def go_result(self):
mpp = float(self.txtMPP.text()) # micrometers per pixel
self.data = pycv.evaluate(self.cnts, mpp)
elements = []
if self.chbContours.isChecked():
elements.append(('contour', (255, 255, 255)))
if self.chbFitting.isChecked():
elements.append(('fit', (0, 255, 0)))
if self.chbIndex.isChecked():
elements.append(('index', (255, 255, 255)))
if self.chbAngle.isChecked():
elements.append(('angle', (255, 0, 0)))
self.imres = pycv.draw(self.im1, self.cnts, elements)
pycv.shown([self.imres], True, True, 0, 0,True, 'Resulting Image')
def go_thresholding(self):
self.im1 = self.imoriginal.copy()
self.im2 = self.imisolated.copy()
b = int(self.txtBottom.text())
t = int(self.txtTop.text())
l = int(self.txtLeft.text())
r = int(self.txtRight.text())
self.im1 = pycv.crop(self.im1, b, t, l, r)
self.im2 = pycv.crop(self.im2, b, t, l, r)
self.im2 = pycv.gray(self.im2) # for analysis
self.im1_canvas = self.im1.copy() # original for visual
self.im2_canvas = pycv.rgb(self.im2.copy()) # analysis for visual
fig, axarr, self.thresh_ims = pycv.shown([self.im1_canvas, self.im2_canvas], False, True, AxisVisible=False,
Title='Thresholding')
# Sliders
# Slider Threshold
ax_slid_th = plt.axes([0.1, 0.01, 0.8, 0.02]) # left, bottom, width, height
self.slid_th = Slider(ax_slid_th, 'THRESHOLD', 0, 100, valinit=50)
self.slid_th.on_changed(self.go_thresholding_update)
# Slider GAUSS-BLUR
ax_slid_blurk = plt.axes([0.1, 0.03, 0.8, 0.02])
height, width = pycv.img_size(self.im2)
self.slid_blurk = Slider(ax_slid_blurk, 'BLUR', 1, int(max([height, width]) / 20), valinit=5)
self.slid_blurk.on_changed(self.go_thresholding_update)
self.go_thresholding_update(0)
plt.show()
def imisolated_crop(self):
fig, self.cropax, ims = pycv.shown([self.imisolated], False, True, 0, 0, True, 'CROP ISOLATED IMAGE')
(h, w) = pycv.img_size(self.imisolated)
self.cropax[0].set_xlim([int(self.txtLeft.text()), w - int(self.txtRight.text())])
self.cropax[0].set_ylim([h - int(self.txtBottom.text()), int(self.txtTop.text())])
ax_apply = plt.axes([0.85, 0.05, 0.1, 0.05]) # left, bottom, width, height
btnApply = Button(ax_apply, 'APPLY')
btnApply.on_clicked(self.imisolated_crop_apply)
ax_reset = plt.axes([0.75, 0.05, 0.1, 0.05]) # left, bottom, width, height
btnReset = Button(ax_reset, 'RESET')
btnReset.on_clicked(self.imisolated_crop_reset)
plt.show()
def imisolated_manipulate(self):
try:
imr, img, imb = cv2.split(self.imisolated)
fig, axarr, self.ims = pycv.shown([self.imisolated, imr, img, imb], False, True, AxisVisible=False,
Title='Manipulate Isolated Image')
ax_s_r = plt.axes([0.1, 0.05, 0.8, 0.02]) # left, bottom, width, height
ax_s_g = plt.axes([0.1, 0.03, 0.8, 0.02])
ax_s_b = plt.axes([0.1, 0.01, 0.8, 0.02])
self.slid_r = Slider(ax_s_r, 'RED', 0.0, 3.0, valinit=1)
self.slid_g = Slider(ax_s_g, 'GREEN', 0.0, 3.0, valinit=1)
self.slid_b = Slider(ax_s_b, 'BLUE', 0.0, 3.0, valinit=1)
self.slid_r.on_changed(self.imisolated_manipulate_update)
self.slid_g.on_changed(self.imisolated_manipulate_update)
self.slid_b.on_changed(self.imisolated_manipulate_update)
fig.canvas.mpl_connect('close_event', self.imisolated_manipulate_close)
plt.show()
except:
print('Error while trying to open manipulate window.')
def cal_determine(self):
try:
img = pycv.load(self.txtImgOriginal.text())
fig, axarr, ims = pycv.shown([img], False, True, AxisVisible=True,
Title='MAKE ZOOM RECTANGLE ON SCALE BAR AND CLOSE')
plt.title("Zoom to scale bar and click APPLY. Close the window to abort.")
ax_apply = plt.axes([0.85, 0.05, 0.1, 0.05]) # left, bottom, width, height
btnApply = Button(ax_apply, 'APPLY')
btnApply.on_clicked(self.cal_determine_apply)
plt.show()
if self.determine_apply:
dx = axarr[0].get_xlim()
x1 = int(numpy.ceil(dx[0]))
x2 = int(numpy.ceil(dx[1]))
p = x2 - x1
self.txtPixels.setText(str(p))
self.btnEqual.click()
except Exception as e:
print(e)
self.statusBar.showMessage('Error while loading Master image for pixel calibration!')
def imisolated_show(self):
if self.imisolated is not None:
pycv.shown([self.imisolated], True, False, AxisVisible=False, Title='Isolated Image')
def imoriginal_show(self):
if self.imoriginal is not None:
pycv.shown([self.imoriginal], True, False, AxisVisible=False, Title='Original Image')