ColorTuner.Camera")
camera = CameraFilter(cameraCli)
app = QApplication(sys.argv)
frame = MainWindow()
frame.setCamera(camera)
frame.show()
app.setStyleSheet(qdarkstyle.load_stylesheet_pyqt5())
t2 = ThreadGUI(frame)
t2.daemon = True
t2.start()
sys.exit(app.exec_())
def main():
import sys
app = QApplication(sys.argv)
w = MainWindow()
sys.exit(app.exec_())
