class CZI:
def __init__(self, path):
self.filename = path
self.czi = CziFile(path)
def getPixelArray(self):
im = self.czi.asarray()
print('Image Width: {}'.format(im.shape[-1]))
print('Image Height: {}'.format(im.shape[-2]))
return im[0, 0, 0, ]
def cvtStandardImgFormat(self, savePath, fmt, compression=False):
im_arr = self.getPixelArray()
if fmt.endswith('jpg') and im_arr[0] > 65535 and im_arr[1] > 65535:
print('Too Large size for JPEG-2000 format...')
return
elif fmt.endswith('png') and im_arr[0] > 10000 and im_arr[1] > 10000:
print('Too Large size for PNG format...')
return
fname = os.path.basename(self.filename)
sname = os.path.splitext(fname)[-1]
im = Image.new_from_array(im_arr)
if fmt.endswith('tiff'):
if compression:
im.write_to_file(savePath + '/' + sname + '.' + fmt,
compression='lzw')
else:
im.write_to_file(savePath + '/' + sname + '.' + fmt,
compression='lzw')
else:
im.write_to_file(savePath + '/' + sname + '.' + fmt)
def read_czi_image(czi_file, channel_names=None):
from czifile import CziFile
czi_img = CziFile(czi_file)
czi_channels = np.transpose(czi_img.asarray()[0, :, 0, :, :, :, 0],
(0, 2, 3, 1))
voxelsize = {}
for s in czi_img.segments():
if s.SID == "ZISRAWMETADATA":
metadata = s.data().split('\n')
for i, row in enumerate(metadata):
if "Distance Id" in row:
s = metadata[i + 1]
voxelsize[row.split('"')[1]] = np.around(
float(s[s.find('>') + 1:s.find('>') +
s[s.find('>'):].find('<')]) * 1e6,
decimals=3)
voxelsize = tuple([voxelsize[dim] for dim in ['X', 'Y', 'Z']])
n_channels = czi_channels.shape[0]
print czi_file.split('/')[-1], " : ", n_channels, " Channels ", voxelsize
if n_channels > 1:
if channel_names is None:
channel_names = ["CH" + str(i) for i in range(n_channels)]
img = {}
for i_channel, channel_name in enumerate(channel_names):
img[channel_name] = SpatialImage(czi_channels[i_channel],
voxelsize=voxelsize)
else:
img = SpatialImage(czi_channels[0], voxelsize=voxelsize)
return img
#import matplotlib as plt from matplotlib import pylab as pl import urllib.request import os #fn='/home/pwatkins/Downloads/0.08 lead_continuous 150-50-50-03.czi' #fn = '/data/pwatkins/kara/sample_alignment_data_from_Kara_20180125/2017/training-zebrafish-4-sections/' +\ # 'zebrafish_20171013_10-15-10/003_Region3.czi' url = 'https://keeper.mpdl.mpg.de/f/ec98ecaff5674dfea904/?dl=1' fn = 'face.czi' urllib.request.urlretrieve(url, fn) czi = CziFile(fn) #print(czi.metadata, dir(czi.metadata)) iimg = czi.asarray() print(iimg.shape) os.remove(fn) #shape = np.array(iimg.shape[3:5]) #img = np.zeros(shape//10 + 1,dtype=iimg.dtype) # #for scene in range(iimg.shape[1]): # cimg = np.squeeze(iimg[0,scene,0,:,:,0])[0::10,0::10] # sel = (cimg > 0) # img[sel] = cimg[sel] img = np.squeeze(iimg) interp_string = 'nearest'
