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File ~.conda\envs\tracking\Lib\site-packages\laptrack_tracking.py:763 in predict_dataframe
coords, frame_index = convert_dataframe_to_coords_frame_index(
File ~.conda\envs\tracking\Lib\site-packages\laptrack\data_conversion.py:81 in convert_dataframe_to_coords_frame_index
coords = convert_dataframe_to_coords(
File ~.conda\envs\tracking\Lib\site-packages\laptrack\data_conversion.py:45 in convert_dataframe_to_coords
assert np.array_equal(np.arange(df[frame_col].max() + 1), [g[0] for g in grps])
I am not an expert here. But i would like to get some idea on where this could be going wrong.
In the labels are not always continuous, meaning that in some frames some labels are not present and so on. so there is not a good trajectory like you have your example.
Hope this is enough information.
Thanks
:)
The text was updated successfully, but these errors were encountered:
Hi @piango, thanks for the report! Unfortunately the error message is not clear, but I suspect that this is because there's a frame without any points in the input dataframe. Let me try to see if there's a way to make it possible to track points even with this condition.
Hi
I just checked.
I removed the frames without any labels. and the workflow example you posted (that I am testing) works well.
So it is the issue.
It would be great if I can still use your pipeline, even if some frames are missing labels.
But its not a priority, and I can understand if you are busy.
Hello
I am new to your cool work here.
I am doing some 3D tracking (in time) of some labeled images.
I am trying some preliminary runs with your example @ laptrack/docs/examples
/3D_tracking.ipynb
And I get an AssertionError at:
track_df, split_df, merge_df = lt.predict_dataframe(
File ~.conda\envs\tracking\Lib\site-packages\laptrack_tracking.py:763 in predict_dataframe
coords, frame_index = convert_dataframe_to_coords_frame_index(
File ~.conda\envs\tracking\Lib\site-packages\laptrack\data_conversion.py:81 in convert_dataframe_to_coords_frame_index
coords = convert_dataframe_to_coords(
File ~.conda\envs\tracking\Lib\site-packages\laptrack\data_conversion.py:45 in convert_dataframe_to_coords
assert np.array_equal(np.arange(df[frame_col].max() + 1), [g[0] for g in grps])
I am not an expert here. But i would like to get some idea on where this could be going wrong.
In the labels are not always continuous, meaning that in some frames some labels are not present and so on. so there is not a good trajectory like you have your example.
Hope this is enough information.
Thanks
:)
The text was updated successfully, but these errors were encountered: