def grayfromIR(self):
ir_filename = os.path.join(os.getcwd(), '..', 'data', self.ircube)
spectral_cube, wavenumbers = read_spimage(ir_filename)
ir_gray = emsc_b(spectral_cube, wavenumbers)
ir_gray_im = ImagePil.fromarray(
min_max_scaler(ir_gray, 0, 255).astype('uint8'))
ir_gray_im = ImagePil.fromarray(
min_max_scaler(standard_scaler(ir_gray), 0, 255).astype('uint8'))
if save == True:
ir_gray_im.save(os.path.join(os.getcwd(), '..', 'data',
'ir_gray.png'),
compress_level=9)
else:
pass
return ir_gray, ir_gray_im
def write_results(self):
img_sitk = blend_images(self.fixed_sitk, self.moving_sitk,
self.final_transform)
PilImage.fromarray(
min_max_scaler(
standard_scaler(sitk.GetArrayViewFromImage(img_sitk)), 0,
255).astype("uint8")).save(self.registration_path)
self.final_transform.WriteTransform(self.transform_path)
def grayfromHandE(self):
he_filename = os.path.join(os.getcwd(), '..', 'data', self.he_image)
he_image = ImagePil.open(he_filename)
he_gray_im = ImagePil.fromarray(
min_max_scaler(he_gray, 0, 255).astype('uint8'))
he_gray_im.save(os.path.join(os.getcwd(), '..', 'data', 'he_gray.png'),
compress_level=9)
return he_gray, he_gray_im
def plot_values(self):
self.metric_values.append(self.registration_method.GetMetricValue())
if (self.registration_method.GetOptimizerIteration() % 10 !=
0) or not self.debug:
return
# Clear the output area (wait=True, to reduce flickering), and plot current data
clear_output(wait=True)
# Plot the similarity metric values
_, (ax1, ax2) = plt.subplots(ncols=2, figsize=(10, 10))
img_sitk = blend_images(self.fixed_sitk, self.moving_sitk,
self.final_transform)
img = min_max_scaler(
standard_scaler(sitk.GetArrayViewFromImage(img_sitk)), 0,
255).astype("uint8")
img = np.asarray(
ImagePil.fromarray(img).resize(
(img.shape[1] / 4, img.shape[0] / 4)))
ax1.imshow(img)
ax2.plot(self.metric_values, "r")
ax2.plot(
self.multires_iterations,
[self.metric_values[index] for index in self.multires_iterations],
"b*",
)
ax2.set_xlabel("Iteration Number", fontsize=12)
ax2.set_ylabel("Metric Value", fontsize=12)
plt.show()
def write(self, filename):
ImagePil.fromarray(min_max_scaler(self.data, 0,
255).astype("uint8")).save(filename)