Difficulty with installing and testing bob
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nora
Nov 22, 2017, 5:05:44 PM11/22/17
to bob-devel
Hi : I am in the process of installing bob and testing it so I can do the hands on experiments, I followed the instructions from this page http://vast.uccs.edu/public-data/IJCB.html.I am in this step now where it ask to register the directory of the database inside ~/.bob_bio_databases.txt.I used the databases.py command and I can see the name of the database but not the path to it.
=====
(bob_py3) peter@peter-Satellite-C850D:~/Downloads$ databases.py
atnt:
Original data: [YOUR_ATNT_DIRECTORY]
=====
I tried to do this command
=====
(bob_py3) peter@peter-Satellite-C850D:~/Downloads$ databases.py
atnt:
Original data: [YOUR_ATNT_DIRECTORY]
=====
I tried to do this command
export ATNT_DATABASE_DIRECTORY=/home/peter/Downloads/att_faces
but nothing happened
could you please advice on what to do next?
I also tried to do the nose test and here is what I got
====
(bob_py3) peter@peter-Satellite-C850D:~/Downloads$ conda install nose
Fetching package metadata .............
Solving package specifications: .
Package plan for installation in environment /home/peter/.conda/envs/bob_py3:
The following NEW packages will be INSTALLED:
nose: 1.3.7-py36hcdf7029_2 defaults
Proceed ([y]/n)? y
=====
=====
(bob_py3) peter@peter-Satellite-C850D:~/Downloads$ nosetests -vs bob.bio.base
bob.bio.base.test.test_algorithms.test_pca ... bob.bio.base@2017-11-22 14:27:24,422 -- INFO: -> Training LinearMachine using PCA
Intel MKL FATAL ERROR: Cannot load libmkl_def.so.
=====
=====
(bob_py3) peter@peter-Satellite-C850D:~/Downloads$ nosetests -sv bob.bio.gmm
bob.bio.gmm.test.test_algorithms.test_gmm ... bob.bio.gmm@2017-11-22 14:45:27,909 -- INFO: -> Training UBM model with 5 training files
bob.bio.gmm@2017-11-22 14:45:27,911 -- DEBUG: .... Training with 500 feature vectors
bob.bio.gmm@2017-11-22 14:45:27,911 -- DEBUG: .... Creating machines
bob.bio.gmm@2017-11-22 14:45:27,912 -- INFO: -> Training K-Means
bob.learn.em@2017-11-22 14:45:27,913 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-22 14:45:27,914 -- DEBUG: average euclidean distance = 368.078425
bob.learn.em@2017-11-22 14:45:27,916 -- DEBUG: convergence value = 0.420920
bob.bio.gmm@2017-11-22 14:45:27,917 -- INFO: -> Training GMM
bob.learn.em@2017-11-22 14:45:27,920 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-22 14:45:27,923 -- DEBUG: log likelihood = -111.493542
bob.learn.em@2017-11-22 14:45:27,923 -- DEBUG: convergence value = 0.000412
bob.learn.em@2017-11-22 14:45:27,926 -- INFO: EM training converged after 0 iterations with convergence value 0.000412
bob.bio.gmm@2017-11-22 14:45:27,927 -- DEBUG: .... Saving model to file '/tmp/bobtest_byjrj0al.hdf5'
bob.bio.gmm@2017-11-22 14:45:27,948 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-22 14:45:27,955 -- DEBUG: .... Enrolling with 100 feature vectors
bob.learn.em@2017-11-22 14:45:27,956 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-22 14:45:27,957 -- DEBUG: log likelihood = -111.277058
bob.learn.em@2017-11-22 14:45:27,958 -- DEBUG: convergence value = 0.004922
ok
bob.bio.gmm.test.test_algorithms.test_gmm_regular ... bob.bio.gmm@2017-11-22 14:45:27,993 -- INFO: -> Training UBM model with 5 training files
bob.bio.gmm@2017-11-22 14:45:27,994 -- DEBUG: .... Training with 500 feature vectors
bob.bio.gmm@2017-11-22 14:45:27,995 -- DEBUG: .... Creating machines
bob.bio.gmm@2017-11-22 14:45:27,996 -- INFO: -> Training K-Means
bob.learn.em@2017-11-22 14:45:27,998 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-22 14:45:27,999 -- DEBUG: average euclidean distance = 368.078425
bob.learn.em@2017-11-22 14:45:28,000 -- DEBUG: convergence value = 0.420920
bob.bio.gmm@2017-11-22 14:45:28,001 -- INFO: -> Training GMM
bob.learn.em@2017-11-22 14:45:28,004 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-22 14:45:28,007 -- DEBUG: log likelihood = -111.493542
bob.learn.em@2017-11-22 14:45:28,007 -- DEBUG: convergence value = 0.000412
bob.learn.em@2017-11-22 14:45:28,008 -- INFO: EM training converged after 0 iterations with convergence value 0.000412
bob.bio.gmm@2017-11-22 14:45:28,008 -- DEBUG: .... Saving model to file '/tmp/bobtest_ejwp6wgp.hdf5'
bob.bio.gmm@2017-11-22 14:45:28,029 -- DEBUG: .... Enrolling with 100 feature vectors
bob.learn.em@2017-11-22 14:45:28,030 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-22 14:45:28,031 -- DEBUG: log likelihood = -111.277058
bob.learn.em@2017-11-22 14:45:28,032 -- DEBUG: convergence value = 0.004922
ok
bob.bio.gmm.test.test_algorithms.test_isv ... bob.bio.gmm@2017-11-22 14:45:28,081 -- DEBUG: .... Training with 2500 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,082 -- DEBUG: .... Creating machines
bob.bio.gmm@2017-11-22 14:45:28,082 -- INFO: -> Training K-Means
bob.learn.em@2017-11-22 14:45:28,089 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-22 14:45:28,110 -- DEBUG: average euclidean distance = 369.235419
bob.learn.em@2017-11-22 14:45:28,111 -- DEBUG: convergence value = 0.462682
bob.bio.gmm@2017-11-22 14:45:28,116 -- INFO: -> Training GMM
bob.learn.em@2017-11-22 14:45:28,135 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-22 14:45:28,154 -- DEBUG: log likelihood = -111.505114
bob.learn.em@2017-11-22 14:45:28,154 -- DEBUG: convergence value = 0.000456
bob.learn.em@2017-11-22 14:45:28,159 -- INFO: EM training converged after 0 iterations with convergence value 0.000456
bob.bio.gmm@2017-11-22 14:45:28,160 -- INFO: -> Projecting training data
bob.bio.gmm@2017-11-22 14:45:28,160 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,161 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,162 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,165 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,166 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,167 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,168 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,169 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,170 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,172 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,173 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,174 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,175 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,176 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,177 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,177 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,178 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,180 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,181 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,182 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,183 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,183 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,184 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,185 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,186 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-22 14:45:28,187 -- INFO: -> Training ISV enroller
Intel MKL FATAL ERROR: Cannot load libmkl_def.so.
=====
Please advice on how to proceed.I would really appreciate your help.
Thanks
Manuel Günther
Nov 22, 2017, 5:23:40 PM11/22/17
to bob-devel
Dear Nora,
After running databases.py again, now the correct path should be displayed. Let me know if this does not work.
by default, we do not know where you have downloaded your copy of the dataset to. Therefore, inside of the ~/.bob_bio_databases.txt you have to specify your database directory. Hence, for you the content could look something like:
[YOUR_ATNT_DIRECTORY]=/home/peter/Downloads/att_faces After running databases.py again, now the correct path should be displayed. Let me know if this does not work.
For the MKL error, it seems that there is a missing dependency (MKL) that has not been installed. Can you please describe, which part of the installation procedure of http://vast.uccs.edu/public-data/IJCB.html you were following?
Best regards
Manuel
nora
Nov 22, 2017, 6:17:08 PM11/22/17
to bob-devel
Thanks a lot for your response ,I have my database in the downloads with the name att_faces ,inside my bob_py3 i can not see ~/.bob_bio_databases.txt but i can see other files such as bin,lib,etc so I already created .bob_bio_databases.txt and inside it i put [YOUR_ATNT_DIRECTORY]=/home/peter/Downloads/att_faces
I still see the same thing.
(bob_py3) peter@peter-Satellite-C850D:~/Downloads$ databases.py
atnt:
Original data: [YOUR_ATNT_DIRECTORY]
For the second issue ,in http://vast.uccs.edu/public-data/IJCB.html where it ask to register the directory of the database ,it ask to go to Database Installation Documentation == https://www.idiap.ch/software/bob/docs/bob/bob.bio.base/stable/installation.html#databases. so i was following this link.
