problem with notebook: Demo: Denoising of 2D cell images #85
Description
Dear all,
when trying to run the above notebook, cell 5
from csbdeep.data import no_background_patches, norm_percentiles, sample_percentiles
X, Y, XY_axes = create_patches (
raw_data = raw_data,
patch_size = (128,128),
patch_filter = no_background_patches(0),
n_patches_per_image = 2,
save_file = 'data/my_training_data.npz',
)
produces the following error:
0%| | 0/2457 [00:00<?, ?it/s]
ValueError Traceback (most recent call last)
Cell In[8], line 3
1 from csbdeep.data import no_background_patches, norm_percentiles, sample_percentiles
----> 3 X, Y, XY_axes = create_patches (
4 raw_data = raw_data,
5 patch_size = (128,128),
6 patch_filter = no_background_patches(0),
7 n_patches_per_image = 2,
8 save_file = 'data/my_training_data.npz',
9 )
File ~.conda\envs\jupyter_env\Lib\site-packages\csbdeep\data\generate.py:346, in create_patches(raw_data, patch_size, n_patches_per_image, patch_axes, save_file, transforms, patch_filter, normalization, shuffle, verbose)
343 (channel is None or (isinstance(channel,int) and 0<=channel<x.ndim)) or _raise(ValueError())
344 channel is None or patch_size[channel]==x.shape[channel] or _raise(ValueError('extracted patches must contain all channels.'))
--> 346 _Y,_X = sample_patches_from_multiple_stacks((y,x), patch_size, n_patches_per_image, mask, patch_filter)
348 s = slice(i*n_patches_per_image,(i+1)*n_patches_per_image)
349 X[s], Y[s] = normalization(_X,_Y, x,y,mask,channel)
File ~.conda\envs\jupyter_env\Lib\site-packages\csbdeep\data\generate.py:102, in sample_patches_from_multiple_stacks(datas, patch_size, n_samples, datas_mask, patch_filter, verbose)
99 if n_valid == 0:
100 raise ValueError("'patch_filter' didn't return any region to sample from")
--> 102 sample_inds = choice(range(n_valid), n_samples, replace=(n_valid < n_samples))
104 # valid_inds = [v + s.start for s, v in zip(border_slices, valid_inds)] # slow for large n_valid
105 # rand_inds = [v[sample_inds] for v in valid_inds]
106 rand_inds = [v[sample_inds] + s.start for s, v in zip(border_slices, valid_inds)]
File ~.conda\envs\jupyter_env\Lib\site-packages\csbdeep\utils\utils.py:263, in choice(population, k, replace)
260 try:
261 # save state of 'random' and set seed using 'np.random'
262 state = random.getstate()
--> 263 random.seed(np.random.randint(np.iinfo(int).min, np.iinfo(int).max))
264 if replace:
265 # sample with replacement
266 return random.choices(population, k=k)
File numpy\random\mtrand.pyx:796, in numpy.random.mtrand.RandomState.randint()
File numpy\random\_bounded_integers.pyx:2877, in numpy.random._bounded_integers._rand_int32()
ValueError: low is out of bounds for int32
What is wrong???
Thanks and best,
Matthias