bob issueshttps://gitlab.idiap.ch/groups/bob/-/issues2017-10-21T19:07:03Zhttps://gitlab.idiap.ch/bob/bob.learn.libsvm/-/issues/8Segmentation fault when printing bob.learn.libsvm.Machine2017-10-21T19:07:03ZAndré AnjosSegmentation fault when printing bob.learn.libsvm.Machine*Created by: 183amir*
Here is the code that leads to the segmentation fault:
```python
import bob.io.base
import bob.learn.libsvm
fin = bob.io.base.HDF5File('scores/svm/regular/svm_machine.hdf5', 'r')
fin.cd('svm_machine')
s...*Created by: 183amir*
Here is the code that leads to the segmentation fault:
```python
import bob.io.base
import bob.learn.libsvm
fin = bob.io.base.HDF5File('scores/svm/regular/svm_machine.hdf5', 'r')
fin.cd('svm_machine')
svm_machine = bob.learn.libsvm.Machine(fin)
fin.cd('/')
fin.close()
print(svm_machine) # < -- it happens here!
```
Here is the back trace:
```
bin/gdb-python test.py
GNU gdb (Debian 7.7.1+dfsg-5) 7.7.1
Copyright (C) 2014 Free Software Foundation, Inc.
License GPLv3+: GNU GPL version 3 or later <http://gnu.org/licenses/gpl.html>
This is free software: you are free to change and redistribute it.
There is NO WARRANTY, to the extent permitted by law. Type "show copying"
and "show warranty" for details.
This GDB was configured as "x86_64-linux-gnu".
Type "show configuration" for configuration details.
For bug reporting instructions, please see:
<http://www.gnu.org/software/gdb/bugs/>.
Find the GDB manual and other documentation resources online at:
<http://www.gnu.org/software/gdb/documentation/>.
For help, type "help".
Type "apropos word" to search for commands related to "word"...
Reading symbols from /bob-stable/py27/bin/python...(no debugging symbols found)...done.
Starting program: /bob-stable-2016-05-09/py27/bin/python test.py
[Thread debugging using libthread_db enabled]
Using host libthread_db library "/lib/x86_64-linux-gnu/libthread_db.so.1".
[New Thread 0x7ffff1403700 (LWP 16549)]
[New Thread 0x7ffff0c02700 (LWP 16550)]
[New Thread 0x7fffee401700 (LWP 16551)]
[New Thread 0x7fffebc00700 (LWP 16552)]
[New Thread 0x7fffe93ff700 (LWP 16553)]
Program received signal SIGSEGV, Segmentation fault.
__memcpy_sse2_unaligned () at ../sysdeps/x86_64/multiarch/memcpy-sse2-unaligned.S:33
33 ../sysdeps/x86_64/multiarch/memcpy-sse2-unaligned.S: No such file or directory.
(gdb) bt
#0 __memcpy_sse2_unaligned () at ../sysdeps/x86_64/multiarch/memcpy-sse2-unaligned.S:33
#1 0x000000000047da9f in ?? ()
#2 0x00000000005e9b69 in PyUnicodeUCS4_FromFormat ()
#3 0x00007fffe209cf0a in PyBobLearnLibsvmMachine_Repr(PyBobLearnLibsvmMachineObject*) ()
from /bob-stable-2016-05-09/py27/local/lib/python2.7/site-packages/bob/learn/libsvm/_library.so
#4 0x000000000052ef8c in PyObject_Str ()
#5 0x000000000052db50 in ?? ()
#6 0x000000000052cd3b in PyFile_WriteObject ()
#7 0x00000000004d08a7 in PyEval_EvalFrameEx ()
#8 0x00000000004c87a1 in PyEval_EvalCodeEx ()
#9 0x00000000005030ef in ?? ()
#10 0x00000000004f8c72 in PyRun_FileExFlags ()
#11 0x00000000004f7d77 in PyRun_SimpleFileExFlags ()
#12 0x00000000004982f2 in Py_Main ()
#13 0x00007ffff6f12b45 in __libc_start_main (main=0x497d80 <main>, argc=2, argv=0x7fffffffdd88, init=<optimized out>, fini=<optimized out>, rtld_fini=<optimized out>, stack_end=0x7fffffffdd78)
at libc-start.c:287
#14 0x0000000000497ca0 in _start ()
```https://gitlab.idiap.ch/bob/bob.learn.libsvm/-/issues/6Error using NU_SVC machine2018-06-13T08:44:14ZAndré AnjosError using NU_SVC machine*Created by: acostapazo*
I got the following error using a trainer with machine_type=='NU_SVC'
RuntimeError: 1D `input' array should have 0 elements matching `bob.learn.libsvm.Machine' input size, not 3 elements
I tried to reprodu...*Created by: acostapazo*
I got the following error using a trainer with machine_type=='NU_SVC'
RuntimeError: 1D `input' array should have 0 elements matching `bob.learn.libsvm.Machine' input size, not 3 elements
I tried to reproduce this behaviour using the following code. Here we can observe that with random data (100 per each classes) all works in a expected way, but if I use different data, the machine that I get from the trainer seams corrupted. Take note that the machine shape is very unexpected in the second test and this produces the error.
