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)