Amir Mohammadi
Nov 23, 2017, 2:48:51 AM11/23/17
to bob-...@googlegroups.com
This mkl error was fixed: https://gitlab.idiap.ch/bob/bob.conda/issues/38
Try updating bob.math and see if it fixes it:
conda update bob.math
Best,
Amir
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nora
Nov 23, 2017, 3:11:33 PM11/23/17
to bob-devel
Hi Amir:
Thanks a lot for your reply ,I updated bob.math as you suggested and now I got different error message ,please see below
=======
(bob_py3) peter@peter-Satellite-C850D:~/Downloads$ conda update bob.math
Thanks a lot for your reply ,I updated bob.math as you suggested and now I got different error message ,please see below
=======
(bob_py3) peter@peter-Satellite-C850D:~/Downloads$ conda update bob.math
Fetching package metadata .............
Solving package specifications: .
Package plan for installation in environment /home/peter/.conda/envs/bob_py3:
The following NEW packages will be INSTALLED:
libgfortran: 3.0.0-1 defaults
The following packages will be UPDATED:
bob.math: 3.0.0-np113py36_0 https://www.idiap.ch/software/bob/conda --> 3.0.0-np113py36_1 https://www.idiap.ch/software/bob/conda
The following packages will be DOWNGRADED:
mkl: 2018.0.0-hb491cac_4 defaults --> 2017.0.1-0 defaults
numpy: 1.13.3-py36ha12f23b_0 defaults --> 1.13.1-py36_0 defaults
scipy: 1.0.0-py36hbf646e7_0 defaults --> 0.19.1-np113py36_0 defaults
The following packages will be UPDATED:
bob.math: 3.0.0-np113py36_0 https://www.idiap.ch/software/bob/conda --> 3.0.0-np113py36_1 https://www.idiap.ch/software/bob/conda
The following packages will be DOWNGRADED:
mkl: 2018.0.0-hb491cac_4 defaults --> 2017.0.1-0 defaults
numpy: 1.13.3-py36ha12f23b_0 defaults --> 1.13.1-py36_0 defaults
scipy: 1.0.0-py36hbf646e7_0 defaults --> 0.19.1-np113py36_0 defaults
Proceed ([y]/n)? y
numpy-1.13.1-p 100% |###############################| Time: 0:00:13 543.74 kB/s
scipy-0.19.1-n 100% |###############################| Time: 0:01:22 463.70 kB/s
bob.math-3.0.0 100% |###############################| Time: 0:00:01 3.43 MB/s
========
========
scipy-0.19.1-n 100% |###############################| Time: 0:01:22 463.70 kB/s
bob.math-3.0.0 100% |###############################| Time: 0:00:01 3.43 MB/s
========
========
(bob_py3) peter@peter-Satellite-C850D:~/Downloads$ conda install nose
Fetching package metadata .............
Solving package specifications: .
# All requested packages already installed.
# packages in environment at /home/peter/.conda/envs/bob_py3:
#
nose 1.3.7 py36hcdf7029_2 defaults
=======
=======
# packages in environment at /home/peter/.conda/envs/bob_py3:
#
nose 1.3.7 py36hcdf7029_2 defaults
=======
=======
(bob_py3) peter@peter-Satellite-C850D:~/Downloads$ nosetests -vs bob.bio.base
bob.bio.base.test.test_algorithms.test_pca ... bob.bio.base@2017-11-23 12:17:36,569 -- INFO: -> Training LinearMachine using PCA
bob.bio.base@2017-11-23 12:17:37,861 -- INFO: ... Keeping 5 PCA dimensions
bob.bio.base@2017-11-23 12:17:37,974 -- INFO: -> Training LinearMachine using PCA
bob.bio.base@2017-11-23 12:17:38,577 -- INFO: ... Keeping 140 PCA dimensions
ok
bob.bio.base.test.test_algorithms.test_lda ... bob.bio.base@2017-11-23 12:17:38,737 -- INFO: -> Training Linear Machine using PCA
bob.bio.base@2017-11-23 12:17:38,920 -- INFO: ... Limiting PCA subspace to 10 dimensions
bob.bio.base@2017-11-23 12:17:38,921 -- INFO: -> Projecting training data to PCA subspace
bob.bio.base@2017-11-23 12:17:38,945 -- INFO: -> Training Linear Machine using LDA
bob.bio.base@2017-11-23 12:17:39,066 -- INFO: -> Training Linear Machine using PCA
bob.bio.base@2017-11-23 12:17:39,244 -- INFO: ... Limiting PCA subspace to 132 dimensions
bob.bio.base@2017-11-23 12:17:39,245 -- INFO: -> Projecting training data to PCA subspace
bob.bio.base@2017-11-23 12:17:39,343 -- INFO: -> Training Linear Machine using LDA
ok
bob.bio.base.test.test_algorithms.test_distance ... ok
bob.bio.base.test.test_algorithms.test_bic ... bob.bio.base@2017-11-23 12:17:39,665 -- INFO: -> Computing pairs
bob.bio.base@2017-11-23 12:17:39,668 -- INFO: -> Limiting intrapersonal pairs from 450 to 100
bob.bio.base@2017-11-23 12:17:39,669 -- INFO: -> Limiting extrapersonal pairs from 4500 to 100
bob.bio.base@2017-11-23 12:17:39,670 -- INFO: -> Computing 100 intrapersonal results
bob.bio.base@2017-11-23 12:17:39,674 -- INFO: -> Computing 100 extrapersonal results
bob.bio.base@2017-11-23 12:17:39,677 -- INFO: -> Training BIC machine
bob.bio.base@2017-11-23 12:17:39,837 -- INFO: -> Computing pairs
bob.bio.base@2017-11-23 12:17:39,840 -- INFO: -> Limiting intrapersonal pairs from 450 to 100
bob.bio.base@2017-11-23 12:17:39,841 -- INFO: -> Limiting extrapersonal pairs from 4500 to 100
bob.bio.base@2017-11-23 12:17:39,842 -- INFO: -> Computing 100 intrapersonal results
bob.bio.base@2017-11-23 12:17:39,846 -- INFO: -> Computing 100 extrapersonal results
bob.bio.base@2017-11-23 12:17:39,852 -- INFO: -> Training BIC machine
ok
bob.bio.base.test.test_algorithms.test_plda ... bob.bio.base@2017-11-23 12:17:39,991 -- INFO: -> Training LinearMachine using PCA
bob.bio.base@2017-11-23 12:17:40,170 -- INFO: -> limiting PCA subspace to 10 dimensions
bob.bio.base@2017-11-23 12:17:40,177 -- INFO: -> Training PLDA base machine
bob.learn.em@2017-11-23 12:17:40,246 -- DEBUG: Iteration = 1/1
ok
bob.bio.base.test.test_algorithms.test_plda_nopca ... bob.bio.base@2017-11-23 12:17:40,432 -- INFO: -> Training PLDA base machine
bob.learn.em@2017-11-23 12:17:40,621 -- DEBUG: Iteration = 1/1
ok
bob.bio.base.test.test_config_file.test_basic ... ok
bob.bio.base.test.test_config_file.test_compare_to_cmdline_basic ... ok
bob.bio.base.test.test_config_file.test_compare_to_cmdline_resources ... ok
bob.bio.base.test.test_config_file.test_compare_to_cmdline_skip ... ok
bob.bio.base.test.test_config_file.test_from_resource ... ok
bob.bio.base.test.test_config_file.test_from_module ... ok
bob.bio.base.test.test_config_file.test_order ... ok
bob.bio.base.test.test_config_file.test_order_inverse ... ok
bob.bio.base.test.test_extractor.test_linearize ... ok
bob.bio.base.test.test_filelist.test_query ... ok
bob.bio.base.test.test_filelist.test_query_protocol ... ok
bob.bio.base.test.test_filelist.test_query_dense ... ok
bob.bio.base.test.test_filelist.test_annotation ... ok
bob.bio.base.test.test_filelist.test_multiple_extensions ... ok
bob.bio.base.test.test_filelist.test_driver_api ... ok
bob.bio.base.test.test_preprocessor.test_filename ... ok
bob.bio.base.test.test_scripts.test_grid_search ... ok
bob.bio.base.test.test_scripts.test_verify_parallel ...
