[BUG] brainreg-napari rescale fails when stack opened using "Open files as stack" #184
Description
Describe the bug
Opening an image stack with "Open files as stack" and then running brainreg in napari on the stack fails with trace below
--> 446 run_niftyreg(
registration_output_folder = PosixPath('/home/alessandro')
paths = <brainreg.core.paths.Paths object at 0x7de5b8ded630>
atlas = allen mouse atlas (res. 25um)
target_brain = <class 'numpy.ndarray'> (510, 396, 310) float64
n_processes = 18
additional_images_downsample = {'section_001_01': '/media/alessandro/T7/brainglobe-course-data/MS_cx_left/stitchedImages_100/2/section_001_01.tif'}
data_orientation = 'psl'
atlas.metadata["orientation"] = 'asr'
atlas.metadata = {'name': 'allen_mouse', 'citation': 'Wang et al 2020, https://doi.org/10.1016/j.cell.2020.04.007', 'atlas_link': 'http://www.brain-map.org', 'species': 'Mus musculus', 'symmetric': True, 'resolution': [25.0, 25.0, 25.0], 'orientation': 'asr', 'version': '1.2', 'shape': [528, 320, 456], 'trasform_to_bg': [[1.0, 0.0, 0.0, 0.0], [0.0, 1.0, 0.0, 0.0], [0.0, 0.0, 1.0, 0.0], [0.0, 0.0, 0.0, 1.0]], 'additional_references': []}
niftyreg_args = NiftyregArgs(affine_n_steps=6, affine_use_n_steps=5, freeform_n_steps=6, freeform_use_n_steps=4, bending_energy_weight=0.95, grid_spacing=-10, smoothing_sigma_reference=-1, smoothing_sigma_floating=-1.0, histogram_n_bins_floating=128.0, histogram_n_bins_reference=128.0, debug=False)
PRE_PROCESSING_ARGS = None
scaling = [0.2, 0.08, 0.08]
load_parallel = True
sort_input_file = False
n_free_cpus = 2
save_original_orientation = False
brain_geometry = <geometry_keys.Full brain: 'full'>
447 registration_output_folder,
448 paths,
449 atlas,
450 target_brain,
451 n_processes,
452 additional_images_downsample,
453 data_orientation,
454 atlas.metadata["orientation"],
455 niftyreg_args,
456 PRE_PROCESSING_ARGS,
457 scaling,
458 load_parallel,
459 sort_input_file,
460 n_free_cpus,
461 save_original_orientation=save_original_orientation,
462 brain_geometry=brain_geometry.value,
463 )
465 logging.info("Calculating volumes of each brain area")
466 calculate_volumes(
467 atlas,
468 paths.registered_atlas,
(...)
473 right_hemisphere_value=2,
474 )
File ~/dev/brainreg/brainreg/core/backend/niftyreg/run.py:202, in run_niftyreg(***failed resolving arguments***)
196 tmp_downsampled_brain_standard_path = os.path.join(
197 niftyreg_paths.niftyreg_directory,
198 f"downsampled_standard_{name_to_save}.nii",
199 )
201 # do the tiff part at the beginning
--> 202 downsampled_brain = load_any(
filename = '/media/alessandro/T7/brainglobe-course-data/MS_cx_left/stitchedImages_100/2/section_001_01.tif'
scaling[1] = 0.08
scaling = [0.2, 0.08, 0.08]
scaling[2] = 0.08
scaling[0] = 0.2
load_parallel = True
sort_input_file = False
n_free_cpus = 2
203 filename,
204 scaling[1],
205 scaling[2],
206 scaling[0],
207 load_parallel=load_parallel,
208 sort_input_file=sort_input_file,
209 n_free_cpus=n_free_cpus,
210 )
212 downsampled_brain = bg.map_stack_to(
213 DATA_ORIENTATION, ATLAS_ORIENTATION, downsampled_brain
214 ).astype(np.uint16, copy=False)
216 save_nii(
217 downsampled_brain, atlas.resolution, tmp_downsampled_brain_path
218 )
File ~/mambaforge/envs/brainreg/lib/python3.10/site-packages/brainglobe_utils/image_io/load.py:94, in load_any(src_path='/media/alessandro/T7/brainglobe-course-data/MS_cx_left/stitchedImages_100/2/section_001_01.tif', x_scaling_factor=0.08, y_scaling_factor=0.08, z_scaling_factor=0.2, anti_aliasing=True, load_parallel=True, sort_input_file=False, as_numpy=False, n_free_cpus=2)
92 elif src_path.endswith((".tif", ".tiff")):
93 logging.debug("Data type is: tif stack")
---> 94 img = load_img_stack(
src_path = '/media/alessandro/T7/brainglobe-course-data/MS_cx_left/stitchedImages_100/2/section_001_01.tif'
x_scaling_factor = 0.08
y_scaling_factor = 0.08
z_scaling_factor = 0.2
anti_aliasing = True
95 src_path,
96 x_scaling_factor,
