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]))