def read(filename: str) -> Tuple[np.ndarray, czimd.CziMetadata]:
"""Read the pixel data of an CZI image file. Scaling factor
of 1.0 will be used.
:param filename: filename of the CZI to be read
:return: CZI pixel data and the CziMetadata class
"""
# get the CZI metadata
md = czimd.CziMetadata(filename)
# read CZI using aicspylibczi
aicsczi = CziFile(filename)
# in case of a non-mosaic CZI file
if not aicsczi.is_mosaic():
# get all scenes
all_scenes, md = read_nonmosaic(filename=filename)
# in case of a mosaic CZI file
if aicsczi.is_mosaic():
# get all scenes
all_scenes, md = read_mosaic(filename=filename, scale=1.0)
return all_scenes, md
def read_nonmosaic(filename: str) -> Tuple[Union[np.ndarray, None], czimd.CziMetadata]:
"""Read CZI pixel data from non-mosaic image data
:param filename: filename of the CZI file to be read
:return: CZI pixel data and the CziMetadata class
"""
# get the CZI metadata
md = czimd.CziMetadata(filename)
# read CZI using aicspylibczi
aicsczi = CziFile(filename)
if aicsczi.is_mosaic():
# check if this CZIn is really a non-mosaic file
print("CZI is a mosaic file. Please use the readczi_mosaic method instead")
return None, md
# get the shape for the 1st scene
scene = czimd.CziScene(aicsczi, sceneindex=0)
shape_all = scene.shape_single_scene
# only update the shape for the scene if the CZI has an S-Dimension
if scene.hasS:
shape_all[scene.posS] = md.dims.SizeS
print("Shape all Scenes : ", shape_all)
print("DimString all Scenes : ", scene.single_scene_dimstr)
# create an empty array with the correct dimensions
all_scenes = np.empty(aicsczi.size, dtype=md.npdtype)
# loop over scenes if CZI is not a mosaic image
if md.dims.SizeS is None:
sizeS = 1
else:
sizeS = md.dims.SizeS
for s in range(sizeS):
# read the image stack for the current scene
current_scene, shp = aicsczi.read_image(S=s)
# create th index lists containing the slice objects
if scene.hasS:
idl_scene = [slice(None, None, None)] * (len(all_scenes.shape) - 2)
idl_scene[aicsczi.dims.index("S")] = 0
idl_all = [slice(None, None, None)] * (len(all_scenes.shape) - 2)
idl_all[aicsczi.dims.index("S")] = s
# cast current stack into the stack for all scenes
all_scenes[tuple(idl_all)] = current_scene[tuple(idl_scene)]
# if there is no S-Dimension use the stack directly
if not scene.hasS:
all_scenes = current_scene
print("Shape all scenes (no mosaic)", all_scenes.shape)
return all_scenes, md
def read_mosaic(filename: str, scale: float=1.0) -> Tuple[Union[np.ndarray, None], czimd.CziMetadata]:
"""Read the pixel data of an CZI image file with an option scale factor
to read the image with lower resolution and array size
:param filename: filename of the CZI mosaic file to be read
:param scale: scaling factor when reading the mosaic.
:return: CZI pixel data and the updated CziMetadata class
"""
# do not allow scale > 1.0
if scale > 1.0:
print("Scale factor > 1.0 is not recommended. Using scale = 1.0.")
scale = 1.0
# get the CZI metadata
md = czimd.CziMetadata(filename)
# read CZI using aicspylibczi
aicsczi = CziFile(filename)
if not aicsczi.is_mosaic():
# check if this CZI is really a non-mosaic file
print("CZI is not a mosaic file. Please use the read_nonmosaic method instead")
return None, md
# get data for 1st scene and create the required shape for all scenes
scene = czimd.CziScene(aicsczi, sceneindex=0)
shape_all = scene.shape_single_scene
if scene.hasS:
shape_all[scene.posS] = md.dims.SizeS
if not scene.hasS:
num_scenes = 1
print("Shape all Scenes (scale=1.0): ", shape_all)
print("DimString all Scenes : ", scene.single_scene_dimstr)
# create empty array to hold all scenes
all_scenes = np.empty(shape_all, dtype=md.npdtype)
resize_done = False
# loop over scenes if CZI is not Mosaic
for s in range(num_scenes):
scene = czimd.CziScene(aicsczi, sceneindex=s)
# create a slice object for all_scenes array
if not scene.isRGB:
#idl_all = [slice(None, None, None)] * (len(all_scenes.shape) - 2)
idl_all = [slice(None, None, None)] * (len(shape_all) - 2)
if scene.isRGB:
#idl_all = [slice(None, None, None)] * (len(all_scenes.shape) - 3)
idl_all = [slice(None, None, None)] * (len(shape_all) - 3)
# update the entry with the current S index
if not scene.hasS:
