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sgoldenlab / simba

SimBA (Simple Behavioral Analysis), a pipeline and GUI for developing supervised behavioral classifiers
https://simba-uw-tf-dev.readthedocs.io/
GNU General Public License v3.0
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Duplication of animal from SLEAP .slp or .csv file #155

Open catubc opened 2 years ago

catubc commented 2 years ago

Describe the bug Hello I am trying to label behavior for an mp4 video and I don't see the video panel showing up as in the simba instructions. Is this normal? There is an attribute error in the dataframe, not clear where the error could be coming from, perhaps tkinter?

Thanks so much

Ubuntu 18.04, conda tkinter version: tk 8.6.10 hbc83047_0 anaconda

simba1

[Edit: ] I think I might be missing the .csv generation step.

catubc commented 2 years ago

Ok, so it seems that I had to manually move the .csv files to get past this step. I had assumed simba would extract the .csv data from the .slp file and populate.

But I'm still getting an error due to the naming of the animals. 

(simba3) cat@cat-Precision-T3610:~$ simba
Exception in Tkinter callback
Traceback (most recent call last):
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/tkinter/__init__.py", line 1705, in __call__
    return self.func(*args)
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/simba/SimBA.py", line 3924, in <lambda>
    button_labelaggression = Button(label_labelaggression, text='Select video (create new video annotation)',command= lambda:choose_folder(self.projectconfigini))
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/simba/labelling_aggression.py", line 364, in choose_folder
    MainInterface()
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/simba/labelling_aggression.py", line 178, in __init__
    load_frame(0, self.window, self.fbox, )
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/simba/labelling_aggression.py", line 441, in load_frame
    currAnimal = currDf.loc[currDf.index[current_frame_number], [currXheader, currYheader]]
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/pandas/core/indexing.py", line 1418, in __getitem__
    return self._getitem_tuple(key)
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/pandas/core/indexing.py", line 805, in _getitem_tuple
    return self._getitem_lowerdim(tup)
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/pandas/core/indexing.py", line 961, in _getitem_lowerdim
    return getattr(section, self.name)[new_key]
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/pandas/core/indexing.py", line 1424, in __getitem__
    return self._getitem_axis(maybe_callable, axis=axis)
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/pandas/core/indexing.py", line 1839, in _getitem_axis
    return self._getitem_iterable(key, axis=axis)
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/pandas/core/indexing.py", line 1133, in _getitem_iterable
    keyarr, indexer = self._get_listlike_indexer(key, axis, raise_missing=False)
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/pandas/core/indexing.py", line 1092, in _get_listlike_indexer
    keyarr, indexer, o._get_axis_number(axis), raise_missing=raise_missing
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/pandas/core/indexing.py", line 1177, in _validate_read_indexer
    key=key, axis=self.obj._get_axis_name(axis)
KeyError: "None of [Index(['female_nose_1_2_x', 'female_nose_1_2_y'], dtype='object')] are in the [index]"

And here's the top of the .csv:


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5,49
sronilsson commented 2 years ago

Hi @catubc! The labelling interface looks in project_folder/csv/features_extracted for a CSV (or parquet, depending on your settings) and a matching video file. It looks like there aren't any files in the folder, I can see that the feature extraction step failed: Extracting features from 0 files. This suggests that the step before this, the outlier correction, might not have been completed - I recommend you click on the red skip outlier correction button the the [Outlier correction] tab. This should give you files to generate features for. The printouts in your screenshot suggests the video is fine.

Just a note, I can see the readthedocs documentation. I have not written that and do not maintain and haven't read it, I don't think anyone in the lab is developing or maintaining those docs. I recommend the github mds' for the docs https://github.com/sgoldenlab/simba#scenario-tutorials

sronilsson commented 2 years ago

@catubc - do all of your animals have the same body-parts tracked? Did you manually move them from input_csv to features_extracted folder?

catubc commented 2 years ago

Ok, I started over from scratch with a new project. This time I didnot move any .csv files anywhere. And yes, all the animals have 6 points along the spine labeled. However, there is occlusion at times and SLEAP does not return labels for some cases. I assume this would be ok, or at least if I ran the interpolation step.

I can now get to outlier correction, not sure. It's still a similar crash. 