97 y_scaling_factor,
98 z_scaling_factor,
99 anti_aliasing=anti_aliasing,
100 )
101 elif src_path.endswith(".nrrd"):
102 logging.debug("Data type is: nrrd")
File ~/mambaforge/envs/brainreg/lib/python3.10/site-packages/brainglobe_utils/image_io/load.py:163, in load_img_stack(stack_path='/media/alessandro/T7/brainglobe-course-data/MS_cx_left/stitchedImages_100/2/section_001_01.tif', x_scaling_factor=0.08, y_scaling_factor=0.08, z_scaling_factor=0.2, anti_aliasing=True)
160 logging.debug("Downsampling stack in X/Y")
161 for plane in tqdm(range(0, len(stack))):
162 downsampled_stack.append(
--> 163 transform.rescale(
downsampled_stack = []
transform = <module 'skimage.transform' from '/home/alessandro/mambaforge/envs/brainreg/lib/python3.10/site-packages/skimage/transform/__init__.py'>
stack = <class 'numpy.ndarray'> (4949, 3873) uint16
plane = 0
x_scaling_factor = 0.08
y_scaling_factor = 0.08
(y_scaling_factor, x_scaling_factor) = (0.08, 0.08)
anti_aliasing = True
164 stack[plane],
165 (y_scaling_factor, x_scaling_factor),
166 mode="constant",
167 preserve_range=True,
168 anti_aliasing=anti_aliasing,
169 )
170 )
172 logging.debug("Converting downsampled stack to array")
173 stack = np.array(downsampled_stack)
File ~/mambaforge/envs/brainreg/lib/python3.10/site-packages/skimage/_shared/utils.py:316, in channel_as_last_axis.__call__.<locals>.fixed_func(*args=(<class 'numpy.ndarray'> (3873,) uint16, (0.08, 0.08)), **kwargs={'anti_aliasing': True, 'mode': 'constant', 'preserve_range': True})
313 channel_axis = kwargs.get('channel_axis', None)
315 if channel_axis is None:
--> 316 return func(*args, **kwargs)
func = <function rescale at 0x7de5a7cdeef0>
args = (<class 'numpy.ndarray'> (3873,) uint16, (0.08, 0.08))
kwargs = {'mode': 'constant', 'preserve_range': True, 'anti_aliasing': True}
318 # TODO: convert scalars to a tuple in anticipation of eventually
319 # supporting a tuple of channel axes. Right now, only an
320 # integer or a single-element tuple is supported, though.
321 if np.isscalar(channel_axis):
File ~/mambaforge/envs/brainreg/lib/python3.10/site-packages/skimage/transform/_warps.py:280, in rescale(image=<class 'numpy.ndarray'> (3873,) uint16, scale=<class 'numpy.ndarray'> (2,) float64, order=None, mode='constant', cval=0, clip=True, preserve_range=True, anti_aliasing=True, anti_aliasing_sigma=None, channel_axis=None)
277 if len(scale) > 1:
278 if ((not multichannel and len(scale) != image.ndim) or
279 (multichannel and len(scale) != image.ndim - 1)):
--> 280 raise ValueError("Supply a single scale, or one value per spatial "
281 "axis")
282 if multichannel:
283 scale = np.concatenate((scale, [1]))But brainreg runs fine if you use Open Folder instead.
To Reproduce
- Open
napariwithbrainreg-napariinstalled - Run
Open files as stackand select all files in a folder - Run brainreg
Expected behaviour
Brainreg should work irrespective of how the image stack was opened.
Log file
n/a
Screenshots
n/a
Computer used (please complete the following information):
Platform: Linux-6.5.0-25-generic-x86_64-with-glibc2.35
System: Ubuntu 22.04.4 LTS
Python: 3.10.13 | packaged by conda-forge | (main, Dec 23 2023, 15:36:39) [GCC 12.3.0]
Qt: 5.15.2
PyQt5: 5.15.10
NumPy: 1.26.4
SciPy: 1.12.0
Dask: 2024.3.0
VisPy: 0.14.1
magicgui: 0.8.2
superqt: 0.6.2
in-n-out: 0.1.9
app-model: 0.2.4
npe2: 0.7.4
OpenGL:
- GL version: 4.6.0 NVIDIA 535.161.07
- MAX_TEXTURE_SIZE: 32768
Screens:
- screen 1: resolution 3440x1440, scale 1.0
Settings path:
- /home/alessandro/.config/napari/brainreg_fae7ff8a72d2d6e4cddefe1455346cfd57814491/settings.yaml
Plugins:
- brainglobe-napari-io: 0.3.4 (10 contributions)
- brainglobe-segmentation: 1.2.3 (2 contributions)
- brainreg: 1.0.7.dev1+g31e2111 (4 contributions)
- napari: 0.4.19.post1 (77 contributions)
- napari-console: 0.0.9 (0 contributions)
- napari-svg: 0.1.10 (2 contributions)
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