ok
bob.bio.base.test.test_scripts.test_verify_config ... ok
bob.bio.base.test.test_scripts.test_verify_algorithm_noprojection ... ok
bob.bio.base.test.test_scripts.test_verify_no_ztnorm ... ok
bob.bio.base.test.test_scripts.test_verify_resources ... ok
bob.bio.base.test.test_scripts.test_verify_commandline ... ok
bob.bio.base.test.test_scripts.test_verify_compressed ... ok
bob.bio.base.test.test_scripts.test_verify_calibrate ... ok
bob.bio.base.test.test_scripts.test_verify_fileset ... ok
bob.bio.base.test.test_scripts.test_verify_filelist ... ok
bob.bio.base.test.test_scripts.test_verify_missing ... bob.bio.base@2017-11-23 12:24:57,346 -- ERROR: There are NaN scores inside one of the score files for group dev; ZT-Norm will not work
ok
bob.bio.base.test.test_scripts.test_verify_five_col ... ok
bob.bio.base.test.test_scripts.test_verify_execute_only ... Would have executed task 'preprocess' with no parameters
Would have executed task 'compute-scores' with group='dev' and score-type='A'
Would have executed task 'compute-scores' with group='dev' and score-type='B'
Would have executed task 'compute-scores' with group='dev' and score-type='C'
Would have executed task 'compute-scores' with group='dev' and score-type='D'
Would have executed task 'compute-scores' with group='dev' and score-type='Z'
ok
bob.bio.base.test.test_scripts.test_internal_raises ... bob.bio.base@2017-11-23 12:25:53,275 -- ERROR: During the execution, an exception was raised: The option --group is an internal option and cannot be used to define experiments; did you mean to use --groups?
bob.bio.base@2017-11-23 12:25:53,353 -- ERROR: During the execution, an exception was raised: The option --model-type is an internal option and cannot be used to define experiments
bob.bio.base@2017-11-23 12:25:53,433 -- ERROR: During the execution, an exception was raised: The option --score-type is an internal option and cannot be used to define experiments
ok
bob.bio.base.test.test_scripts.test_verify_generate_config ... Configuration file '/tmp/bobtest_agehigh4/config.py' was written; exiting
ok
bob.bio.base.test.test_scripts.test_fusion ... ok
bob.bio.base.test.test_scripts.test_evaluate_closedset ... The HTER of the development set of 'no norm' is 50.000%
The HTER of the evaluation set of 'no norm' is 50.000%
The HTER of the development set of 'ZT norm' is 50.000%
The HTER of the evaluation set of 'ZT norm' is 50.000%
The Recognition Rate of the development set of 'no norm' is 0.000%
The Recognition Rate of the development set of 'no norm' is 0.000%
The Recognition Rate of the development set of 'ZT norm' is 0.000%
The Recognition Rate of the development set of 'ZT norm' is 0.000%
ok
bob.bio.base.test.test_scripts.test_evaluate_openset ... ok
bob.bio.base.test.test_scripts.test_resources ... ok
bob.bio.base.test.test_scripts.test_collect_results ... ok
bob.bio.base.test.test_scripts.test_scripts ... ok
bob.bio.base.test.test_tools.test_file_selector ... ok
bob.bio.base.test.test_utils.test_resources ... ok
bob.bio.base.test.test_utils.test_grid ... ok
bob.bio.base.test.test_utils.test_io ... ok
bob.bio.base.test.test_utils.test_io_vstack ... ok
bob.bio.base.test.test_utils.test_sampling ... ok
----------------------------------------------------------------------
Ran 50 tests in 520.693s
OK
bob.c++@2017-11-23 12:26:17,090 -- ERROR: Cannot compute FAR or FRR with threshold NaNCannot compute FAR or FRR with threshold NaN
=====
=====
(bob_py3) peter@peter-Satellite-C850D:~/Downloads$ nosetests -vs bob.bio.gmm
bob.bio.gmm.test.test_algorithms.test_gmm ... bob.bio.gmm@2017-11-23 12:37:50,436 -- INFO: -> Training UBM model with 5 training files
bob.bio.gmm@2017-11-23 12:37:50,440 -- DEBUG: .... Training with 500 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,441 -- DEBUG: .... Creating machines
bob.bio.gmm@2017-11-23 12:37:50,442 -- INFO: -> Training K-Means
bob.learn.em@2017-11-23 12:37:50,443 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,445 -- DEBUG: average euclidean distance = 368.078425
bob.learn.em@2017-11-23 12:37:50,447 -- DEBUG: convergence value = 0.420920
bob.bio.gmm@2017-11-23 12:37:50,448 -- INFO: -> Training GMM
bob.learn.em@2017-11-23 12:37:50,453 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,457 -- DEBUG: log likelihood = -111.493542
bob.learn.em@2017-11-23 12:37:50,458 -- DEBUG: convergence value = 0.000412
bob.learn.em@2017-11-23 12:37:50,458 -- INFO: EM training converged after 0 iterations with convergence value 0.000412
bob.bio.gmm@2017-11-23 12:37:50,458 -- DEBUG: .... Saving model to file '/tmp/bobtest_2ejby561.hdf5'
bob.bio.gmm@2017-11-23 12:37:50,485 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,491 -- DEBUG: .... Enrolling with 100 feature vectors
bob.learn.em@2017-11-23 12:37:50,493 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,495 -- DEBUG: log likelihood = -111.277058
bob.learn.em@2017-11-23 12:37:50,495 -- DEBUG: convergence value = 0.004922
ok
bob.bio.gmm.test.test_algorithms.test_gmm_regular ... bob.bio.gmm@2017-11-23 12:37:50,542 -- INFO: -> Training UBM model with 5 training files
bob.bio.gmm@2017-11-23 12:37:50,544 -- DEBUG: .... Training with 500 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,545 -- DEBUG: .... Creating machines
bob.bio.gmm@2017-11-23 12:37:50,545 -- INFO: -> Training K-Means
bob.learn.em@2017-11-23 12:37:50,548 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,551 -- DEBUG: average euclidean distance = 368.078425
bob.learn.em@2017-11-23 12:37:50,552 -- DEBUG: convergence value = 0.420920
bob.bio.gmm@2017-11-23 12:37:50,554 -- INFO: -> Training GMM
bob.learn.em@2017-11-23 12:37:50,560 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,563 -- DEBUG: log likelihood = -111.493542
bob.learn.em@2017-11-23 12:37:50,564 -- DEBUG: convergence value = 0.000412
bob.learn.em@2017-11-23 12:37:50,564 -- INFO: EM training converged after 0 iterations with convergence value 0.000412
bob.bio.gmm@2017-11-23 12:37:50,565 -- DEBUG: .... Saving model to file '/tmp/bobtest_f297yidj.hdf5'
bob.bio.gmm@2017-11-23 12:37:50,584 -- DEBUG: .... Enrolling with 100 feature vectors
bob.learn.em@2017-11-23 12:37:50,585 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,586 -- DEBUG: log likelihood = -111.277058
bob.learn.em@2017-11-23 12:37:50,586 -- DEBUG: convergence value = 0.004922
ok
bob.bio.gmm.test.test_algorithms.test_isv ... bob.bio.gmm@2017-11-23 12:37:50,655 -- DEBUG: .... Training with 2500 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,656 -- DEBUG: .... Creating machines
bob.bio.gmm@2017-11-23 12:37:50,656 -- INFO: -> Training K-Means
bob.learn.em@2017-11-23 12:37:50,661 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,665 -- DEBUG: average euclidean distance = 369.235419
bob.learn.em@2017-11-23 12:37:50,666 -- DEBUG: convergence value = 0.462682
bob.bio.gmm@2017-11-23 12:37:50,671 -- INFO: -> Training GMM
bob.learn.em@2017-11-23 12:37:50,686 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,699 -- DEBUG: log likelihood = -111.505114
bob.learn.em@2017-11-23 12:37:50,699 -- DEBUG: convergence value = 0.000456
bob.learn.em@2017-11-23 12:37:50,700 -- INFO: EM training converged after 0 iterations with convergence value 0.000456
bob.bio.gmm@2017-11-23 12:37:50,700 -- INFO: -> Projecting training data
bob.bio.gmm@2017-11-23 12:37:50,701 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,701 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,702 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,703 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,704 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,705 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,706 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,707 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,707 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,708 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,709 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,710 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,711 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,712 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,712 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,713 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,714 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,715 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,716 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,717 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,718 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,719 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,719 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,720 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,721 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,722 -- INFO: -> Training ISV enroller
bob.learn.em@2017-11-23 12:37:50,732 -- DEBUG: Iteration = 1/1
bob.bio.gmm@2017-11-23 12:37:50,756 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,763 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,766 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,767 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,768 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,769 -- DEBUG: .... Projecting 20 feature vectors
ok
bob.bio.gmm.test.test_algorithms.test_jfa ... bob.bio.gmm@2017-11-23 12:37:50,809 -- INFO: -> Training UBM model with 5 training files
bob.bio.gmm@2017-11-23 12:37:50,810 -- DEBUG: .... Training with 500 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,811 -- DEBUG: .... Creating machines
bob.bio.gmm@2017-11-23 12:37:50,811 -- INFO: -> Training K-Means
bob.learn.em@2017-11-23 12:37:50,813 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,814 -- DEBUG: average euclidean distance = 368.078425
bob.learn.em@2017-11-23 12:37:50,815 -- DEBUG: convergence value = 0.420920
bob.bio.gmm@2017-11-23 12:37:50,816 -- INFO: -> Training GMM
bob.learn.em@2017-11-23 12:37:50,820 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,823 -- DEBUG: log likelihood = -111.493542
bob.learn.em@2017-11-23 12:37:50,824 -- DEBUG: convergence value = 0.000412
bob.learn.em@2017-11-23 12:37:50,824 -- INFO: EM training converged after 0 iterations with convergence value 0.000412
bob.bio.gmm@2017-11-23 12:37:50,824 -- DEBUG: .... Saving model to file '/tmp/bobtest_e7cn4d8m.hdf5'
bob.bio.gmm@2017-11-23 12:37:50,842 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,851 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,852 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,852 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,853 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,853 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,854 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,854 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,855 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,855 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,856 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,856 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,857 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,857 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,858 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,858 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,859 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,859 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,860 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,860 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,861 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,861 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,862 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,862 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,863 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,863 -- DEBUG: .... Projecting 20 feature vectors
bob.learn.em@2017-11-23 12:37:50,865 -- INFO: V subspace estimation...