Warning: The video name could not be found in the .SLP meta-data table
SimBA therefore gives the imported CSV the same name as the SLP file.
To be sure that SimBAs slp import function works, make sure the .SLP file and the associated video file has the same file name - e.g., "Video1.mp4" and "Video1.slp" before importing the videos and SLP files to SimBA.
Re-organizing pose data-frame based on user-assigned identities: 2020_08_01_11_27_15_857870_compressed_corrected.mp4....
Interpolating missing values (Method: Body-parts: Nearest) ...
Please select the project_config.ini file
/media/cat/256GB/dan/simba/cohorts/gerbils2/project_folder/project_config.ini
Table updated.
/media/cat/256GB/dan/simba/cohorts/gerbils2/project_folder/logs generated.
/media/cat/256GB/dan/simba/cohorts/gerbils2/project_folder/logs generated.
Outlier correction settings updated in project_config.ini
Number of Frames: 28802
/media/cat/256GB/dan/simba/cohorts/gerbils2/project_folder/csv/features_extracted/2020_08_01_11_27_15_857870_compressed_corrected.csv @@@@@@@@@@@@@
The CSV file could not be located at the following path: /media/cat/256GB/dan/simba/cohorts/gerbils2/project_folder/csv/features_extracted/2020_08_01_11_27_15_857870_compressed_corrected.csv . It may be that you missed a step in the analysis. Please generate the file before proceeding.
None
Applying settings for multi-animal tracking...

And here's the command line:

(simba3) cat@cat-Precision-T3610:~$ simba
Exception in Tkinter callback
Traceback (most recent call last):
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/tkinter/__init__.py", line 1705, in __call__
    return self.func(*args)
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/simba/SimBA.py", line 3924, in <lambda>
    button_labelaggression = Button(label_labelaggression, text='Select video (create new video annotation)',command= lambda:choose_folder(self.projectconfigini))
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/simba/labelling_aggression.py", line 364, in choose_folder
    MainInterface()
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/simba/labelling_aggression.py", line 178, in __init__
    load_frame(0, self.window, self.fbox, )
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/simba/labelling_aggression.py", line 441, in load_frame
    currAnimal = currDf.loc[currDf.index[current_frame_number], [currXheader, currYheader]]
AttributeError: 'NoneType' object has no attribute 'loc'
catubc commented 2 years ago

I went back and ran feature-extraction also.

(simba3) cat@cat-Precision-T3610:~$ simba
Exception in Tkinter callback
Traceback (most recent call last):
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/tkinter/__init__.py", line 1705, in __call__
    return self.func(*args)
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/simba/SimBA.py", line 3924, in <lambda>
    button_labelaggression = Button(label_labelaggression, text='Select video (create new video annotation)',command= lambda:choose_folder(self.projectconfigini))
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/simba/labelling_aggression.py", line 364, in choose_folder
    MainInterface()
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/simba/labelling_aggression.py", line 178, in __init__
    load_frame(0, self.window, self.fbox, )
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/simba/labelling_aggression.py", line 441, in load_frame
    currAnimal = currDf.loc[currDf.index[current_frame_number], [currXheader, currYheader]]
AttributeError: 'NoneType' object has no attribute 'loc'

feat

catubc commented 2 years ago

I'm also getting this error, I think during outlierCorrection (or even if I try to skip it).


Exception in Tkinter callback
Traceback (most recent call last):
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/tkinter/__init__.py", line 1705, in __call__
    return self.func(*args)
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/simba/SimBA.py", line 3895, in <lambda>
    button_skipOC = Button(label_outliercorrection,text='Skip outlier correction (CAUTION)',fg='red', command=lambda:skip_outlier_c(self.projectconfigini))
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/simba/outlier_scripts/skip_outlierCorrection.py", line 61, in skip_outlier_c
    csv_df.columns = newHeaders
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/pandas/core/generic.py", line 5192, in __setattr__
    return object.__setattr__(self, name, value)
  File "pandas/_libs/properties.pyx", line 67, in pandas._libs.properties.AxisProperty.__set__
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/pandas/core/generic.py", line 690, in _set_axis
    self._data.set_axis(axis, labels)
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/pandas/core/internals/managers.py", line 183, in set_axis
    "values have {new} elements".format(old=old_len, new=new_len)
ValueError: Length mismatch: Expected axis has 126 elements, new values have 108 elements

[Edit:] Perhaps I'm not getting past the outlier correction. Maybe due to missing values in the data where SLEAP did not find any features?

catubc commented 2 years ago

Actually, I think the interpolation step is failing well before I get to these steps.

