def loadTiffStack(fname,useLibTiff=False): """ Read a TIFF stack. We're using tifflib by default as, right now, only this works when the application is compile on Windows. [17/08/15] Bugs: known to fail with tiffs produced by Icy [23/07/15] """ if not os.path.exists(fname): print "imageStackLoader.loadTiffStack can not find %s" % fname return purePython = True if useLibTiff: from libtiff import TIFFfile import numpy as np tiff = TIFFfile(fname) samples, sample_names = tiff.get_samples() #we should have just one print "Loading:\n" + tiff.get_info() + " with libtiff\n" im = np.asarray(samples[0]) else: print "Loading:\n" + fname + " with tifffile\n" from tifffile import imread im = imread(fname) im=im.swapaxes(1,2) print "read image of size: cols: %d, rows: %d, layers: %d" % (im.shape[1],im.shape[2],im.shape[0]) return im
def load_tiff_stack(fname, use_lib_tiff=False): """ Read a TIFF stack. We're using tifflib by default as, right now, only this works when the application is compile on Windows. [17/08/15] Bugs: known to fail with tiffs produced by Icy [23/07/15] """ if not check_file_exists(fname, "load_tiff_stack"): return if use_lib_tiff: try: from libtiff import TIFFfile except ImportError: # Suppresses error in IDE when libtiff not installed raise tiff = TIFFfile(fname) samples, sample_names = tiff.get_samples() # we should have just one print("Loading: " + tiff.get_info() + " with libtiff\n") im = np.asarray(samples[0]) else: print("Loading: " + fname + " with tifffile\n") from tifffile import imread im = imread(fname) im = im.swapaxes(1, 2) print("read image of size: cols: %d, rows: %d, layers: %d" % (im.shape[1], im.shape[2], im.shape[0])) return im
def read_tif(filename,channel=0): """Read a tif image :Parameters: - `filename` (str) - name of the file to read """ # TIF reader tif = libtiff.TIFF.open(filename) if tif.GetField('ImageDescription'): tif = TIFFfile(filename) arr = tif.get_tiff_array() _data = arr[:].T info_str = tif.get_info() else: i = 1 while not tif.LastDirectory(): i+=1 tif.ReadDirectory() tif.SetDirectory(0) _data = np.zeros((i,)+tif.read_image().shape,dtype=tif.read_image().dtype) for ii,i in enumerate(tif.iter_images()): _data[ii] = i _data = _data.transpose(2, 1, 0) info_str = tif.info() nx, ny, nz = _data.shape # -- prepare metadata dictionnary -- info_dict = dict( filter( lambda x: len(x)==2, (inf.split(':') for inf in info_str.split("\n")) ) ) for k,v in info_dict.iteritems(): info_dict[k] = v.strip() # -- getting the voxelsizes from the tiff image: sometimes # there is a BoundingBox attribute, sometimes there are # XResolution, YResolution, ZResolution or spacing. # the object returned by get_tiff_array has a "get_voxel_sizes()" # method but it fails, so here we go. -- if "BoundingBox" in info_dict: bbox = info_dict["BoundingBox"] xm, xM, ym, yM, zm, zM = map(float,bbox.split()) _vx = (xM-xm)/nx _vy = (yM-ym)/ny _vz = (zM-zm)/nz else: # -- When we have [XYZ]Resolution fields, it describes the # number of voxels per real unit. In SpatialImage we want the # voxelsizes, which is the number of real units per voxels. # So we must invert the result. -- if "XResolution" in info_dict: # --resolution is stored in a [(values, precision)] list-of-one-tuple, or # sometimes as a single number -- xres_str = eval(info_dict["XResolution"]) if isinstance(xres_str, list) and isinstance(xres_str[0], tuple): xres_str = xres_str[0] _vx = float(xres_str[0])/xres_str[1] elif isinstance(xres_str, (int, float)): _vx = float(xres_str) else: _vx = 1. _vx = 1./_vx if _vx != 0 else 1. else: _vx = 1.0 # dumb fallback, maybe we will find something smarter later on if "YResolution" in info_dict: # --resolution is stored in a [(values, precision)] list-of-one-tuple, or # sometimes as a single number -- yres_str = eval(info_dict["YResolution"]) if isinstance(yres_str, list) and isinstance(yres_str[0], tuple): yres_str = yres_str[0] _vy = float(yres_str[0])/yres_str[1] elif isinstance(yres_str, (int, float)): _vy = float(yres_str) else: _vy = 1. _vy = 1./_vy if _vy != 0 else 1. else: _vy = 1.0 # dumb fallback, maybe we will find something smarter later on if "ZResolution" in info_dict: # --resolution is stored in a [(values, precision)] list-of-one-tuple, or # sometimes as a single number -- zres_str = eval(info_dict["ZResolution"]) if isinstance(zres_str, list) and isinstance(zres_str[0], tuple): zres_str = zres_str[0] _vz = float(zres_str[0])/zres_str[1] elif isinstance(zres_str, (int, float)): _vz = float(zres_str) else: _vz = 1. _vz = 1./_vz if _vz != 0 else 1. else: if "spacing" in info_dict: _vz = eval(info_dict["spacing"]) else: _vz = 1.0 # dumb fallback, maybe we will find something smarter later on tif.close() # -- dtypes are not really stored in a compatible way (">u2" instead of uint16) # but we can convert those -- dt = np.dtype(_data.dtype.name) # -- Return a SpatialImage please! -- im = SpatialImage(_data, dtype=dt) im.resolution = _vx,_vy,_vz return im
def read_tif(filename,channel=0): """Read a tif image :Parameters: - `filename` (str) - name of the file to read """ # TIF reader tif = libtiff.TIFF.open(filename) if tif.GetField('ImageDescription'): tif = TIFFfile(filename) arr = tif.get_tiff_array() _data = arr[:].T info_str = tif.get_info() else: i = 1 while not tif.LastDirectory(): i+=1 tif.ReadDirectory() tif.SetDirectory(0) _data = np.zeros((i,)+tif.read_image().shape,dtype=tif.read_image().dtype) for ii,i in enumerate(tif.iter_images()): _data[ii] = i _data = _data.transpose(2, 1, 0) info_str = tif.info() nx, ny, nz = _data.shape # -- prepare metadata dictionnary -- info_dict = dict( filter( lambda x: len(x)==2, (inf.split(':') for inf in info_str.split("\n")) ) ) info_dict.update(dict( filter( lambda x: len(x)==2,(inf.split('=') for inf in info_str.split("\n"))) )) for k,v in info_dict.iteritems(): info_dict[k] = v.strip() info_dict.update({'Filename':filename.split('/')[-1]}) print info_dict # -- getting the voxelsizes from the tiff image: sometimes # there is a BoundingBox attribute, sometimes there are # XResolution, YResolution, ZResolution or spacing. # the object returned by get_tiff_array has a "get_voxel_sizes()" # method but it fails, so here we go. -- if "BoundingBox" in info_dict: bbox = info_dict["BoundingBox"] xm, xM, ym, yM, zm, zM = map(float,bbox.split()) _vx = (xM-xm)/nx _vy = (yM-ym)/ny _vz = (zM-zm)/nz else: # -- When we have [XYZ]Resolution fields, it describes the # number of voxels per real unit. In SpatialImage we want the # voxelsizes, which is the number of real units per voxels. # So we must invert the result. -- if "XResolution" in info_dict: # --resolution is stored in a [(values, precision)] list-of-one-tuple, or # sometimes as a single number -- xres_str = eval(info_dict["XResolution"]) if isinstance(xres_str, list) and isinstance(xres_str[0], tuple): xres_str = xres_str[0] _vx = float(xres_str[0])/xres_str[1] elif isinstance(xres_str, (int, float)): _vx = float(xres_str) else: _vx = 1. _vx = 1./_vx if _vx != 0 else 1. else: _vx = 1.0 # dumb fallback, maybe we will find something smarter later on if "YResolution" in info_dict: # --resolution is stored in a [(values, precision)] list-of-one-tuple, or # sometimes as a single number -- yres_str = eval(info_dict["YResolution"]) if isinstance(yres_str, list) and isinstance(yres_str[0], tuple): yres_str = yres_str[0] _vy = float(yres_str[0])/yres_str[1] elif isinstance(yres_str, (int, float)): _vy = float(yres_str) else: _vy = 1. _vy = 1./_vy if _vy != 0 else 1. else: _vy = 1.0 # dumb fallback, maybe we will find something smarter later on if "ZResolution" in info_dict: # --resolution is stored in a [(values, precision)] list-of-one-tuple, or # sometimes as a single number -- zres_str = eval(info_dict["ZResolution"]) if isinstance(zres_str, list) and isinstance(zres_str[0], tuple): zres_str = zres_str[0] _vz = float(zres_str[0])/zres_str[1] elif isinstance(zres_str, (int, float)): _vz = float(zres_str) else: _vz = 1. _vz = 1./_vz if _vz != 0 else 1. else: if "spacing" in info_dict: _vz = eval(info_dict["spacing"]) else: _vz = 1.0 # dumb fallback, maybe we will find something smarter later on tif.close() # -- dtypes are not really stored in a compatible way (">u2" instead of uint16) # but we can convert those -- dt = np.dtype(_data.dtype.name) # -- Return a SpatialImage please! -- im = SpatialImage(_data, dtype=dt) im.resolution = _vx,_vy,_vz im.info = info_dict return im