bob.learn.em@2017-11-23 12:37:50,865 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,866 -- INFO: U subspace estimation...
bob.learn.em@2017-11-23 12:37:50,867 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,868 -- INFO: D subspace estimation...
bob.learn.em@2017-11-23 12:37:50,869 -- DEBUG: Iteration = 1/1
bob.bio.gmm@2017-11-23 12:37:50,879 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,880 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,880 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,881 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,881 -- DEBUG: .... Projecting 20 feature vectors
ok
bob.bio.gmm.test.test_algorithms.test_ivector_cosine ... bob.bio.gmm@2017-11-23 12:37:50,919 -- DEBUG: .... Training with 500 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,919 -- DEBUG: .... Creating machines
bob.bio.gmm@2017-11-23 12:37:50,920 -- INFO: -> Training K-Means
bob.learn.em@2017-11-23 12:37:50,921 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,923 -- DEBUG: average euclidean distance = 368.078425
bob.learn.em@2017-11-23 12:37:50,923 -- DEBUG: convergence value = 0.420920
bob.bio.gmm@2017-11-23 12:37:50,925 -- INFO: -> Training GMM
bob.learn.em@2017-11-23 12:37:50,930 -- DEBUG: Iteration = 1/25
bob.learn.em@2017-11-23 12:37:50,933 -- DEBUG: log likelihood = -111.493542
bob.learn.em@2017-11-23 12:37:50,934 -- DEBUG: convergence value = 0.000412
bob.learn.em@2017-11-23 12:37:50,934 -- INFO: EM training converged after 0 iterations with convergence value 0.000412
bob.bio.gmm@2017-11-23 12:37:50,934 -- INFO: -> Projecting training data
bob.bio.gmm@2017-11-23 12:37:50,935 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,936 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,937 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,938 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,939 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,940 -- INFO: -> Projecting training data
bob.bio.gmm@2017-11-23 12:37:50,940 -- INFO: -> Training IVector enroller
bob.learn.em@2017-11-23 12:37:50,941 -- DEBUG: Iteration = 1/1
bob.bio.gmm@2017-11-23 12:37:50,973 -- INFO: -> Training Whitening
bob.bio.gmm@2017-11-23 12:37:50,982 -- DEBUG: .... Saving model to file 'HDF5File(filename='/tmp/bobtest_4bgka4k3.hdf5')'
bob.bio.gmm@2017-11-23 12:37:51,034 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,042 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,057 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,060 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,063 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,065 -- DEBUG: .... Projecting 20 feature vectors
ok
bob.bio.gmm.test.test_algorithms.test_ivector_plda ... bob.bio.gmm@2017-11-23 12:37:51,174 -- DEBUG: .... Training with 2500 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,175 -- DEBUG: .... Creating machines
bob.bio.gmm@2017-11-23 12:37:51,177 -- INFO: -> Training K-Means
bob.learn.em@2017-11-23 12:37:51,184 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:51,190 -- DEBUG: average euclidean distance = 369.235419
bob.learn.em@2017-11-23 12:37:51,191 -- DEBUG: convergence value = 0.462682
bob.bio.gmm@2017-11-23 12:37:51,197 -- INFO: -> Training GMM
bob.learn.em@2017-11-23 12:37:51,213 -- DEBUG: Iteration = 1/25
bob.learn.em@2017-11-23 12:37:51,225 -- DEBUG: log likelihood = -111.505114
bob.learn.em@2017-11-23 12:37:51,226 -- DEBUG: convergence value = 0.000456
bob.learn.em@2017-11-23 12:37:51,226 -- INFO: EM training converged after 0 iterations with convergence value 0.000456
bob.bio.gmm@2017-11-23 12:37:51,227 -- INFO: -> Projecting training data
bob.bio.gmm@2017-11-23 12:37:51,227 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,228 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,229 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,230 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,230 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,232 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,232 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,233 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,234 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,235 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,236 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,237 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,238 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,239 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,242 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,243 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,244 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,245 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,246 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,247 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,248 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,249 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,250 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,250 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,251 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,252 -- INFO: -> Projecting training data
bob.bio.gmm@2017-11-23 12:37:51,252 -- INFO: -> Training IVector enroller
bob.learn.em@2017-11-23 12:37:51,255 -- DEBUG: Iteration = 1/1
bob.bio.gmm@2017-11-23 12:37:51,259 -- INFO: -> Training Whitening
bob.bio.gmm@2017-11-23 12:37:51,262 -- INFO: -> Training PLDA projector
bob.learn.em@2017-11-23 12:37:51,265 -- DEBUG: Iteration = 1/2
bob.learn.em@2017-11-23 12:37:51,266 -- DEBUG: Iteration = 2/2
bob.bio.gmm@2017-11-23 12:37:51,269 -- DEBUG: .... Saving model to file 'HDF5File(filename='/tmp/bobtest_srgauq6p.hdf5')'
bob.bio.gmm@2017-11-23 12:37:51,323 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,328 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,330 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,332 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,334 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,340 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,367 -- INFO: 1.218798
ok
bob.bio.gmm.test.test_algorithms.test_ivector_lda_wccn_plda ... bob.bio.gmm@2017-11-23 12:37:51,452 -- DEBUG: .... Training with 2500 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,455 -- DEBUG: .... Creating machines
bob.bio.gmm@2017-11-23 12:37:51,458 -- INFO: -> Training K-Means
bob.learn.em@2017-11-23 12:37:51,477 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:51,492 -- DEBUG: average euclidean distance = 369.235419
bob.learn.em@2017-11-23 12:37:51,495 -- DEBUG: convergence value = 0.462682
bob.bio.gmm@2017-11-23 12:37:51,507 -- INFO: -> Training GMM
bob.learn.em@2017-11-23 12:37:51,544 -- DEBUG: Iteration = 1/25
bob.learn.em@2017-11-23 12:37:51,566 -- DEBUG: log likelihood = -111.505114
bob.learn.em@2017-11-23 12:37:51,567 -- DEBUG: convergence value = 0.000456
bob.learn.em@2017-11-23 12:37:51,568 -- INFO: EM training converged after 0 iterations with convergence value 0.000456
bob.bio.gmm@2017-11-23 12:37:51,569 -- INFO: -> Projecting training data
bob.bio.gmm@2017-11-23 12:37:51,569 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,571 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,573 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,574 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,575 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,576 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,578 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,579 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,580 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,583 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,585 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,586 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,587 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,588 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,589 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,592 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,593 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,595 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,596 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,597 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,598 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,601 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,603 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,604 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,605 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,607 -- INFO: -> Projecting training data
bob.bio.gmm@2017-11-23 12:37:51,607 -- INFO: -> Training IVector enroller
bob.learn.em@2017-11-23 12:37:51,610 -- DEBUG: Iteration = 1/1
bob.bio.gmm@2017-11-23 12:37:51,615 -- INFO: -> Training Whitening
bob.bio.gmm@2017-11-23 12:37:51,618 -- INFO: -> Training LDA projector
bob.bio.gmm@2017-11-23 12:37:51,619 -- INFO: -> Training WCCN projector
bob.bio.gmm@2017-11-23 12:37:51,621 -- INFO: -> Training PLDA projector
bob.learn.em@2017-11-23 12:37:51,655 -- DEBUG: Iteration = 1/2
bob.learn.em@2017-11-23 12:37:51,656 -- DEBUG: Iteration = 2/2
bob.bio.gmm@2017-11-23 12:37:51,660 -- DEBUG: .... Saving model to file 'HDF5File(filename='/tmp/bobtest_zk0mj90r.hdf5')'
bob.bio.gmm@2017-11-23 12:37:51,779 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,806 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,810 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,812 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,813 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,814 -- DEBUG: .... Projecting 20 feature vectors
ok
bob.bio.gmm.test.test_scripts.test_gmm_parallel ... ok
bob.bio.gmm.test.test_scripts.test_isv_parallel ... ok
bob.bio.gmm.test.test_scripts.test_ivector_cosine_parallel ... ok
bob.bio.gmm.test.test_scripts.test_ivector_lda_wccn_plda_parallel ... ok
bob.bio.gmm.test.test_scripts.test_gmm_sequential ... ok
bob.bio.gmm.test.test_scripts.test_isv_sequential ... ok
bob.bio.gmm.test.test_scripts.test_ivector_cosine_sequential ... ok
bob.bio.gmm.test.test_scripts.test_ivector_lda_wccn_plda_sequential ... ok
bob.bio.gmm.test.test_scripts.test_internal_raises ... bob.bio.gmm@2017-11-23 12:57:44,134 -- ERROR: During the execution, an exception was raised: The option --iteration is an internal option and cannot be used to define experiments
bob.bio.gmm@2017-11-23 12:57:44,202 -- ERROR: During the execution, an exception was raised: The option --group is an internal option and cannot be used to define experiments; did you mean to use --groups?
