class SimpleExample1(BaseWidget):
def __init__(self):
super(SimpleExample1, self).__init__("FaceGate")
# self.visible = True
self.set_margin(300)
self.formset = [('_firstname', '_middlename', '_lastname'), '_button',
'_fullname', ' _image', ' ']
# self.formset = [ {
# 'Tab1':['_firstname','||','_middlename','||','_lastname'],
# 'Tab2': ['_fullname']
# },
# '=',(' ','_button', ' ') ]
#Use dictionaries for tabs
#Use the sign '=' for a vertical splitter
#Use the signs '||' for a horizontal splitter
#Definition of the forms fields
self._firstname = ControlText('First name', 'Default value')
self._middlename = ControlText('Middle name')
self._lastname = ControlText('Lastname name')
self._fullname = ControlText('Full name')
self._button = ControlButton('Press this button')
self._image = ControlImage()
self.run()
# #Define the button action
# self._button.value = self.__buttonAction
# def __buttonAction(self):
# """Button action event"""
# self._fullname.value = self._firstname.value +" "+ self._middlename.value + \
# " "+ self._lastname.value
def run(self):
self._image.value = 'numbered.jpg'
self._image.repaint()
class TomographGUI(BaseWidget):
def __init__(self):
super(TomographGUI,self).__init__('TomographGUI')
self.formset = [('_file','_loadButton'),
'_det_nr', '_angl_spread',
'_angl_it', '_filter_size',
('_image', '_sinogram', '_output'), '_startButton',]
#Definition of the forms fields
self._file = ControlFile()
self._loadButton = ControlButton('Load')
self._det_nr = ControlText('Detectors number')
self._angl_spread = ControlText('Angular spread')
self._angl_it = ControlText('Angluar step')
self._filter_size = ControlText('Filter size')
self._image = ControlImage()
self._sinogram = ControlImage()
self._output = ControlImage()
self._startButton = ControlButton('Start')
self._loadButton.value = self.__load
self._startButton.value = self.__start
def __load(self):
if (self._file.value):
self._image.value = cv2.imread(self._file.value, cv2.IMREAD_GRAYSCALE);
self._image.repaint()
def __normalize(self, image):
min = np.min(image)
max = np.max(image)
normalized = (image - min) / (max - min)
return normalized
def __start(self):
if (self._image.value is None):
return False
det_nr = int(self._det_nr.value)
ang_spread = int(self._angl_spread.value)
it_ang = int(self._angl_it.value)
filter_size = int(self._filter_size.value)
image = cv2.imread(self._file.value, cv2.IMREAD_GRAYSCALE)
radon = Radon(image, det_nr, ang_spread, it_ang, filter_size)
radon.transform()
sinogram = radon.getSinogram()
self._sinogram.value = self.__normalize(sinogram)
self._sinogram.repaint()
radon.transform(inverse=True)
result = radon.getResult()
self._output.value = self.__normalize(result)
self._output.repaint()