waldeland / cnn-for-asi Goto Github PK

Hello Mr Waldeland
Your code is so amazing I want to say

I using CoLab to run the code however I got this error when I try to test my model :

> ####################################################################
> 
> Loading data cube from /content/gdrive/My Drive/cnn_for_ASI/F3/data.segy with:
>   Crosslines:  300 : 1249
>   Inlines:     276 : 476
>   Timeslices:  1 : 462
>  |----------------------------------------------------------------------------------------------------| 0.0%  - h min s left
>  |====================================================================================================| 100.0%  - 0h 0min 5s 
> Interpolating down sampled results to fit input cube
> Finished interpolating
> Writing interpretation to /content/gdrive/My Drive/cnn_for_ASI/F3/salt.segy
> ---------------------------------------------------------------------------
> IndexError                                Traceback (most recent call last)
> <ipython-input-12-d73513020e49> in <module>()
>      65 in_file = join(dataset_name, 'data.segy')
>      66 out_file = join(dataset_name, 'salt.segy')
> ---> 67 writeSEGY(out_file, in_file, classified_cube)
> 
> /content/data.py in writeSEGY(out_filename, in_filename, out_cube)
>      58         # loop through inlines and insert output
>      59         for i in src.ilines:
> ---> 60             iline = out_cube[i-iline_start,:,:]
>      61             src.iline[i] = np.ascontiguousarray(iline.astype(dtype))
>      62 
> 
> IndexError: invalid index to scalar variable.
> 
> ####################################################################

the code was running fine in my local PC but I don't have good GPU so I moved to CoLab, any suggestions to fix that error ???

thank you
Ahmad Bahaa

Hello,

While trying to visualize the Test logs i ran : tensorboard --logdir=log/* (i mean for every possible subfolder) since the tensorboard --outditr=log didn't work.

But even though there are logs in the log/train and the log/test folder tensorboard does not seem to be able to see them! ( i use tensorboard 1.5.1)
Any thoughts?

Thanks in advance

--Dimitris

hello, Sir, sorry to bother you! As follows, I meet a error when runing test.py.
Interpolating down sampled results to fit input cube Traceback (most recent call last): File "test.py", line 64, in <module> classified_cube = interpret( network.classify, data, data_info, 'full', None, im_size, 16, use_gpu=use_gpu) File "/home/leeyang/data/cnn_asi/utils.py", line 123, in interpret class_cube[i] = interpn(pred_points, class_cube[i].astype('float').squeeze(), grid_output_cube, method='linear', fill_value=0, bounds_error=False) File "/home/leeyang/anaconda3/lib/python3.6/site-packages/scipy/interpolate/interpolate.py", line 2648, in interpn return interp(xi) File "/home/leeyang/anaconda3/lib/python3.6/site-packages/scipy/interpolate/interpolate.py", line 2481, in __call__ indices, norm_distances, out_of_bounds = self._find_indices(xi.T) File "/home/leeyang/anaconda3/lib/python3.6/site-packages/scipy/interpolate/interpolate.py", line 2529, in _find_indices norm_distances.append((x - grid[i]) / MemoryError
Have you meet such a problem?

Hello Dr Waldeland,

I have been trying to work through your code on Penobscot interpretation dataset for facies classification. I had a few questions:

1. I need to work with multi-label classification. So, I need to store a single image in train folder with all the classes drawn in that image or I need to store separate image files.
   Thank you in advance 🙂

Line 98 in train.py needs to be changed from

logger.log_scalar('training_loss', var_to_np(loss),i)

to
logger.log_scalar('training_loss', var_to_np(loss).tolist(),i)

Dear ..

Can you comment.. why this error is . with any data
axes don't match the array. ?

Dear Anders,
Could you please explain: what is training data here?
I am a bit confused: here I see that you put one labelled png slice extracted from seismic cube and it corresponds to inline in seismic. So technically we could extract all inlines and predict salt/not salt on them. At the same time, while talk on augmentation on EAGE E-lecture you told that there are geometric transforms that are done on 65 * 65 * 65 seismic cube to increase training data. Finally, what is training data full slice labelled or small cube?
Thank you.

Sincerely,
Kirill

Dear Mr. Anders Waldeland,

Thank you for sharing your work! I am new to using ML and DL for Seismic Interpretation. I want to try your workflow out.
Could you please explain how you managed to extract cross/inlines in form of grayscale images from SEG-Y file?
I donwloaded Penobscot dataset with all cross/inlines and masks, and want to manage my SEG-Y file in the same manner.
I have my dataset from Petrel; there is no such option. I searched the web and have not found solution.
Thank you.

Sincerely,
Kirill

Thank you for sharing your code!

I saw that this is missing a license, if you could please add one, otherwise it is difficult to contribute and build on top of.

Second question: When will the article be released?

Thanks!

We tried to use the code to train a network to identify 3 classes.

To do this using our own image data we modified the class_color_coding dict in data.py to be

# Add colors to this table to make it possible to have more classes
class_color_coding =[
    [0,0,232], #non-gully
    [250,170,30], #gullies
    [207,207,207], #undefined
] 

after doing this the network would not train successfully and an exception occurs. On debugging it appears that the code tries to locate non existent labels with a class_ind > 2

Dear Mr. Waldeland,

I would like to express extreme gratitude for your services in this field.

Can you please tell how to visualize a particular cross line or inline as you have done in your paper?

Your help in this matter would be highly appreciated.

Regards,
Mohammad Farzanullah

Version numbers for requirements are not provided.

Tensorflow-package should at least be 1.14.