def __init__(self,
preprocessing: Optional[Union[ImagePreproParams,
Dict]] = None):
if preprocessing:
if isinstance(preprocessing, ImagePreproParams):
self._preprocessing = preprocessing
elif isinstance(preprocessing, dict):
self._preprocessing = ImagePreproParams(**preprocessing)
else:
self._preprocessing = ImagePreproParams()
def test_sitk_backend(
disk_im_gry,
disk_im_mch_notile,
disk_im_rgb,
):
im_gry = sitk_backend(str(disk_im_gry),
preprocessing=ImagePreproParams(image_type="FL"))
# im_mch = sitk_backend(str(disk_im_mch_notile), preprocessing={"image_type":"FL"})
im_rgb = sitk_backend(str(disk_im_rgb),
preprocessing=ImagePreproParams(image_type="BF"))
assert im_gry.GetSize() == (2048, 2048)
# assert im_mch.GetSize() == (2048,2048,3)
assert im_rgb.GetSize() == (2048, 2048)
def test_czi_read_mc_std_preprocess():
image_fp = os.path.join(PRIVATE_DIR, "czi_4ch_16bit.czi")
preprocessing = ImagePreproParams()
ri = reg_image_loader(image_fp, 1, preprocessing=preprocessing)
ri.read_reg_image()
assert ri.reg_image.GetNumberOfComponentsPerPixel() == 1
assert ri.reg_image.GetPixelID() == 1
def check_cache_preprocessing(self, output_dir: Union[str, Path],
image_tag: str):
"""
Parameters
----------
output_dir: path
Where cached data is on disk
image_tag:
Tag of the image modality
Returns
-------
prepro_flag: bool
Whether a preprocessed version of the image exists in the cache.
"""
(
out_image_fp,
out_params_fp,
out_mask_fp,
_,
_,
) = self._get_all_cache_data_fps(output_dir, image_tag)
if out_image_fp.exists() and out_params_fp.exists():
cached_preprocessing = ImagePreproParams.parse_file(out_params_fp)
return self.preprocessing == cached_preprocessing
else:
return False
def preprocess_reg_image_intensity(
self, image: sitk.Image,
preprocessing: ImagePreproParams) -> sitk.Image:
"""
Preprocess image intensity data to single channel image.
Parameters
----------
image: sitk.Image
reg_image to be preprocessed
preprocessing: ImagePreproParams
Parameters of the preprocessing
Returns
-------
image: sitk.Image
Preprocessed single-channel image
"""
if preprocessing.image_type.value == "FL":
preprocessing.invert_intensity = False
elif preprocessing.image_type.value == "BF":
preprocessing.max_int_proj = False
preprocessing.contrast_enhance = False
if self.is_rgb:
preprocessing.invert_intensity = True
if preprocessing.max_int_proj:
image = sitk_max_int_proj(image)
if preprocessing.contrast_enhance:
image = contrast_enhance(image)
if preprocessing.invert_intensity:
image = sitk_inv_int(image)
if preprocessing.custom_processing:
for k, v in preprocessing.custom_processing.items():
print(f"performing preprocessing: {k}")
image = v(image)
image.SetSpacing((self.image_res, self.image_res))
return image
def test_wsireg2d_add_modality_w_np(data_out_dir, im_mch_np):
wsi_reg = WsiReg2D(gen_project_name_str(), str(data_out_dir))
wsi_reg.add_modality(
"test_mod",
im_mch_np,
0.65,
channel_names=["test"],
channel_colors=["red"],
)
assert np.array_equal(
wsi_reg.modalities.get("test_mod").get("image_filepath"), im_mch_np)
assert wsi_reg.modalities.get("test_mod").get("image_res") == 0.65
assert wsi_reg.modalities.get("test_mod").get("channel_names") == ["test"]
assert wsi_reg.modalities.get("test_mod").get("channel_colors") == ["red"]
assert (wsi_reg.modalities.get("test_mod").get("preprocessing") ==
ImagePreproParams())
assert wsi_reg.modalities.get("test_mod").get("mask") == None
assert wsi_reg.n_modalities == 1
def load_from_cache(self, output_dir: Union[str, Path], image_tag: str):
"""
Read in preprocessed data from the cache folder.
