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Nan to num #1

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Nan to num #1

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7facb16
add nan_to_num before cast
seanmcculloch Dec 6, 2024
d05e458
chunked interest points
seanmcculloch Dec 11, 2024
d4a0676
Merge branch 'chunked_blob_detection' into nan_to_num
seanmcculloch Dec 11, 2024
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7 changes: 5 additions & 2 deletions bigstream/features.py
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Original file line number Diff line number Diff line change
@@ -1,6 +1,8 @@
import numpy as np
from fishspot.filter import white_tophat, apply_foreground_mask

# from fishspot.detect import detect_spots_log

from scipy.stats.mstats import winsorize

import numpy as np
Expand Down Expand Up @@ -43,9 +45,11 @@ def detect_spots_log(
#return blob_log(image, **kwargs)
return chunked_blob_log(image, **kwargs)


import numpy as np
from skimage.feature import blob_log


def chunked_blob_log(image, **kwargs): #sigma_list, chunk_size=(128, 128, 128), overlap=(32, 32, 32)):
chunk_size=(256, 256, 256)
overlap=(64, 64, 64)
Expand Down Expand Up @@ -91,8 +95,7 @@ def blob_detection(
max_blob_radius : scalar float
The largest size blob you want to find in voxel units
**kwargs : any additional kwargs
Passed to fishspot.detect_spots_log

Passed to fishspot.detect_spots_log∂
Returns
-------
blob_coordinates_and_intensities : nd-array Nx4
Expand Down
2 changes: 1 addition & 1 deletion bigstream/transform.py
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Expand Up @@ -125,7 +125,7 @@ def apply_transform(

# execute, return as numpy array
resampled = resampler.Execute(mov)
return sitk.GetArrayViewFromImage(resampled).astype(dtype)
return np.nan_to_num(sitk.GetArrayViewFromImage(resampled),nan=0.0,posinf=0.0,neginf=0.0).astype(dtype)


def apply_transform_to_coordinates(
Expand Down