idl_all[s] = s
if scene.hasS:
idl_all[scene.posS] = s
# in case T-Z-H dimension are found
if scene.hasT is True and scene.hasZ is True and scene.hasH is True:
# read array for the scene
for h, t, z, c in product(range(scene.sizeH),
range(scene.sizeT),
range(scene.sizeZ),
range(scene.sizeC)):
# read the array for the 1st scene using the ROI
scene_array_htzc = aicsczi.read_mosaic(region=(scene.xstart,
scene.ystart,
scene.width,
scene.height),
scale_factor=scale,
H=h,
T=t,
Z=z,
C=c)
print("Shape Single Scene (Scalefactor: ", scale, ": ", scene_array_htzc.shape)
# check if all_scenes array must be resized due to scaling
if scale < 1.0 and not resize_done:
shape_all[-1] = scene_array_htzc.shape[-1]
shape_all[-2] = scene_array_htzc.shape[-2]
all_scenes = np.resize(all_scenes, shape_all)
# add new entries to metadata
md = adaptmd_scale(md, scene_array_htzc.shape[-1], scene_array_htzc.shape[-2], scale=scale)
resize_done = True
# create slide object for the current mosaic scene
# idl_scene = [slice(None, None, None)] * (len(scene.shape_single_scene) - 2)
idl_all[scene.posS] = s
idl_all[scene.posH] = h
idl_all[scene.posT] = t
idl_all[scene.posZ] = z
idl_all[scene.posC] = c
# cast the current scene into the stack for all scenes
all_scenes[tuple(idl_all)] = scene_array_htzc
# in case T-Z-H dimension are found
if scene.hasT is True and scene.hasZ is True and scene.hasH is False:
# read array for the scene
for t, z, c in product(range(scene.sizeT),
range(scene.sizeZ),
range(scene.sizeC)):
# read the array for the 1st scene using the ROI
scene_array_tzc = aicsczi.read_mosaic(region=(scene.xstart,
scene.ystart,
scene.width,
scene.height),
scale_factor=scale,
T=t,
Z=z,
C=c)
print("Shape Single Scene (Scalefactor: ", scale, ": ", scene_array_tzc.shape)
# check if all_scenes array must be resized due to scaling
if scale < 1.0 and not resize_done:
shape_all[-1] = scene_array_tzc.shape[-1]
shape_all[-2] = scene_array_tzc.shape[-2]
all_scenes = np.resize(all_scenes, shape_all)
# add new entries to metadata
md = adaptmd_scale(md, scene_array_tzc.shape[-1], scene_array_tzc.shape[-2], scale=scale)
resize_done = True
# create slide object for the current mosaic scene
# idl_scene = [slice(None, None, None)] * (len(scene.shape_single_scene) - 2)
idl_all[scene.posS] = s
idl_all[scene.posT] = t
idl_all[scene.posZ] = z
idl_all[scene.posC] = c
# cast the current scene into the stack for all scenes
all_scenes[tuple(idl_all)] = scene_array_tzc
if scene.hasT is False and scene.hasZ is False:
# create an array for the scene
for c in range(scene.sizeC):
scene_array_c = aicsczi.read_mosaic(region=(scene.xstart,
scene.ystart,
scene.width,
scene.height),
scale_factor=scale,
C=c)
print("Shape Single Scene (Scalefactor: ", scale, ": ", scene_array_c.shape)
# check if all_scenes array must be resized due to scaling
if scale < 1.0 and not resize_done:
#new_shape = shape_all
shape_all[-1] = scene_array_c.shape[-1]
shape_all[-2] = scene_array_c.shape[-2]
all_scenes = np.resize(all_scenes, shape_all)
# add new entries to metadata
md = adaptmd_scale(md, scene_array_c.shape[-1], scene_array_c.shape[-2], scale=scale)
resize_done = True
idl_all[scene.posS] = s
idl_all[scene.posC] = c
# cast the current scene into the stack for all scenes
all_scenes[tuple(idl_all)] = scene_array_c
return all_scenes, md
import napari
from czitools import czi_metadata as czimd
from aicsimageio import AICSImage
from utils import misc, napari_tools
filename = r'd:\Testdata_Zeiss\CZI_Testfiles\testwell96.czi'
# get the complete metadata at once as one big class
mdata = czimd.CziMetadata(filename)
# test using AICSImageIO
aics_img = AICSImage(filename)
print(aics_img.shape)
for k, v in aics_img.dims.items():
print(k, v)
# get the stack as dask array
stack = misc.get_daskstack(aics_img)
mdata.dimstring = "S" + aics_img.dims.order
dim_order, dim_index, dim_valid = czimd.CziMetadata.get_dimorder(
mdata.dimstring)
setattr(mdata, "dim_order", dim_order)
setattr(mdata, "dim_index", dim_index)
setattr(mdata, "dim_valid", dim_valid)
# start the napari viewer and show the image
# show array inside napari viewer
viewer = napari.Viewer()
layers = napari_tools.show(viewer,