import pylab as plt import Registration.registration_new as registration from skimage.exposure import rescale_intensity import Unzipping.unzip as uzip import scipy.io as spio import os dataset_folder = '../../Data/Holly/czifile_test_tiff' out_view_aligned_folder = os.path.join(dataset_folder, 'view_aligned-t') fio.mkdir(out_view_aligned_folder) """ Load dataset and pair up data. """ dataset_files = fio.load_dataset( dataset_folder, ext='.tif', split_key='_', split_position=3) # load in the just aligned files. view_pair_files = fio.pair_views(dataset_files, ext='.tif', split_key='_', split_position=3, view_by=2) """ Do Sift3D registration to align the sequence of paired views. """ processfiles = np.hstack(view_pair_files) reg_config = { 'downsample': 8., # 'lib_path': '../Pipeline/SIFT3D/build/lib/wrappers/matlab/', 'lib_path':
if __name__ == "__main__": import numpy as np import Utility_Functions.file_io as fio import Utility_Functions.stack as stack from skimage.exposure import rescale_intensity import Unzipping.unzip as uzip import time infolder = '../../Data/Holly/czifile_test' outfolder = '../../Data/Holly/czifile_test_tiff' fio.mkdir(outfolder) datasets = fio.load_dataset(infolder, ext='.czi', split_position=3, split_key='_') pad_num = 11 for datafile in datasets[:]: t1 = time.time() im = fio.read_czifile(datafile) im = im[:, ::-1] """ Rescale to uint8 """ im = np.uint8( 255 * rescale_intensity(im * 1.)) # rescale the image intensity n_x, n_y, n_z = im.shape
# """ # Declare similarity registration settings # """ # reg_config_similarity = {'downsample' :4.0, # 'modality' :'multimodal', # 'max_iter':500, # 'type': 'similarity', # 'return_img':0} # # sim_tforms = registration.matlab_register_similarity_batch(dataset_files, out_pre_folder, out_aligned_folder, reg_config_similarity, timer=True, debug=True) #============================================================================== # Registration: Register dataset. (similarity transform - no shear). we try using SIFT. #============================================================================== dataset_files = fio.load_dataset(out_pre_folder, ext='.tif', split_key='TP_', split_position=1) """ Declare similarity registration settings """ # reg_config_similarity = {'downsample' :4.0, # 'modality' :'multimodal', # 'max_iter':500, # 'type': 'similarity'} # mode 2 = sequential registration mode. reg_config = { 'downsample': 4., #8 ant 'lib_path': '/home/felix/Documents/Software/SIFT3D/build/lib/wrappers/matlab', 'mode': 2, 'return_img': 0
#from Unzipping.File2_ed_felix import order_image #from Unzipping.File3_ed_felix import map_max_projection ##from Unzipping.inputdata import load_and_rescale_image import Utility_Functions.file_io as fio import Unzipping.unzip_backup as uzip import numpy as np import pylab as plt from skimage.exposure import rescale_intensity, equalize_adapthist import Geometry.transforms as tf import Registration.registration_new as registration # load in a set of files. dataset_folder = '/media/felix/Elements/Shankar LightSheet/Example Timelapse/test' out_aligned_folder = os.path.join(dataset_folder, 'aligned2') dataset_files = fio.load_dataset( out_aligned_folder, ext='.tif', split_key='TP_', split_position=1) # load in the just aligned files. out_folder = 'test_non-rigid-registered' fio.mkdir(out_folder) from scipy.misc import imsave from tqdm import tqdm import Visualisation.volume_img as vol_img import Geometry.meshtools as meshtools # test the parametrization approach again? o for i in tqdm(range(len(dataset_files))[1:-1]): reg_config = {'alpha': 0.1, 'levels': [8, 4, 2, 1], 'warps': [4, 2, 0, 0]}
import scipy.io as spio import Utility_Functions.stack as stack from scipy.ndimage import zoom #============================================================================== # load in the dataset #============================================================================== dataset_folder1 = '/media/felix/Elements1/Shankar LightSheet/Data/Holly_Test/Volume_Blending/L871_Emb2_a1_registered' dataset_folder2 = '/media/felix/Elements1/Shankar LightSheet/Data/Holly_Test/Volume_Blending/L871_Emb2_a2_registered' ####============================================================================== #### Load data ####============================================================================== # load the files. dataset_files1 = fio.load_dataset(dataset_folder1, ext='.tif', split_position=1) dataset_files2 = fio.load_dataset(dataset_folder2, ext='.tif', split_position=1) join_axis = 0 for i in range(len(dataset_files1))[:1]: vol1 = fio.read_multiimg_PIL(dataset_files1[i]) vol2 = fio.read_multiimg_PIL(dataset_files2[i]) # normal blending com1, com2 = registration.COM_2d(vol1.mean(axis=1), vol2.mean(axis=1)) join_point = int(.5 * (com1[0] + com2[0]))