def __houghLineTransformSlot(self):
# 如果当前不是二值图像 则直接返回
if not isBinaryImage(self.__imgList[-1]):
MessageDialog(self, '需要先在「分割」菜单中进行二值化')
return
newImg, flag = houghLineTransform(self.__imgList[-1])
if flag:
self.__appendImg(newImg)
else:
MessageDialog(self, '未检测到直线')
def __orbFeatureDetectionSlot(self):
# 如果当前不是灰度图 则直接返回
if not self.__imgList[-1].ndim == 2:
MessageDialog(self, '需要先在「基本」菜单中进行灰度化')
return
self.__appendImg(orbFeatureDetection(self.__imgList[-1]))
def __contourTracingSlot(self):
# 如果当前不是二值图像 则直接返回
if not isBinaryImage(self.__imgList[-1]):
MessageDialog(self, '需要先在「分割」菜单中进行二值化')
return
self.__appendImg(contourTracing(self.__imgList[-1]))
def __morphologyPreviewSlot(self):
# 如果当前不是二值图像 则直接返回
if not isBinaryImage(self.__imgList[-1]):
MessageDialog(self, '需要先在「分割」菜单中进行二值化')
self.ui.hs_morphology_radius.setValue(0)
return
if self.ui.radio_morphology_shape_rect.isChecked():
shape = 'rect'
elif self.ui.radio_morphology_shape_circle.isChecked():
shape = 'circle'
else:
shape = 'cross'
radius = self.ui.hs_morphology_radius.value()
if self.ui.radio_morphology_type_dilate.isChecked():
self.__previewImgDict['morphology'] = dilateOperation(
self.__imgList[-1], shape, radius)
elif self.ui.radio_morphology_type_erode.isChecked():
self.__previewImgDict['morphology'] = erodeOperation(
self.__imgList[-1], shape, radius)
elif self.ui.radio_morphology_type_open.isChecked():
self.__previewImgDict['morphology'] = openOperation(
self.__imgList[-1], shape, radius)
else:
self.__previewImgDict['morphology'] = closeOperation(
self.__imgList[-1], shape, radius)
self.__viewer.changeImage(self.__previewImgDict['morphology'])
def __otsuThresholdBtnSlot(self):
# 如果当前不是灰度图 则直接返回
if not self.__imgList[-1].ndim == 2:
MessageDialog(self, '需要先在「基本」菜单中进行灰度化')
return
self.__appendImg(otsuThresholdSegmentation(self.__imgList[-1]))
def __histogramEqualizationBtnSlot(self):
# 如果当前不是灰度图 则直接返回
if not self.__imgList[-1].ndim == 2:
MessageDialog(self, '需要先进行灰度化')
return
self.__appendImg(histogramEqualization(self.__imgList[-1]))
def __toGrayImageBtnSlot(self):
# 如果已经是灰度图 则直接返回
if self.__imgList[-1].ndim == 2:
MessageDialog(self, '当前已经是灰度图像')
return
self.__appendImg(cv.cvtColor(self.__imgList[-1], cv.COLOR_BGR2GRAY))
def _OnFind(self, event):
start, end = self.DoFind(event.GetFindString())
if start == -1:
msg = MessageDialog(self,
'Find/Replace',
'Cannot find "' + event.GetFindString() + '"',
icon='information')
msg.ShowModal()
else:
self.fSetSelection(start, end)
def __fixedThresholdPreviewSlot(self, threshold):
# 如果当前不是灰度图 则直接返回
if not self.__imgList[-1].ndim == 2:
MessageDialog(self, '需要先在「基本」菜单中进行灰度化')
self.ui.hs_fixed_threshold.setValue(127)
return
self.__previewImgDict['fixedThreshold'] = fixedThresholdSegmentation(
self.__imgList[-1], threshold)
self.__viewer.changeImage(self.__previewImgDict['fixedThreshold'])
self.__fixedThresholdActiveFlag = True # 置为激活状态
def __laplacianEdgeDetectionBtnSlot(self):
# 如果当前不是灰度图 则直接返回
if not self.__imgList[-1].ndim == 2:
MessageDialog(self, '需要先在「基本」菜单中进行灰度化')
return
if self.ui.radio_laplacian_edge_detection_type_4.isChecked():
neighbourhood = 4
else:
neighbourhood = 8
self.__appendImg(
laplacianEdgeDetection(self.__imgList[-1], neighbourhood))
def __cannyEdgePreviewSlot(self):
# 如果当前不是灰度图 则直接返回
if not self.__imgList[-1].ndim == 2:
MessageDialog(self, '需要先在「基本」菜单中进行灰度化')
self.ui.hs_canny_low_threshold.setValue(100)
self.ui.hs_canny_high_threshold.setValue(200)
return
lowThreshold = self.ui.hs_canny_low_threshold.value()
highThreshold = self.ui.hs_canny_high_threshold.value()
self.__previewImgDict['cannyEdge'] = cannyEdgeDetection(
self.__imgList[-1], lowThreshold, highThreshold)
self.__viewer.changeImage(self.__previewImgDict['cannyEdge'])
self.__cannyEdgeActiveFlag = True # 置为激活状态
def __sobelEdgeDetectionBtnSlot(self):
# 如果当前不是灰度图 则直接返回
if not self.__imgList[-1].ndim == 2:
MessageDialog(self, '需要先在「基本」菜单中进行灰度化')
return
if self.ui.radio_sobel_edge_detection_axis_x.isChecked():
axis = 'x'
else:
axis = 'y'
if self.ui.radio_sobel_edge_detection_radius_1.isChecked():
radius = 1
elif self.ui.radio_sobel_edge_detection_radius_2.isChecked():
radius = 2
else:
radius = 3
self.__appendImg(sobelEdgeDetection(self.__imgList[-1], axis, radius))
def __adaptiveThresholdPreviewSlot(self):
# 如果当前不是灰度图 则直接返回
if not self.__imgList[-1].ndim == 2:
MessageDialog(self, '需要先在「基本」菜单中进行灰度化')
self.ui.hs_adaptive_threshold_radius.setValue(0)
self.ui.hs_adaptive_threshold_offset.setValue(0)
return
if self.ui.radio_adaptive_threshold_type_average.isChecked():
method = 'mean'
else:
method = 'gaussian'
radius = self.ui.hs_adaptive_threshold_radius.value()
offset = self.ui.hs_adaptive_threshold_offset.value()
if radius == 0:
self.__previewImgDict['adaptiveThreshold'] = self.__imgList[-1]
else:
self.__previewImgDict[
'adaptiveThreshold'] = adaptiveThresholdSegmentation(
self.__imgList[-1], method, radius, offset)
self.__viewer.changeImage(self.__previewImgDict['adaptiveThreshold'])