Is there some other preprocessing step that I have to do on the .slp file? Perhaps Talmo has code to fix the .slp files before loading into simba?

inteprolation .

sronilsson commented 2 years ago

Hi @catubc - I think most or all errors, could originate from the body part configuration that you specified SimBA to use in your project - we have 6 animals each with 6 body-parts each having 3 values (x,y,p) (663=108). SimBA, however, assumes that there should be 126 columns, which means that there is either an extra body-part for each animal, or an extra animal.

When you click skip outlier correction, SimBA takes the imported pose-estimation files, and without performing any outlier correction, just modifies the headings to make it compatible with the rest of the functions down-stream, and make similar regardless of the pose-estimation tool it comes from (sleap, dlc, animal tracker etc..) It is here SimBA tries to fit 126 headers to a 108-field file and this is the reason you see the error. When you specified the body-parts, is it possible you added an animal too many or a body-part too many?

When you define the body-parts, the data is saved in a CSV at project_folder/logs/measures/body_parts_configuration/body_configurations.csv (or something very similar, I can't remember exact). You could open this file in your project and check for any odd ones that should not be there?

catubc commented 2 years ago

Thanks for that, so there's clearly something weird going on. Perhaps I used 0-based indices in simba somewhere?

In any case, I'm certain there aren't additional animals or features, here's the sleap file and the nodes and track info, there are only 6 animals (female, male, pup1-4) and 6 features (nose, spine1-5).

(sleap) cat@cat-Precision-T7610:~/data/simba$ python
Python 3.6.13 |Anaconda, Inc.| (default, Jun  4 2021, 14:25:59) 
[GCC 7.5.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import sleap
s2021-12-20 12:27:22.061021: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1
l>>> sleap.load_file(2020_08_01_11_27_15_857870_compressed_corrected.mp4.predictions.slp')
Labels(labeled_frames=28802, videos=1, skeletons=1, tracks=6)
>>> labels = sleap.load_file('2020_08_01_11_27_15_857870_compressed_corrected.mp4.predictions.slp')
>>> labels.nodes
[Node(name='spine5', weight=1.0), Node(name='spine2', weight=1.0), Node(name='spine4', weight=1.0), Node(name='nose', weight=1.0), Node(name='spine3', weight=1.0), Node(name='spine1', weight=1.0)]
>>> labels.tracks
[Track(spawned_on=0, name='female'), Track(spawned_on=0, name='male'), Track(spawned_on=0, name='pup1'), Track(spawned_on=0, name='pup2'), Track(spawned_on=0, name='pup3'), Track(spawned_on=0, name='pup4')]
>>>
catubc commented 2 years ago

Here's the make simba config step make_simba_config

catubc commented 2 years ago

And here's the import sleap step import_sleap

catubc commented 2 years ago

And here's the confirmation that simba only sees 6 animals and 6 features animals

catubc commented 2 years ago

The error occurs right after I press "c" at this step. Screenshot from 2021-12-20 18-45-33

catubc commented 2 years ago

And this error reoccurs at outlier detection again. Screenshot from 2021-12-20 18-51-21

Screenshot from 2021-12-20 18-51-31

sronilsson commented 2 years ago

Yeah your tracking data looks solid. It also looks good after you have imported into SimBA, as in your screenshot from the project_folder/csv/input_csv example a while back. It is the next step, after import, when you click skip outlier correction where SimBA tries to apply the the headers that you specify the user_defined configuration on your files we get the error and I think I know why.. I'm not sure you are going to like me for this solution.. :) but bear in mind it is designed to accommodate people who have an unequal and different body-parts tracked on different animals. In the # bodyparts entry box you set 36, not 6. And you create a table looking like this (excuse me, I dont have SimBA installed on where I am and had to draw it in a spreadsheet: image

If this is too much of a pain, we could modify the project_folder/logs/measures/body_parts_configuration/body_configurations.csv files directly.

catubc commented 2 years ago

Well, I did the first option you suggested, but I get the exact same error Screenshot from 2021-12-20 19-06-03 .

catubc commented 2 years ago

Screenshot from 2021-12-20 19-07-49

catubc commented 2 years ago

Screenshot from 2021-12-20 19-12-58

catubc commented 2 years ago

Re: option #2, this file doesn't exist

...project_folder/logs/measures/body_parts_configuration/body_configurations.csv files directly.

