volume-visualization/imageprocessing/tiffPreparer.py

import os
import re
import glob

import numpy as np

from django.conf import settings

from skimage.io import imread
from skimage.io import ImageCollection
from skimage import img_as_ubyte

from tifffile import TiffFile

import subprocess
import shutil
import tifffile

import logging

logger = logging.getLogger(__name__)


def processTiffFile(filepath):
    # ends with tif* check
    if re.search('.tif(f)?$', filepath) is None:
        raise ValueError('no tif(f) file given, given filename was "%s"' % filepath)

    logger.debug('tiffPreparer: reading file: "%s"' % filepath)
    inputFile = imread(filepath, plugin='tifffile')

    shape = inputFile.shape
    if len(inputFile.shape) is 2:
        tiffFile = TiffFile(filepath)
        if len(tiffFile.series[0].shape) > 2:
            '''
            skimage could not read tifffile properly
            have to do a workaround:
            1. let imagej divide the tifffile into multiple images
            2. let skimage read the multiple images at once
            3. resize shape to fit the original shape

            '''
            concreteFilenameParts = filepath.split('/')
            concreteFilename = concreteFilenameParts[len(concreteFilenameParts) - 1]
            concreteFilename = re.sub('.tif(f)?$', '', concreteFilename)
            print(concreteFilename)
            sequencePath = settings.PATH_TIFF_SEQUENCER + concreteFilename + '/'

            if os.path.exists(sequencePath):
                shutil.rmtree(sequencePath)

            os.mkdir(sequencePath)
            fJCmd = settings.PATH_FIJI + ' --headless -macro /home/fschultze/master/webapp/imagej/tiffSequencer.txt '
            fJCmd += filepath + ':' + sequencePath + concreteFilename + '.tif'
            print(fJCmd)
            returnCode = subprocess.call(fJCmd, shell=True)
            logger.debug('tiffPreparer: returnCode ' + str(returnCode))
            if returnCode != 0:
                raise Exception('please refer to logs')

            collection = ImageCollection(sequencePath + '*.tif')
            images = collection.concatenate()

            if len(tiffFile.series[0].shape) > len(images.shape):
                images = images.reshape(tiffFile.series[0].shape)

            inputFile = images
        else:
            y, x = shape
            inputFile = inputFile.reshape((1, 1, y, x))

    elif len(inputFile.shape) is 3:
        z, y, x = shape
        inputFile = inputFile.reshape((1, z, y, x))

    return inputFile


def imread_convert(f):
    image = imread(f, plugin='tifffile')

    return img_as_ubyte(image)


def prepareImageSequence(path):
    filenames = sorted(glob.glob(os.path.join(path, '*.tif*')))
    z = len(filenames)
    first = tifffile.imread(filenames[0])
    y, x = first.shape
    images = np.empty((z, y, x), dtype=first.dtype)
    images[0, :, :] = first

    for i, filename in enumerate(filenames[1:]):
        images[i, :, :] = tifffile.imread(filename)

    images = images.reshape((1, z, y, x))

    return images