Parameters
----------
output_dir: path
Where cached data is on disk
image_tag:
Tag of the image modality
Returns
-------
from_cache_flag: bool
Whether data was read from cache
"""
(
image_fp,
params_fp,
mask_fp,
init_tform_fp,
osize_tform_fp,
) = self._get_all_cache_data_fps(output_dir, image_tag)
read_from_cache = self.check_cache_preprocessing(output_dir, image_tag)
if read_from_cache:
self._reg_image = sitk.ReadImage(str(image_fp))
self._preprocessing = ImagePreproParams(
**json.load(open(params_fp, "r")))
self.pre_reg_transforms = json.load(open(init_tform_fp, "r"))
if osize_tform_fp.exists():
self.original_size_transform = json.load(
open(osize_tform_fp, "r"))
if mask_fp.exists():
self._mask = sitk.ReadImage(str(mask_fp))
return True
else:
return False
def test_tifffile_dask_backend(
disk_im_gry_pyr,
disk_im_mch_pyr,
disk_im_rgb_pyr,
disk_im_gry,
disk_im_mch,
disk_im_rgb,
):
im_gry_pyr = tifffile_dask_backend(
disk_im_gry_pyr,
largest_series=0,
preprocessing=ImagePreproParams(image_type="FL"),
)
im_mch_pyr = tifffile_dask_backend(
disk_im_mch_pyr,
largest_series=0,
preprocessing=ImagePreproParams(image_type="FL"),
)
im_rgb_pyr = tifffile_dask_backend(
disk_im_rgb_pyr,
largest_series=0,
preprocessing=ImagePreproParams(image_type="BF"),
)
im_gry = tifffile_dask_backend(
disk_im_gry,
largest_series=0,
preprocessing=ImagePreproParams(image_type="FL"),
)
im_mch = tifffile_dask_backend(
disk_im_mch,
largest_series=0,
preprocessing=ImagePreproParams(image_type="FL"),
)
im_rgb = tifffile_dask_backend(
disk_im_rgb,
largest_series=0,
preprocessing=ImagePreproParams(image_type="BF"),
)
assert im_gry_pyr.GetSize() == (2048, 2048)
assert im_mch_pyr.GetSize() == (2048, 2048, 3)
assert im_rgb_pyr.GetSize() == (2048, 2048)
assert im_gry.GetSize() == (2048, 2048)
assert im_mch.GetSize() == (2048, 2048, 3)
assert im_rgb.GetSize() == (2048, 2048)
def test_czi_read_rgb_bf_preprocess_default():
image_fp = os.path.join(PRIVATE_DIR, "czi_rgb.czi")
preprocessing = ImagePreproParams()
ri = reg_image_loader(image_fp, 1, preprocessing=preprocessing)
ri.read_reg_image()
assert ri.reg_image.GetNumberOfComponentsPerPixel() == 1
def preprocess_reg_image_spatial(
self,
image: sitk.Image,
preprocessing: ImagePreproParams,
imported_transforms=None,
) -> Tuple[sitk.Image, List[Dict]]:
"""
Spatial preprocessing of the reg_image.
Parameters
----------
image: sitk.Image
reg_image to be preprocessed
preprocessing: ImagePreproParams
Spatial preprocessing parameters
imported_transforms:
Not implemented yet..
Returns
-------
image: sitk.Image
Spatially preprcessed image ready for registration
transforms: list of transforms
List of pre-initial transformations
"""
transforms = []
original_size = image.GetSize()
if preprocessing.downsampling > 1:
print("performing downsampling by factor: {}".format(
preprocessing.downsampling))
image.SetSpacing((self.image_res, self.image_res))
image = sitk.Shrink(
image,
(preprocessing.downsampling, preprocessing.downsampling),
)
if self._mask is not None:
self._mask.SetSpacing((self.image_res, self.image_res))
self._mask = sitk.Shrink(
self._mask,
(
preprocessing.downsampling,
preprocessing.downsampling,
),
)
image_res = image.GetSpacing()[0]
else:
image_res = self.image_res
if float(preprocessing.rot_cc) != 0.0:
print(f"rotating counter-clockwise {preprocessing.rot_cc}")
rot_tform = gen_rigid_tform_rot(image, image_res,
preprocessing.rot_cc)
(
composite_transform,
_,
final_tform,
) = prepare_wsireg_transform_data({"initial": [rot_tform]})
image = transform_plane(image, final_tform, composite_transform)
if self._mask is not None:
self._mask.SetSpacing((image_res, image_res))
self._mask = transform_plane(self._mask, final_tform,
composite_transform)
transforms.append(rot_tform)
