label_boundaries problem with ndim = label_img.ndim

[Arctic_python]

Hello,
I am trying to label the boundaries of an image that was segmented and labelled. I am doing something wrong because the code below returns

auroura_bound=segmentation.find_boundaries(props,connectivity=1,mode='thick',background=0)
  File "/usr/local/lib/python3.4/dist-packages/skimage/segmentation/boundaries.py", line 148, in find_boundaries
    ndim = label_img.ndim
AttributeError: 'list' object has no attribute 'ndim'

1. label_image=measure.label(g_median_bin, background=0) # g_median_bin is a binary image
2. label_image=label_image+1 # adjusted from -1 to 0
3. props = measure.regionprops(label_image,intensity_image=g_median_bin) # creating a regionprops object
4. label_bound=segmentation.find_boundaries(props,connectivity=1,mode='thick',background=0) # finding boundaries
5. boundaries=segmentation.mark_boundaries(g_median,label_bound)

label_bound=segmentation.find_boundaries(props,connectivity=1,mode='thick',background=0)
  File "/usr/local/lib/python3.4/dist-packages/skimage/segmentation/boundaries.py", line 148, in find_boundaries
    ndim = label_img.ndim
AttributeError: 'list' object has no attribute 'ndim'

I think line 4. is redundant and not required for mark_boundary?!

[Stefan van der Walt]

On 2015-12-01 21:00:16, Arctic_python <ejs...@alaska.edu> wrote:
> ndim = label_img.ndim
> AttributeError: 'list' object has no attribute 'ndim'
>

> 1. label_image=measure.label(g_median_bin, background=0) # g_median_bin
> is a binary image

That does not seem to be true, given the error message.

Stéfan

[Eyal Saiet]

Stefan,

I do not understand what is not true about the label_image object.

bellow is the code, in addition I added a plot of the label_image object.

1. label_image=measure.label(g_median_bin, background=0)
2. label_image +=1
3. plt.figure()
4. plt.imshow(label_image,cmap=plt.cm.gray,interpolation='nearest',origin='lower')
5. plt.title('label_image')
6. plt.show()
7. props = measure.regionprops(label_image,intensity_image=g_median_bin)
8. label_bound=segmentation.find_boundaries(props,connectivity=1,mode='thick',background=0)
9. boundaries=segmentation.mark_boundaries(g_median,label_bound)

--
You received this message because you are subscribed to a topic in the Google Groups "scikit-image" group.
To unsubscribe from this topic, visit https://groups.google.com/d/topic/scikit-image/PwmizxFahYE/unsubscribe.
To unsubscribe from this group and all its topics, send an email to scikit-image...@googlegroups.com.
To post to this group, send an email to scikit...@googlegroups.com.
To view this discussion on the web, visit https://groups.google.com/d/msgid/scikit-image/87zixt8mie.fsf%40berkeley.edu.

For more options, visit https://groups.google.com/d/optout.

--

Eyal Saiet

Project manager

Remote sensing and in-situ measurements

Geophysical Institute 

University of Alaska Fairbanks

Fairbanks, AK 99775

(907) 750 6555 (cell)

ejs...@alaska.edu

[Juan Nunez-Iglesias]

Hi Eyal,

You are passing a list of regionprops (props, in your code) to "find_boundaries", whereas it expects an array: a single image of labeled objects (label_img, in your code).

Juan.

--
You received this message because you are subscribed to the Google Groups "scikit-image" group.
To unsubscribe from this group and stop receiving emails from it, send an email to scikit-image...@googlegroups.com.
To post to this group, send email to scikit...@googlegroups.com.
To view this discussion on the web, visit https://groups.google.com/d/msgid/scikit-image/CA%2BysReAKgzF%3DJXEjz7hti8sz0EBS_Hr%3DPaFWTxN6FV-GtROB0w%40mail.gmail.com.

[Eyal Saiet]

thanks Juan, I have tried that too:

1. label_image=measure.label(g_median_bin, background=0)
2. label_image +=1
3. plt.figure()
4. plt.imshow(label_image,cmap=plt.cm.gray,interpolation='nearest',origin='lower')
5. plt.title('label_image')
6. plt.show()
7. props=measure.regionprops(label_image,intensity_image=g_median_bin)

1. label_bound=segmentation.find_boundaries(label_image,connectivity=1,mode='thick',background=0)
2. boundaries=segmentation.mark_boundaries(g_median,label_bound)

Traceback (most recent call last):
  File attributes_thrash.py", line 127, in <module>
    boundaries=segmentation.mark_boundaries(g_median,label_bound)#,color=(1,0,0), outline_color=None, mode='outer', background_label=0)
  File "/usr/local/lib/python3.4/dist-packages/skimage/segmentation/boundaries.py", line 213, in mark_boundaries
    background=background_label)
  File "/usr/local/lib/python3.4/dist-packages/skimage/segmentation/boundaries.py", line 156, in find_boundaries
    max_label = np.iinfo(label_img.dtype).max
  File "/usr/local/lib/python3.4/dist-packages/numpy/core/getlimits.py", line 254, in __init__
    raise ValueError("Invalid integer data type.")
ValueError: Invalid integer data type.

Process finished with exit code 1

To post to this group, send email to scikit...@googlegroups.com.
To view this discussion on the web, visit https://groups.google.com/d/msgid/scikit-image/CA%2BJHcKT5TijcW_Xa%3DEJt%2Bdi-o_3Hn5PmuHJzXc0YyM44vFr%2BDA%40mail.gmail.com.

For more options, visit https://groups.google.com/d/optout.

[Juan Nunez-Iglesias]

You don't need to find the boundaries manually before calling mark_boundaries. From the docstring of mark_boundaries:

Parameters

----------

image : (M, N[, 3]) array

    Grayscale or RGB image.

label_img : (M, N) array of int

    Label array where regions are marked by different integer values.

Currently, you are passing a boolean array to a function that expects an integer array, which is why it's failing.

In general, it's a good idea to try typing "help(function_name)" when things are failing to make sure that you are passing in the right information to the function you're using! (You can then press "q" to exit help.)

I hope that, erm, helps! =)

Juan.

To view this discussion on the web, visit https://groups.google.com/d/msgid/scikit-image/CA%2BysReD7NpvQdJgNfk_0h9b43wSEJ1TobPG0jf_MsKj6CGxDcg%40mail.gmail.com.