In the logs subdirectories there's only 1 file project_bp_names.csv:


female_nose_1_2
female_spine1_1_2
female_spine2_1_2
female_spine3_1_2
female_spine4_1_2
female_spine5_1_2
male_nose_2
male_spine1_2
male_spine2_2
male_spine3_2
male_spine4_2
male_spine5_2
pup1_nose_3
pup1_spine1_3
pup1_spine2_3
pup1_spine3_3
pup1_spine4_3
pup1_spine5_3
pup2_nose_4
pup2_spine1_4
pup2_spine2_4
pup2_spine3_4
pup2_spine4_4
pup2_spine5_4
pup3_nose_5
pup3_spine1_5
pup3_spine2_5
pup3_spine3_5
pup3_spine4_5
pup3_spine5_5
pup4_nose_6
pup4_spine1_6
pup4_spine2_6
pup4_spine3_6
pup4_spine4_6
pup4_spine5_6
catubc commented 2 years ago

So one weird thing appears to be that the sleap .csv files inthe root directory and in the input_CSV have different number of headings

Here's the one from the project_folder/csv/input_csv:

scorer,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi
bodypart,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi,SLEAP_multi
coords,female_nose_x,female_nose_y,female_nose_p,female_spine1_x,female_spine1_y,female_spine1_p,female_spine2_x,female_spine2_y,female_spine2_p,female_spine3_x,female_spine3_y,female_spine3_p,female_spine4_x,female_spine4_y,female_spine4_p,female_spine5_x,female_spine5_y,female_spine5_p,female_nose_x,female_nose_y,female_nose_p,female_spine1_x,female_spine1_y,female_spine1_p,female_spine2_x,female_spine2_y,female_spine2_p,female_spine3_x,female_spine3_y,female_spine3_p,female_spine4_x,female_spine4_y,female_spine4_p,female_spine5_x,female_spine5_y,female_spine5_p,male_nose_x,male_nose_y,male_nose_p,male_spine1_x,male_spine1_y,male_spine1_p,male_spine2_x,male_spine2_y,male_spine2_p,male_spine3_x,male_spine3_y,male_spine3_p,male_spine4_x,male_spine4_y,male_spine4_p,male_spine5_x,male_spine5_y,male_spine5_p,pup1_nose_x,pup1_nose_y,pup1_nose_p,pup1_spine1_x,pup1_spine1_y,pup1_spine1_p,pup1_spine2_x,pup1_spine2_y,pup1_spine2_p,pup1_spine3_x,pup1_spine3_y,pup1_spine3_p,pup1_spine4_x,pup1_spine4_y,pup1_spine4_p,pup1_spine5_x,pup1_spine5_y,pup1_spine5_p,pup2_nose_x,pup2_nose_y,pup2_nose_p,pup2_spine1_x,pup2_spine1_y,pup2_spine1_p,pup2_spine2_x,pup2_spine2_y,pup2_spine2_p,pup2_spine3_x,pup2_spine3_y,pup2_spine3_p,pup2_spine4_x,pup2_spine4_y,pup2_spine4_p,pup2_spine5_x,pup2_spine5_y,pup2_spine5_p,pup3_nose_x,pup3_nose_y,pup3_nose_p,pup3_spine1_x,pup3_spine1_y,pup3_spine1_p,pup3_spine2_x,pup3_spine2_y,pup3_spine2_p,pup3_spine3_x,pup3_spine3_y,pup3_spine3_p,pup3_spine4_x,pup3_spine4_y,pup3_spine4_p,pup3_spine5_x,pup3_spine5_y,pup3_spine5_p,pup4_nose_x,pup4_nose_y,pup4_nose_p,pup4_spine1_x,pup4_spine1_y,pup4_spine1_p,pup4_spine2_x,pup4_spine2_y,pup4_spine2_p,pup4_spine3_x,pup4_spine3_y,pup4_spine3_p,pup4_spine4_x,pup4_spine4_y,pup4_spine4_p,pup4_spine5_x,pup4_spine5_y,pup4_spine5_p
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...
catubc commented 2 years ago

And here's the one in the root directory where the .slp file is:

,Animal_1_nose_x,Animal_1_nose_y,Animal_1_nose_p,Animal_1_spine1_x,Animal_1_spine1_y,Animal_1_spine1_p,Animal_1_spine2_x,Animal_1_spine2_y,Animal_1_spine2_p,Animal_1_spine3_x,Animal_1_spine3_y,Animal_1_spine3_p,Animal_1_spine4_x,Animal_1_spine4_y,Animal_1_spine4_p,Animal_1_spine5_x,Animal_1_spine5_y,Animal_1_spine5_p,Animal_2_nose_x,Animal_2_nose_y,Animal_2_nose_p,Animal_2_spine1_x,Animal_2_spine1_y,Animal_2_spine1_p,Animal_2_spine2_x,Animal_2_spine2_y,Animal_2_spine2_p,Animal_2_spine3_x,Animal_2_spine3_y,Animal_2_spine3_p,Animal_2_spine4_x,Animal_2_spine4_y,Animal_2_spine4_p,Animal_2_spine5_x,Animal_2_spine5_y,Animal_2_spine5_p,Animal_3_nose_x,Animal_3_nose_y,Animal_3_nose_p,Animal_3_spine1_x,Animal_3_spine1_y,Animal_3_spine1_p,Animal_3_spine2_x,Animal_3_spine2_y,Animal_3_spine2_p,Animal_3_spine3_x,Animal_3_spine3_y,Animal_3_spine3_p,Animal_3_spine4_x,Animal_3_spine4_y,Animal_3_spine4_p,Animal_3_spine5_x,Animal_3_spine5_y,Animal_3_spine5_p,Animal_4_nose_x,Animal_4_nose_y,Animal_4_nose_p,Animal_4_spine1_x,Animal_4_spine1_y,Animal_4_spine1_p,Animal_4_spine2_x,Animal_4_spine2_y,Animal_4_spine2_p,Animal_4_spine3_x,Animal_4_spine3_y,Animal_4_spine3_p,Animal_4_spine4_x,Animal_4_spine4_y,Animal_4_spine4_p,Animal_4_spine5_x,Animal_4_spine5_y,Animal_4_spine5_p,Animal_5_nose_x,Animal_5_nose_y,Animal_5_nose_p,Animal_5_spine1_x,Animal_5_spine1_y,Animal_5_spine1_p,Animal_5_spine2_x,Animal_5_spine2_y,Animal_5_spine2_p,Animal_5_spine3_x,Animal_5_spine3_y,Animal_5_spine3_p,Animal_5_spine4_x,Animal_5_spine4_y,Animal_5_spine4_p,Animal_5_spine5_x,Animal_5_spine5_y,Animal_5_spine5_p,Animal_6_nose_x,Animal_6_nose_y,Animal_6_nose_p,Animal_6_spine1_x,Animal_6_spine1_y,Animal_6_spine1_p,Animal_6_spine2_x,Animal_6_spine2_y,Animal_6_spine2_p,Animal_6_spine3_x,Animal_6_spine3_y,Animal_6_spine3_p,Animal_6_spine4_x,Animal_6_spine4_y,Animal_6_spine4_p,Animal_6_spine5_x,Animal_6_spine5_y,Animal_6_spine5_p
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catubc commented 2 years ago

Anyways, I'm open to any other suggestions. Thanks so much for the help.

sronilsson commented 2 years ago

There is something going on in how you defined the body-parts for the first animal. The last integer is the animal number (SimBA uses this integer to keep the animals separated): So you have an AnimalName_BodyPartName_AnimalInteger. You see that the female for some reason has an extra digit:

image.

sronilsson commented 2 years ago

Open the file, change female to this below, save file, and try and run it again.

image

catubc commented 2 years ago

Thanks, not sure where that's from, seems simba is generating these extra indexes.