bob.bio.gmm@2017-11-23 12:57:44,269 -- ERROR: During the execution, an exception was raised: The option --model-type is an internal option and cannot be used to define experiments
bob.bio.gmm@2017-11-23 12:57:44,338 -- ERROR: During the execution, an exception was raised: The option --score-type is an internal option and cannot be used to define experiments
bob.bio.gmm@2017-11-23 12:57:44,405 -- ERROR: During the execution, an exception was raised: The option --iteration is an internal option and cannot be used to define experiments
bob.bio.gmm@2017-11-23 12:57:44,473 -- ERROR: During the execution, an exception was raised: The option --group is an internal option and cannot be used to define experiments; did you mean to use --groups?
bob.bio.gmm@2017-11-23 12:57:44,540 -- ERROR: During the execution, an exception was raised: The option --model-type is an internal option and cannot be used to define experiments
bob.bio.gmm@2017-11-23 12:57:44,608 -- ERROR: During the execution, an exception was raised: The option --score-type is an internal option and cannot be used to define experiments
bob.bio.gmm@2017-11-23 12:57:44,678 -- ERROR: During the execution, an exception was raised: The option --iteration is an internal option and cannot be used to define experiments
bob.bio.gmm@2017-11-23 12:57:44,748 -- ERROR: During the execution, an exception was raised: The option --group is an internal option and cannot be used to define experiments; did you mean to use --groups?
bob.bio.gmm@2017-11-23 12:57:44,819 -- ERROR: During the execution, an exception was raised: The option --model-type is an internal option and cannot be used to define experiments
bob.bio.gmm@2017-11-23 12:57:44,888 -- ERROR: During the execution, an exception was raised: The option --score-type is an internal option and cannot be used to define experiments
ok
----------------------------------------------------------------------
Ran 16 tests in 1194.677s
OK
(bob_py3) peter@peter-Satellite-C850D:~/Downloads$
========
Please advise ,Thanks a lot in advance.
bob.bio.base@2017-11-23 12:17:37,861 -- INFO: ... Keeping 5 PCA dimensions
bob.bio.base@2017-11-23 12:17:37,974 -- INFO: -> Training LinearMachine using PCA
bob.bio.base@2017-11-23 12:17:38,577 -- INFO: ... Keeping 140 PCA dimensions
ok
bob.bio.base.test.test_algorithms.test_lda ... bob.bio.base@2017-11-23 12:17:38,737 -- INFO: -> Training Linear Machine using PCA
bob.bio.base@2017-11-23 12:17:38,920 -- INFO: ... Limiting PCA subspace to 10 dimensions
bob.bio.base@2017-11-23 12:17:38,921 -- INFO: -> Projecting training data to PCA subspace
bob.bio.base@2017-11-23 12:17:38,945 -- INFO: -> Training Linear Machine using LDA
bob.bio.base@2017-11-23 12:17:39,066 -- INFO: -> Training Linear Machine using PCA
bob.bio.base@2017-11-23 12:17:39,244 -- INFO: ... Limiting PCA subspace to 132 dimensions
bob.bio.base@2017-11-23 12:17:39,245 -- INFO: -> Projecting training data to PCA subspace
bob.bio.base@2017-11-23 12:17:39,343 -- INFO: -> Training Linear Machine using LDA
ok
bob.bio.base.test.test_algorithms.test_distance ... ok
bob.bio.base.test.test_algorithms.test_bic ... bob.bio.base@2017-11-23 12:17:39,665 -- INFO: -> Computing pairs
bob.bio.base@2017-11-23 12:17:39,668 -- INFO: -> Limiting intrapersonal pairs from 450 to 100
bob.bio.base@2017-11-23 12:17:39,669 -- INFO: -> Limiting extrapersonal pairs from 4500 to 100
bob.bio.base@2017-11-23 12:17:39,670 -- INFO: -> Computing 100 intrapersonal results
bob.bio.base@2017-11-23 12:17:39,674 -- INFO: -> Computing 100 extrapersonal results
bob.bio.base@2017-11-23 12:17:39,677 -- INFO: -> Training BIC machine
bob.bio.base@2017-11-23 12:17:39,837 -- INFO: -> Computing pairs
bob.bio.base@2017-11-23 12:17:39,840 -- INFO: -> Limiting intrapersonal pairs from 450 to 100
bob.bio.base@2017-11-23 12:17:39,841 -- INFO: -> Limiting extrapersonal pairs from 4500 to 100
bob.bio.base@2017-11-23 12:17:39,842 -- INFO: -> Computing 100 intrapersonal results
bob.bio.base@2017-11-23 12:17:39,846 -- INFO: -> Computing 100 extrapersonal results
bob.bio.base@2017-11-23 12:17:39,852 -- INFO: -> Training BIC machine
ok
bob.bio.base.test.test_algorithms.test_plda ... bob.bio.base@2017-11-23 12:17:39,991 -- INFO: -> Training LinearMachine using PCA
bob.bio.base@2017-11-23 12:17:40,170 -- INFO: -> limiting PCA subspace to 10 dimensions
bob.bio.base@2017-11-23 12:17:40,177 -- INFO: -> Training PLDA base machine
bob.learn.em@2017-11-23 12:17:40,246 -- DEBUG: Iteration = 1/1
ok
bob.bio.base.test.test_algorithms.test_plda_nopca ... bob.bio.base@2017-11-23 12:17:40,432 -- INFO: -> Training PLDA base machine
bob.learn.em@2017-11-23 12:17:40,621 -- DEBUG: Iteration = 1/1
ok
bob.bio.base.test.test_config_file.test_basic ... ok
bob.bio.base.test.test_config_file.test_compare_to_cmdline_basic ... ok
bob.bio.base.test.test_config_file.test_compare_to_cmdline_resources ... ok
bob.bio.base.test.test_config_file.test_compare_to_cmdline_skip ... ok
bob.bio.base.test.test_config_file.test_from_resource ... ok
bob.bio.base.test.test_config_file.test_from_module ... ok
bob.bio.base.test.test_config_file.test_order ... ok
bob.bio.base.test.test_config_file.test_order_inverse ... ok
bob.bio.base.test.test_extractor.test_linearize ... ok
bob.bio.base.test.test_filelist.test_query ... ok
bob.bio.base.test.test_filelist.test_query_protocol ... ok
bob.bio.base.test.test_filelist.test_query_dense ... ok
bob.bio.base.test.test_filelist.test_annotation ... ok
bob.bio.base.test.test_filelist.test_multiple_extensions ... ok
bob.bio.base.test.test_filelist.test_driver_api ... ok
bob.bio.base.test.test_preprocessor.test_filename ... ok
bob.bio.base.test.test_scripts.test_grid_search ... ok
bob.bio.base.test.test_scripts.test_verify_parallel ...