```
import os
import numpy
numpy.random.seed(10)
import bob.learn.libsvm
def svm_predict(svm_machine, data):
labels = [svm_machine.predict_class_and_scores(x)[0][0] for x in data]
return numpy.array(labels)
def train_and_test(train_class1,train_class2,test):
svm_trainer = bob.learn.libsvm.Trainer(machine_type='NU_SVC')
svm_machine = svm_trainer.train([train_class1,train_class2])
print svm_machine.shape
pred_test = svm_predict(svm_machine,test)
return pred_test
print 'Test 1 ************************************************************'
train_class1 = 0.4 * numpy.random.randn(100, 3).astype(numpy.float64)
train_class2 = 0.6 * numpy.random.randn(100, 3).astype(numpy.float64)
test = 0.4 * numpy.random.randn(20, 3).astype(numpy.float64)
pred_test = train_and_test(train_class1,train_class2,test)
print 'Test 2 (less data) *************************************************'
train_class1 = 0.4 * numpy.random.randn(60, 3).astype(numpy.float64)
train_class2 = 0.6 * numpy.random.randn(290, 3).astype(numpy.float64)
test = 0.4 * numpy.random.randn(20, 3).astype(numpy.float64)
pred_test = train_and_test(train_class1,train_class2,test)
```https://gitlab.idiap.ch/bob/bob.learn.em/-/issues/5division by zero2017-08-12T07:46:06ZAndré Anjosdivision by zero*Created by: khoury*
In train.py, a division by zero error occurred at line 53:
```py
if convergence_threshold!=None and abs((average_output_previous - average_output)/average_output_previous) <= convergence_threshold:
```
in case...*Created by: khoury*
In train.py, a division by zero error occurred at line 53:
```py
if convergence_threshold!=None and abs((average_output_previous - average_output)/average_output_previous) <= convergence_threshold:
```
in case `convergence_threshold` is not None and the trainer does not contain a `compute_likelihood` attribute.https://gitlab.idiap.ch/bob/bob.learn.linear/-/issues/3Regularization-parameter lambda for CGLogRegTrainer-constructor is python res...2017-10-22T20:35:42ZAndré AnjosRegularization-parameter lambda for CGLogRegTrainer-constructor is python reserved-word*Created by: skbidiap*
When I try to use the regularization parameter, using something like:
bob.learn.linear.CGLogRegTrainer(prior=0.5, lambda=0.001)
I get an error message from Python: SyntaxError: invalid syntax
because the par...*Created by: skbidiap*
When I try to use the regularization parameter, using something like:
bob.learn.linear.CGLogRegTrainer(prior=0.5, lambda=0.001)
I get an error message from Python: SyntaxError: invalid syntax
because the parameter-name 'lambda' matches the python keyword 'lambda'.https://gitlab.idiap.ch/bob/bob.learn.libsvm/-/issues/4ONE-CLASS SVM is not supported2017-10-21T19:07:03ZAndré AnjosONE-CLASS SVM is not supported*Created by: acostapazo*
It would be interesting that the package had implemented this feature. It will allow us to train svm machines using only one class data.
I am going to fork the repo in order to submit a pull-request for OC-SV...*Created by: acostapazo*
It would be interesting that the package had implemented this feature. It will allow us to train svm machines using only one class data.