I changed it all and it's still crashing on this elements issue:

female_nose_1
female_spine1_1
female_spine2_1
female_spine3_1
female_spine4_1
female_spine5_1
male_nose_2
male_spine1_2
male_spine2_2
male_spine3_2
male_spine4_2
male_spine5_2
pup1_nose_3
pup1_spine1_3
pup1_spine2_3
pup1_spine3_3
pup1_spine4_3
pup1_spine5_3
pup2_nose_4
pup2_spine1_4
pup2_spine2_4
pup2_spine3_4
pup2_spine4_4
pup2_spine5_4
pup3_nose_5
pup3_spine1_5
pup3_spine2_5
pup3_spine3_5
pup3_spine4_5
pup3_spine5_5
pup4_nose_6
pup4_spine1_6
pup4_spine2_6
pup4_spine3_6
pup4_spine4_6
pup4_spine5_6

Here's the log again


(simba3) cat@cat-Precision-T3610:~$ simba
Qt: Session management error: None of the authentication protocols specified are supported
Exception in Tkinter callback
Traceback (most recent call last):
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/tkinter/__init__.py", line 1705, in __call__
    return self.func(*args)
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/simba/SimBA.py", line 3895, in <lambda>
    button_skipOC = Button(label_outliercorrection,text='Skip outlier correction (CAUTION)',fg='red', command=lambda:skip_outlier_c(self.projectconfigini))
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/simba/outlier_scripts/skip_outlierCorrection.py", line 61, in skip_outlier_c
    csv_df.columns = newHeaders
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/pandas/core/generic.py", line 5192, in __setattr__
    return object.__setattr__(self, name, value)
  File "pandas/_libs/properties.pyx", line 67, in pandas._libs.properties.AxisProperty.__set__
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/pandas/core/generic.py", line 690, in _set_axis
    self._data.set_axis(axis, labels)
  File "/media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/pandas/core/internals/managers.py", line 183, in set_axis
    "values have {new} elements".format(old=old_len, new=new_len)
ValueError: Length mismatch: Expected axis has 126 elements, new values have 108 elements
sronilsson commented 2 years ago

Hmm.. what I would suggest:

For this file with the entries below, your paste suggest that there is an extra empty None row right at the end. Can you attach the actual CSV file here and I can check it?

Also, if I had to troubleshoot this myself, I would: 1: Open this file: /media/cat/4TBSSD/anaconda3/envs/simba3/lib/python3.6/site-packages/simba/outlier_scripts/skip_outlierCorrection.py

  1. Right before line 61 (csv_df.columns = newHeaders), insert a new line: print(newHeaders)

  2. Save, and re-run the outlier correction, and you'll see printed out what the hell the extra columns that SimBA is trying to use are. 

female_spine1_1
female_spine2_1
female_spine3_1
female_spine4_1
female_spine5_1
male_nose_2
male_spine1_2
male_spine2_2
male_spine3_2
male_spine4_2
male_spine5_2
pup1_nose_3
pup1_spine1_3
pup1_spine2_3
pup1_spine3_3
pup1_spine4_3
pup1_spine5_3
pup2_nose_4
pup2_spine1_4
pup2_spine2_4
pup2_spine3_4
pup2_spine4_4
pup2_spine5_4
pup3_nose_5
pup3_spine1_5
pup3_spine2_5
pup3_spine3_5
pup3_spine4_5
pup3_spine5_5
pup4_nose_6
pup4_spine1_6
pup4_spine2_6
pup4_spine3_6
pup4_spine4_6
pup4_spine5_6
catubc commented 2 years ago

Hi. Re: the printout, here's the screen grabs Screenshot from 2021-12-20 21-11-50 Screenshot from 2021-12-20 21-13-02 .

catubc commented 2 years ago

I should also mention that I'm using a special branch of Talmo's code that was developed specifically for our lab. It does bottom-up + ID prediction, and the code I think is still stuck in Ver1.1.0. Perhaps there are some incompatibilities there.