if preprocessing.flip:
print(f"flipping image {preprocessing.flip.value}")
flip_tform = gen_aff_tform_flip(image, image_res,
preprocessing.flip.value)
(
composite_transform,
_,
final_tform,
) = prepare_wsireg_transform_data({"initial": [flip_tform]})
image = transform_plane(image, final_tform, composite_transform)
if self._mask is not None:
self._mask.SetSpacing((image_res, image_res))
self._mask = transform_plane(self._mask, final_tform,
composite_transform)
transforms.append(flip_tform)
if self._mask and preprocessing.crop_to_mask_bbox:
print("computing mask bounding box")
if preprocessing.mask_bbox is None:
mask_bbox = compute_mask_to_bbox(self._mask)
preprocessing.mask_bbox = mask_bbox
if preprocessing.mask_bbox:
print("cropping to mask")
translation_transform = gen_rigid_translation(
image,
image_res,
preprocessing.mask_bbox.X,
preprocessing.mask_bbox.Y,
preprocessing.mask_bbox.WIDTH,
preprocessing.mask_bbox.HEIGHT,
)
(
composite_transform,
_,
final_tform,
) = prepare_wsireg_transform_data(
{"initial": [translation_transform]})
image = transform_plane(image, final_tform, composite_transform)
self.original_size_transform = gen_rig_to_original(
original_size, deepcopy(translation_transform))
if self._mask is not None:
self._mask.SetSpacing((image_res, image_res))
self._mask = transform_plane(self._mask, final_tform,
composite_transform)
transforms.append(translation_transform)
return image, transforms
def test_read_preprocess_array():
da_arr = ensure_dask_array(np.zeros((128, 128, 3), dtype=np.uint8))
mc_arr = ensure_dask_array(np.zeros((3, 128, 128), dtype=np.uint8))
gr_arr = ensure_dask_array(np.zeros((128, 128), dtype=np.uint8))
std_rgb = read_preprocess_array(
da_arr,
preprocessing=ImagePreproParams(image_type="BF"),
force_rgb=None,
)
nonstd_rgb = read_preprocess_array(
mc_arr,
preprocessing=ImagePreproParams(image_type="BF"),
force_rgb=True,
)
all_ch_mc = read_preprocess_array(
mc_arr, preprocessing=ImagePreproParams(image_type="FL"))
ch0_ch_mc = read_preprocess_array(
mc_arr, preprocessing=ImagePreproParams(ch_indices=[0]))
ch01_ch_mc = read_preprocess_array(
mc_arr, preprocessing=ImagePreproParams(ch_indices=[0, 1]))
ch12_ch_mc = read_preprocess_array(
mc_arr, preprocessing=ImagePreproParams(ch_indices=[1, 2]))
ch02_ch_mc = read_preprocess_array(
mc_arr, preprocessing=ImagePreproParams(ch_indices=[0, 2]))
ch1_ch_mc = read_preprocess_array(
mc_arr, preprocessing=ImagePreproParams(ch_indices=[1]))
ch2_ch_mc = read_preprocess_array(
mc_arr, preprocessing=ImagePreproParams(ch_indices=[2]))
std_gr = read_preprocess_array(gr_arr, ImagePreproParams(image_type="FL"))
chsel0_gr = read_preprocess_array(
gr_arr, preprocessing=ImagePreproParams(ch_indices=[0]))
chsel01_gr = read_preprocess_array(
gr_arr, preprocessing=ImagePreproParams(ch_indices=[0, 1]))
assert std_rgb.GetNumberOfComponentsPerPixel() == 1
assert nonstd_rgb.GetNumberOfComponentsPerPixel() == 1
assert all_ch_mc.GetDepth() == 3
assert ch0_ch_mc.GetDepth() == 0
assert ch01_ch_mc.GetDepth() == 2
assert ch12_ch_mc.GetDepth() == 2
assert ch02_ch_mc.GetDepth() == 2
assert ch1_ch_mc.GetDepth() == 0
assert ch2_ch_mc.GetDepth() == 0
assert std_gr.GetDepth() == 0
assert chsel0_gr.GetDepth() == 0
assert chsel01_gr.GetDepth() == 0
assert std_rgb.GetSize() == (128, 128)
assert nonstd_rgb.GetSize() == (128, 128)
assert all_ch_mc.GetSize() == (128, 128, 3)
assert ch0_ch_mc.GetSize() == (128, 128)
assert ch01_ch_mc.GetSize() == (128, 128, 2)
assert ch12_ch_mc.GetSize() == (128, 128, 2)
assert ch02_ch_mc.GetSize() == (128, 128, 2)
assert ch1_ch_mc.GetSize() == (128, 128)
assert ch2_ch_mc.GetSize() == (128, 128)
assert std_gr.GetSize() == (128, 128)
assert chsel0_gr.GetSize() == (128, 128)
assert chsel01_gr.GetSize() == (128, 128)