ok
bob.bio.base.test.test_scripts.test_verify_config ... ok
bob.bio.base.test.test_scripts.test_verify_algorithm_noprojection ... ok
bob.bio.base.test.test_scripts.test_verify_no_ztnorm ... ok
bob.bio.base.test.test_scripts.test_verify_resources ... ok
bob.bio.base.test.test_scripts.test_verify_commandline ... ok
bob.bio.base.test.test_scripts.test_verify_compressed ... ok
bob.bio.base.test.test_scripts.test_verify_calibrate ... ok
bob.bio.base.test.test_scripts.test_verify_fileset ... ok
bob.bio.base.test.test_scripts.test_verify_filelist ... ok
bob.bio.base.test.test_scripts.test_verify_missing ... bob.bio.base@2017-11-23 12:24:57,346 -- ERROR: There are NaN scores inside one of the score files for group dev; ZT-Norm will not work
ok
bob.bio.base.test.test_scripts.test_verify_five_col ... ok
bob.bio.base.test.test_scripts.test_verify_execute_only ... Would have executed task 'preprocess' with no parameters
Would have executed task 'compute-scores' with group='dev' and score-type='A'
Would have executed task 'compute-scores' with group='dev' and score-type='B'
Would have executed task 'compute-scores' with group='dev' and score-type='C'
Would have executed task 'compute-scores' with group='dev' and score-type='D'
Would have executed task 'compute-scores' with group='dev' and score-type='Z'
ok
bob.bio.base.test.test_scripts.test_internal_raises ... bob.bio.base@2017-11-23 12:25:53,275 -- ERROR: During the execution, an exception was raised: The option --group is an internal option and cannot be used to define experiments; did you mean to use --groups?
bob.bio.base@2017-11-23 12:25:53,353 -- ERROR: During the execution, an exception was raised: The option --model-type is an internal option and cannot be used to define experiments
bob.bio.base@2017-11-23 12:25:53,433 -- ERROR: During the execution, an exception was raised: The option --score-type is an internal option and cannot be used to define experiments
ok
bob.bio.base.test.test_scripts.test_verify_generate_config ... Configuration file '/tmp/bobtest_agehigh4/config.py' was written; exiting
ok
bob.bio.base.test.test_scripts.test_fusion ... ok
bob.bio.base.test.test_scripts.test_evaluate_closedset ... The HTER of the development set of 'no norm' is 50.000%
The HTER of the evaluation set of 'no norm' is 50.000%
The HTER of the development set of 'ZT norm' is 50.000%
The HTER of the evaluation set of 'ZT norm' is 50.000%
The Recognition Rate of the development set of 'no norm' is 0.000%
The Recognition Rate of the development set of 'no norm' is 0.000%
The Recognition Rate of the development set of 'ZT norm' is 0.000%
The Recognition Rate of the development set of 'ZT norm' is 0.000%
ok
bob.bio.base.test.test_scripts.test_evaluate_openset ... ok
bob.bio.base.test.test_scripts.test_resources ... ok
bob.bio.base.test.test_scripts.test_collect_results ... ok
bob.bio.base.test.test_scripts.test_scripts ... ok
bob.bio.base.test.test_tools.test_file_selector ... ok
bob.bio.base.test.test_utils.test_resources ... ok
bob.bio.base.test.test_utils.test_grid ... ok
bob.bio.base.test.test_utils.test_io ... ok
bob.bio.base.test.test_utils.test_io_vstack ... ok
bob.bio.base.test.test_utils.test_sampling ... ok
----------------------------------------------------------------------
Ran 50 tests in 520.693s
OK
bob.c++@2017-11-23 12:26:17,090 -- ERROR: Cannot compute FAR or FRR with threshold NaNCannot compute FAR or FRR with threshold NaN
=====
=====
(bob_py3) peter@peter-Satellite-C850D:~/Downloads$ nosetests -vs bob.bio.gmm
bob.bio.gmm.test.test_algorithms.test_gmm ... bob.bio.gmm@2017-11-23 12:37:50,436 -- INFO: -> Training UBM model with 5 training files
bob.bio.gmm@2017-11-23 12:37:50,440 -- DEBUG: .... Training with 500 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,441 -- DEBUG: .... Creating machines
bob.bio.gmm@2017-11-23 12:37:50,442 -- INFO: -> Training K-Means
bob.learn.em@2017-11-23 12:37:50,443 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,445 -- DEBUG: average euclidean distance = 368.078425
bob.learn.em@2017-11-23 12:37:50,447 -- DEBUG: convergence value = 0.420920
bob.bio.gmm@2017-11-23 12:37:50,448 -- INFO: -> Training GMM
bob.learn.em@2017-11-23 12:37:50,453 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,457 -- DEBUG: log likelihood = -111.493542
bob.learn.em@2017-11-23 12:37:50,458 -- DEBUG: convergence value = 0.000412
bob.learn.em@2017-11-23 12:37:50,458 -- INFO: EM training converged after 0 iterations with convergence value 0.000412
bob.bio.gmm@2017-11-23 12:37:50,458 -- DEBUG: .... Saving model to file '/tmp/bobtest_2ejby561.hdf5'
bob.bio.gmm@2017-11-23 12:37:50,485 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,491 -- DEBUG: .... Enrolling with 100 feature vectors
bob.learn.em@2017-11-23 12:37:50,493 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,495 -- DEBUG: log likelihood = -111.277058
bob.learn.em@2017-11-23 12:37:50,495 -- DEBUG: convergence value = 0.004922
ok
bob.bio.gmm.test.test_algorithms.test_gmm_regular ... bob.bio.gmm@2017-11-23 12:37:50,542 -- INFO: -> Training UBM model with 5 training files
bob.bio.gmm@2017-11-23 12:37:50,544 -- DEBUG: .... Training with 500 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,545 -- DEBUG: .... Creating machines
bob.bio.gmm@2017-11-23 12:37:50,545 -- INFO: -> Training K-Means
bob.learn.em@2017-11-23 12:37:50,548 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,551 -- DEBUG: average euclidean distance = 368.078425
bob.learn.em@2017-11-23 12:37:50,552 -- DEBUG: convergence value = 0.420920
bob.bio.gmm@2017-11-23 12:37:50,554 -- INFO: -> Training GMM
bob.learn.em@2017-11-23 12:37:50,560 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,563 -- DEBUG: log likelihood = -111.493542
bob.learn.em@2017-11-23 12:37:50,564 -- DEBUG: convergence value = 0.000412
bob.learn.em@2017-11-23 12:37:50,564 -- INFO: EM training converged after 0 iterations with convergence value 0.000412
bob.bio.gmm@2017-11-23 12:37:50,565 -- DEBUG: .... Saving model to file '/tmp/bobtest_f297yidj.hdf5'
bob.bio.gmm@2017-11-23 12:37:50,584 -- DEBUG: .... Enrolling with 100 feature vectors
bob.learn.em@2017-11-23 12:37:50,585 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,586 -- DEBUG: log likelihood = -111.277058
bob.learn.em@2017-11-23 12:37:50,586 -- DEBUG: convergence value = 0.004922
ok
bob.bio.gmm.test.test_algorithms.test_isv ... bob.bio.gmm@2017-11-23 12:37:50,655 -- DEBUG: .... Training with 2500 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,656 -- DEBUG: .... Creating machines
bob.bio.gmm@2017-11-23 12:37:50,656 -- INFO: -> Training K-Means
bob.learn.em@2017-11-23 12:37:50,661 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,665 -- DEBUG: average euclidean distance = 369.235419
bob.learn.em@2017-11-23 12:37:50,666 -- DEBUG: convergence value = 0.462682
bob.bio.gmm@2017-11-23 12:37:50,671 -- INFO: -> Training GMM
bob.learn.em@2017-11-23 12:37:50,686 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,699 -- DEBUG: log likelihood = -111.505114
bob.learn.em@2017-11-23 12:37:50,699 -- DEBUG: convergence value = 0.000456
bob.learn.em@2017-11-23 12:37:50,700 -- INFO: EM training converged after 0 iterations with convergence value 0.000456
bob.bio.gmm@2017-11-23 12:37:50,700 -- INFO: -> Projecting training data
bob.bio.gmm@2017-11-23 12:37:50,701 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,701 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,702 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,703 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,704 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,705 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,706 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,707 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,707 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,708 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,709 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,710 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,711 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,712 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,712 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,713 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,714 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,715 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,716 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,717 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,718 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,719 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,719 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,720 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,721 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,722 -- INFO: -> Training ISV enroller
bob.learn.em@2017-11-23 12:37:50,732 -- DEBUG: Iteration = 1/1
bob.bio.gmm@2017-11-23 12:37:50,756 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,763 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,766 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,767 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,768 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,769 -- DEBUG: .... Projecting 20 feature vectors
ok
bob.bio.gmm.test.test_algorithms.test_jfa ... bob.bio.gmm@2017-11-23 12:37:50,809 -- INFO: -> Training UBM model with 5 training files
bob.bio.gmm@2017-11-23 12:37:50,810 -- DEBUG: .... Training with 500 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,811 -- DEBUG: .... Creating machines
bob.bio.gmm@2017-11-23 12:37:50,811 -- INFO: -> Training K-Means
bob.learn.em@2017-11-23 12:37:50,813 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,814 -- DEBUG: average euclidean distance = 368.078425
bob.learn.em@2017-11-23 12:37:50,815 -- DEBUG: convergence value = 0.420920
bob.bio.gmm@2017-11-23 12:37:50,816 -- INFO: -> Training GMM
bob.learn.em@2017-11-23 12:37:50,820 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,823 -- DEBUG: log likelihood = -111.493542
bob.learn.em@2017-11-23 12:37:50,824 -- DEBUG: convergence value = 0.000412
bob.learn.em@2017-11-23 12:37:50,824 -- INFO: EM training converged after 0 iterations with convergence value 0.000412
bob.bio.gmm@2017-11-23 12:37:50,824 -- DEBUG: .... Saving model to file '/tmp/bobtest_e7cn4d8m.hdf5'
bob.bio.gmm@2017-11-23 12:37:50,842 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,851 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,852 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,852 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,853 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,853 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,854 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,854 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,855 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,855 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,856 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,856 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,857 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,857 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,858 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,858 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,859 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,859 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,860 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,860 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,861 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,861 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,862 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,862 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,863 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,863 -- DEBUG: .... Projecting 20 feature vectors
bob.learn.em@2017-11-23 12:37:50,865 -- INFO: V subspace estimation...