I put both the .mp4 and the .slp files here (should be uploaded in 5mins):

https://drive.google.com/drive/folders/1VwAq2CuVRCdQlyr6xVQ1OT6FHn8HS4HD?usp=sharing

If you have any other suggestions or have a moment to try and load them, I'd really appreciate it. Thanks so much!

sronilsson commented 2 years ago

Thanks, could you also send me the CSV file, the one inside the project_foldet/csv/input_csv, the one with the SLEP_multi in the top two lines, that I saw in one screenshot?

catubc commented 2 years ago

Ok, I uploaded both the csvs here:

https://drive.google.com/drive/folders/1VwAq2CuVRCdQlyr6xVQ1OT6FHn8HS4HD?usp=sharing

The one inside the input_csv folder is labeled as such, and the one outside in the main location where the SLEAP and video files are has .csv instead of .slp. (I also saved the entire project directory as gerbils4.zip).

Thanks so much, I'm excited to get this fixed and do some tracking.

sronilsson commented 2 years ago

Thanks! Yes we should be able to get this going, thanks for reporting the issues btw.

From what I can see on my phone, the CSV file contains a duplicate of the "female", and this is most likely what is causing the issue. If you scan the headers you'll see two "female" with identical body part coordinates. This issue could have been caused by SimBA, or be present in the the SLP h5 tracking file to begin with. I will look at the SLP h5 to start, but can only do that from a desktop and won't be for a day or so.

If you want to go ahead without me, try deleting the columns representing the duplicate female in the project_folder/csv/input_csv file and it should work to proceed with the skip outlier correction

catubc commented 2 years ago

Hi, thanks for this. I quickly deleted the extra female on inside .csv, but same error. I think actually the rest of the headers also have extra fields (the "SLEAP_multi" parts). These are a bit more tricky to delete as I have to count. If you could find the bug that would be great, otherwise I'll try to get to it later (I am doing wetlab work for the next bit). Thanks so much! catubc

catubc commented 2 years ago

Hi @sronilsson So I was able to get past the duplication issue finally. You were correct, there seems to be a bug somewhere that duplicates the first animal (in our case, the "female" gerbil).

I wrote a quick-and-dirty function for now to fix this duplication so we can test the rest of your pipeline, see below. It loads the simba-outputed CSV and removes the duplicate animal.

I would prefer to have a permanent fix, if you could guide me to the location where you think this happens I could try and fix+pull request it.

Thanks so much, catubc

def fix_simba_duplicate_animal_from_sleap(fname, 
                                          n_animals,
                                          n_features):

    import csv, os

    # read csv
    file = open(fname)
    csvreader = csv.reader(file)
    rows = []
    for row in csvreader:
        rows.append(row)
    file.close()

    # find rows where incorrect # of animals are present
    for k in trange(len(rows)):
        if len(rows[k])!=(1+n_animals*n_features*3):
            temp = rows[k].copy()
            temp = np.delete(temp,np.arange(1,1+n_features*3,1))  # delete the first duplicate occurance of animal #1
            rows[k] = temp

    # 
    with open(fname, 'w') as f:
        writer = csv.writer(f)
        for row in tqdm(rows):
            writer.writerow(row)

#######################################################
project_dir = '/media/cat/256GB/dan/simba/cohorts/gerbils4/'
video_name = '2020_08_01_11_27_15_857870_compressed_corrected.mp4'

fname = os.path.join(project_dir,
                     'project_folder/csv/input_csv',
                     video_name.replace('mp4','csv'))
n_animals = 6
n_features = 6

fix_simba_duplicate_animal_from_sleap(fname,
                                     n_animals,
                                     n_features)
sronilsson commented 2 years ago

Excellent if you do a PR I'd be grateful and review and merge and add to pip package too, I'd just avoid tqdm as its not currently a requirement. It should work if you call fix_simba_duplicate_animal_from_sleap after here:

https://github.com/sgoldenlab/simba/blob/4cac1f8c7864d752bdb49251d4f3b098f7041124/simba/sleap_bottom_up_convert.py#L333

or after this:

https://github.com/sgoldenlab/simba/blob/4cac1f8c7864d752bdb49251d4f3b098f7041124/simba/sleap_bottom_up_convert.py#L340

Sorry did not have time to look myself as traveling for xmas.