bob.learn.em@2017-11-23 12:37:50,865 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,866 -- INFO: U subspace estimation...
bob.learn.em@2017-11-23 12:37:50,867 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,868 -- INFO: D subspace estimation...
bob.learn.em@2017-11-23 12:37:50,869 -- DEBUG: Iteration = 1/1
bob.bio.gmm@2017-11-23 12:37:50,879 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,880 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,880 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,881 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,881 -- DEBUG: .... Projecting 20 feature vectors
ok
bob.bio.gmm.test.test_algorithms.test_ivector_cosine ... bob.bio.gmm@2017-11-23 12:37:50,919 -- DEBUG: .... Training with 500 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,919 -- DEBUG: .... Creating machines
bob.bio.gmm@2017-11-23 12:37:50,920 -- INFO: -> Training K-Means
bob.learn.em@2017-11-23 12:37:50,921 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:50,923 -- DEBUG: average euclidean distance = 368.078425
bob.learn.em@2017-11-23 12:37:50,923 -- DEBUG: convergence value = 0.420920
bob.bio.gmm@2017-11-23 12:37:50,925 -- INFO: -> Training GMM
bob.learn.em@2017-11-23 12:37:50,930 -- DEBUG: Iteration = 1/25
bob.learn.em@2017-11-23 12:37:50,933 -- DEBUG: log likelihood = -111.493542
bob.learn.em@2017-11-23 12:37:50,934 -- DEBUG: convergence value = 0.000412
bob.learn.em@2017-11-23 12:37:50,934 -- INFO: EM training converged after 0 iterations with convergence value 0.000412
bob.bio.gmm@2017-11-23 12:37:50,934 -- INFO: -> Projecting training data
bob.bio.gmm@2017-11-23 12:37:50,935 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,936 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,937 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,938 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,939 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:50,940 -- INFO: -> Projecting training data
bob.bio.gmm@2017-11-23 12:37:50,940 -- INFO: -> Training IVector enroller
bob.learn.em@2017-11-23 12:37:50,941 -- DEBUG: Iteration = 1/1
bob.bio.gmm@2017-11-23 12:37:50,973 -- INFO: -> Training Whitening
bob.bio.gmm@2017-11-23 12:37:50,982 -- DEBUG: .... Saving model to file 'HDF5File(filename='/tmp/bobtest_4bgka4k3.hdf5')'
bob.bio.gmm@2017-11-23 12:37:51,034 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,042 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,057 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,060 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,063 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,065 -- DEBUG: .... Projecting 20 feature vectors
ok
bob.bio.gmm.test.test_algorithms.test_ivector_plda ... bob.bio.gmm@2017-11-23 12:37:51,174 -- DEBUG: .... Training with 2500 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,175 -- DEBUG: .... Creating machines
bob.bio.gmm@2017-11-23 12:37:51,177 -- INFO: -> Training K-Means
bob.learn.em@2017-11-23 12:37:51,184 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:51,190 -- DEBUG: average euclidean distance = 369.235419
bob.learn.em@2017-11-23 12:37:51,191 -- DEBUG: convergence value = 0.462682
bob.bio.gmm@2017-11-23 12:37:51,197 -- INFO: -> Training GMM
bob.learn.em@2017-11-23 12:37:51,213 -- DEBUG: Iteration = 1/25
bob.learn.em@2017-11-23 12:37:51,225 -- DEBUG: log likelihood = -111.505114
bob.learn.em@2017-11-23 12:37:51,226 -- DEBUG: convergence value = 0.000456
bob.learn.em@2017-11-23 12:37:51,226 -- INFO: EM training converged after 0 iterations with convergence value 0.000456
bob.bio.gmm@2017-11-23 12:37:51,227 -- INFO: -> Projecting training data
bob.bio.gmm@2017-11-23 12:37:51,227 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,228 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,229 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,230 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,230 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,232 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,232 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,233 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,234 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,235 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,236 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,237 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,238 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,239 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,242 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,243 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,244 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,245 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,246 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,247 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,248 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,249 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,250 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,250 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,251 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,252 -- INFO: -> Projecting training data
bob.bio.gmm@2017-11-23 12:37:51,252 -- INFO: -> Training IVector enroller
bob.learn.em@2017-11-23 12:37:51,255 -- DEBUG: Iteration = 1/1
bob.bio.gmm@2017-11-23 12:37:51,259 -- INFO: -> Training Whitening
bob.bio.gmm@2017-11-23 12:37:51,262 -- INFO: -> Training PLDA projector
bob.learn.em@2017-11-23 12:37:51,265 -- DEBUG: Iteration = 1/2
bob.learn.em@2017-11-23 12:37:51,266 -- DEBUG: Iteration = 2/2
bob.bio.gmm@2017-11-23 12:37:51,269 -- DEBUG: .... Saving model to file 'HDF5File(filename='/tmp/bobtest_srgauq6p.hdf5')'
bob.bio.gmm@2017-11-23 12:37:51,323 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,328 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,330 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,332 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,334 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,340 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,367 -- INFO: 1.218798
ok
bob.bio.gmm.test.test_algorithms.test_ivector_lda_wccn_plda ... bob.bio.gmm@2017-11-23 12:37:51,452 -- DEBUG: .... Training with 2500 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,455 -- DEBUG: .... Creating machines
bob.bio.gmm@2017-11-23 12:37:51,458 -- INFO: -> Training K-Means
bob.learn.em@2017-11-23 12:37:51,477 -- DEBUG: Iteration = 1/1
bob.learn.em@2017-11-23 12:37:51,492 -- DEBUG: average euclidean distance = 369.235419
bob.learn.em@2017-11-23 12:37:51,495 -- DEBUG: convergence value = 0.462682
bob.bio.gmm@2017-11-23 12:37:51,507 -- INFO: -> Training GMM
bob.learn.em@2017-11-23 12:37:51,544 -- DEBUG: Iteration = 1/25
bob.learn.em@2017-11-23 12:37:51,566 -- DEBUG: log likelihood = -111.505114
bob.learn.em@2017-11-23 12:37:51,567 -- DEBUG: convergence value = 0.000456
bob.learn.em@2017-11-23 12:37:51,568 -- INFO: EM training converged after 0 iterations with convergence value 0.000456
bob.bio.gmm@2017-11-23 12:37:51,569 -- INFO: -> Projecting training data
bob.bio.gmm@2017-11-23 12:37:51,569 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,571 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,573 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,574 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,575 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,576 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,578 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,579 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,580 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,583 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,585 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,586 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,587 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,588 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,589 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,592 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,593 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,595 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,596 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,597 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,598 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,601 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,603 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,604 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,605 -- DEBUG: .... Projecting 100 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,607 -- INFO: -> Projecting training data
bob.bio.gmm@2017-11-23 12:37:51,607 -- INFO: -> Training IVector enroller
bob.learn.em@2017-11-23 12:37:51,610 -- DEBUG: Iteration = 1/1
bob.bio.gmm@2017-11-23 12:37:51,615 -- INFO: -> Training Whitening
bob.bio.gmm@2017-11-23 12:37:51,618 -- INFO: -> Training LDA projector
bob.bio.gmm@2017-11-23 12:37:51,619 -- INFO: -> Training WCCN projector
bob.bio.gmm@2017-11-23 12:37:51,621 -- INFO: -> Training PLDA projector
bob.learn.em@2017-11-23 12:37:51,655 -- DEBUG: Iteration = 1/2
bob.learn.em@2017-11-23 12:37:51,656 -- DEBUG: Iteration = 2/2
bob.bio.gmm@2017-11-23 12:37:51,660 -- DEBUG: .... Saving model to file 'HDF5File(filename='/tmp/bobtest_zk0mj90r.hdf5')'
bob.bio.gmm@2017-11-23 12:37:51,779 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,806 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,810 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,812 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,813 -- DEBUG: .... Projecting 20 feature vectors
bob.bio.gmm@2017-11-23 12:37:51,814 -- DEBUG: .... Projecting 20 feature vectors
ok
bob.bio.gmm.test.test_scripts.test_gmm_parallel ... ok
bob.bio.gmm.test.test_scripts.test_isv_parallel ... ok
bob.bio.gmm.test.test_scripts.test_ivector_cosine_parallel ... ok
bob.bio.gmm.test.test_scripts.test_ivector_lda_wccn_plda_parallel ... ok
bob.bio.gmm.test.test_scripts.test_gmm_sequential ... ok
bob.bio.gmm.test.test_scripts.test_isv_sequential ... ok
bob.bio.gmm.test.test_scripts.test_ivector_cosine_sequential ... ok
bob.bio.gmm.test.test_scripts.test_ivector_lda_wccn_plda_sequential ... ok
bob.bio.gmm.test.test_scripts.test_internal_raises ... bob.bio.gmm@2017-11-23 12:57:44,134 -- ERROR: During the execution, an exception was raised: The option --iteration is an internal option and cannot be used to define experiments
bob.bio.gmm@2017-11-23 12:57:44,202 -- ERROR: During the execution, an exception was raised: The option --group is an internal option and cannot be used to define experiments; did you mean to use --groups?
bob.bio.gmm@2017-11-23 12:57:44,269 -- ERROR: During the execution, an exception was raised: The option --model-type is an internal option and cannot be used to define experiments
bob.bio.gmm@2017-11-23 12:57:44,338 -- ERROR: During the execution, an exception was raised: The option --score-type is an internal option and cannot be used to define experiments
bob.bio.gmm@2017-11-23 12:57:44,405 -- ERROR: During the execution, an exception was raised: The option --iteration is an internal option and cannot be used to define experiments
bob.bio.gmm@2017-11-23 12:57:44,473 -- ERROR: During the execution, an exception was raised: The option --group is an internal option and cannot be used to define experiments; did you mean to use --groups?
bob.bio.gmm@2017-11-23 12:57:44,540 -- ERROR: During the execution, an exception was raised: The option --model-type is an internal option and cannot be used to define experiments
bob.bio.gmm@2017-11-23 12:57:44,608 -- ERROR: During the execution, an exception was raised: The option --score-type is an internal option and cannot be used to define experiments
bob.bio.gmm@2017-11-23 12:57:44,678 -- ERROR: During the execution, an exception was raised: The option --iteration is an internal option and cannot be used to define experiments
bob.bio.gmm@2017-11-23 12:57:44,748 -- ERROR: During the execution, an exception was raised: The option --group is an internal option and cannot be used to define experiments; did you mean to use --groups?
bob.bio.gmm@2017-11-23 12:57:44,819 -- ERROR: During the execution, an exception was raised: The option --model-type is an internal option and cannot be used to define experiments
bob.bio.gmm@2017-11-23 12:57:44,888 -- ERROR: During the execution, an exception was raised: The option --score-type is an internal option and cannot be used to define experiments
ok
----------------------------------------------------------------------
Ran 16 tests in 1194.677s
OK
(bob_py3) peter@peter-Satellite-C850D:~/Downloads$
========
Please advise ,Thanks a lot in advance.
Amir Mohammadi
Nov 23, 2017, 3:49:07 PM11/23/17
to bob-...@googlegroups.com
Hi Nora,
I do not see any errors in what you have posted.nora
Nov 23, 2017, 4:39:56 PM11/23/17
to bob-devel
Hi Amir:
When I run nosetests -vs bob.bio.base,I see this message "Cannot compute FAR or FRR with threshold NaNCannot compute FAR or FRR with threshold NaN" ,also other messages below:
=====
When I run nosetests -vs bob.bio.base,I see this message "Cannot compute FAR or FRR with threshold NaNCannot compute FAR or FRR with threshold NaN" ,also other messages below:
=====
bob.bio.base.test.test_scripts.test_verify_missing ... bob.bio.base@2017-11-23 12:24:57,346 -- ERROR: There are NaN scores inside one of the score files for group dev; ZT-Norm will not work
bob.bio.base.test.test_scripts.test_internal_raises ... bob.bio.base@2017-11-23 12:25:53,275 -- ERROR: During the execution, an exception was raised: The option --group is an internal option and cannot be used to define experiments; did you mean to use --groups?
bob.bio.base@2017-11-23 12:25:53,353 -- ERROR: During the execution, an exception was raised: The option --model-type is an internal option and cannot be used to define experiments
bob.bio.base@2017-11-23 12:25:53,433 -- ERROR: During the execution, an exception was raised: The option --score-type is an internal option and cannot be used to define experiments
ok
bob.bio.base@2017-11-23 12:25:53,353 -- ERROR: During the execution, an exception was raised: The option --model-type is an internal option and cannot be used to define experiments
bob.bio.base@2017-11-23 12:25:53,433 -- ERROR: During the execution, an exception was raised: The option --score-type is an internal option and cannot be used to define experiments
ok
Ran 50 tests in 520.693s
OK
bob.c++@2017-11-23 12:26:17,090 -- ERROR: Cannot compute FAR or FRR with threshold NaNCannot compute FAR or FRR with threshold NaN
=====
OK
bob.c++@2017-11-23 12:26:17,090 -- ERROR: Cannot compute FAR or FRR with threshold NaNCannot compute FAR or FRR with threshold NaN
=====
and when I run nosetests -vs bob.bio.gmm,I see some errors shown below
=====
=====
bob.bio.gmm.test.test_scripts.test_internal_raises ... bob.bio.gmm@2017-11-23 12:57:44,134 -- ERROR: During the execution, an exception was raised: The option --iteration is an internal option and cannot be used to define experiments
bob.bio.gmm@2017-11-23 12:57:44,202 -- ERROR: During the execution, an exception was raised: The option --group is an internal option and cannot be used to define experiments; did you mean to use --groups?
bob.bio.gmm@2017-11-23 12:57:44,269 -- ERROR: During the execution, an exception was raised: The option --model-type is an internal option and cannot be used to define experiments
bob.bio.gmm@2017-11-23 12:57:44,338 -- ERROR: During the execution, an exception was raised: The option --score-type is an internal option and cannot be used to define experiments
bob.bio.gmm@2017-11-23 12:57:44,405 -- ERROR: During the execution, an exception was raised: The option --iteration is an internal option and cannot be used to define experiments
bob.bio.gmm@2017-11-23 12:57:44,473 -- ERROR: During the execution, an exception was raised: The option --group is an internal option and cannot be used to define experiments; did you mean to use --groups?
=======
Thanks
Thanks
Amir Mohammadi
Nov 24, 2017, 11:30:53 AM11/24/17
to bob-...@googlegroups.com
Hi Nora,
These are controlled errors raised during the tests. Your tests are passing. All you need to care about is the big OK word at the end of the tests.
Best,
Amir
nora
Nov 24, 2017, 1:44:57 PM11/24/17
to bob-devel
Thanks Amir ,I really appreciate your help,the next steps I suppose to do is to download the pre-trained VGG Network and wrapper script according to this website :http://vast.uccs.edu/public-data/IJCB.html and then try the experiments for face and voice .Am I on the right direction?
...
Manuel Günther
Nov 24, 2017, 2:40:44 PM11/24/17
to bob-devel
Dear Nora,
for face recognition experiments with VGG, this is the correct way to proceed. While Bob is able to run voice recognition experiments, In http://vast.uccs.edu/public-data/IJCB.html we do not perform any voice recognition experiments. Also, you will need to download one of our speaker recognition datasets (or create your own), and possibly you'll need to install bob.bio.spear. Please check https://www.idiap.ch/software/bob/docs/bob/bob.bio.spear/master/index.html for more details on speaker recognition with Bob.
For your database setup, you have to make sure that your .bob_bio_databases.txt file is inside your HOME directory. Otherwise the configuration system will not find it. The content seems to be correct.
Best regards
Manuel
nora
Nov 24, 2017, 3:23:25 PM11/24/17
to bob-devel
Thanks a lot Manuel for the useful information,I Appreciate your help,for the database I went to my Home directory and could not see .bob_bio_databases.txt so I created one and put inside the path to the atnt database (which I downloaded earlier) =====> [YOUR_ATNT_DIRECTORY]=/home/peter/Downloads/att_faces and now when I do databases.py I can see the path :
==
==
(bob_py3) peter@peter-Satellite-C850D:~/Downloads$ databases.py
atnt:
Original data: /home/peter/Downloads/att_faces
==
Thanks alot
==
Thanks alot
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