I am going to fork the repo in order to submit a pull-request for OC-SVM support.
https://gitlab.idiap.ch/bob/bob.learn.em/-/issues/4Wrong error return in BOB_CATCH_MEMBER2017-08-12T07:46:06ZAndré AnjosWrong error return in BOB_CATCH_MEMBER*Created by: siebenkopf*
It appears that for some functions, the error return is ``-1`` and not ``NULL``. Usually, those functions return ``int`` and not ``PyObject*``. Particularly, this is the case for the constructors such as:
https...*Created by: siebenkopf*
It appears that for some functions, the error return is ``-1`` and not ``NULL``. Usually, those functions return ``int`` and not ``PyObject*``. Particularly, this is the case for the constructors such as:
https://github.com/bioidiap/bob.learn.em/blob/master/bob/learn/em/kmeans_trainer.cpp#L119
and for the setter functions such as:
https://github.com/bioidiap/bob.learn.em/blob/master/bob/learn/em/kmeans_trainer.cpp#L257
This means that the second value in the ``BOB_CATCH_MEMBER`` construct needs to be ``-1`` and not ``NULL`` (aka. ``0``).
@tiagofrepereira2012: could you go through all the files and assure that the error return is correct?https://gitlab.idiap.ch/bob/bob.learn.linear/-/issues/1reference for Focal (in logistic regression) is outdated2017-10-22T20:35:42ZAndré Anjosreference for Focal (in logistic regression) is outdated*Created by: khoury*
Hello,
The current webpage for Focal is:
https://sites.google.com/site/nikobrummer/focal
instead of:
http://www.dsp.sun.ac.za/~nbrummer/focal/
Cheers,
Elie
*Created by: khoury*
Hello,
The current webpage for Focal is:
https://sites.google.com/site/nikobrummer/focal
instead of:
http://www.dsp.sun.ac.za/~nbrummer/focal/
Cheers,
Elie
https://gitlab.idiap.ch/bob/bob.learn.libsvm/-/issues/3Regression using SVM is not supported2018-06-05T07:59:22ZAndré AnjosRegression using SVM is not supported*Created by: tiagofrepereira2012*
Issue copied from here: https://github.com/idiap/bob/issues/182
#################
@laurentes
We should either update the documentation and remove options such as NU_SVR, or support the regressio...*Created by: tiagofrepereira2012*
Issue copied from here: https://github.com/idiap/bob/issues/182
#################
@laurentes
We should either update the documentation and remove options such as NU_SVR, or support the regression task correctly.
@anjos
Supporting a regression task could be easily patched by adding another method to the class called double regress(const blitz::Array<double,1>& input).
To make that clean, one would need to check for NU_SVR || EPSILON_SVR all over the place to make sure the user is not trying to predict classes with a regression SVM.
Another alternative (I'm not sure that would be better) would be to create two inherited classes ClassificationSupportVector and RegressionSupportVector, which only contain specific methods for those tasks, avoiding the excessive checking. All common functionality remains in SupportVector.
Please share your thoughts.https://gitlab.idiap.ch/bob/bob.learn.em/-/issues/3KMeans returns NaNs2022-02-11T15:08:46ZAndré AnjosKMeans returns NaNs*Created by: siebenkopf*
I have lately run into a problem, where the ``bob.learn.em.KMeansTrainer`` returns a machine, where some of the means are ``nan``. I have enough training data (several millions), and I want to have 1000 means.
...*Created by: siebenkopf*
I have lately run into a problem, where the ``bob.learn.em.KMeansTrainer`` returns a machine, where some of the means are ``nan``. I have enough training data (several millions), and I want to have 1000 means.
I guess that this problem is related to the fact that some means are under-represented with data (i.e., no data point is assigned for a specific mean). Then, re-computing the means will end up in a division by zero, which turns into ``nan`` values.
To avoid that, it is possible to re-initialize the under-represented mean by selecting the data point that is furthest away from the (other) current means, something like:
```py
# get the maximum distance
furthest_training_sample = numpy.argmax([max(distance(data, mean) for mean in means) for data in training_data])
# assign new mean
new_mean = training_data[furthest_training_sample]
```https://gitlab.idiap.ch/bob/bob.learn.libsvm/-/issues/2Number of support vectors for a SVM model2017-10-21T19:07:03ZAndré AnjosNumber of support vectors for a SVM model*Created by: tiagofrepereira2012*
Today is not possible to check the number of support vectors using the bob.learn.libsvm.Machine class.
Would be useful to have this feature.*Created by: tiagofrepereira2012*
Today is not possible to check the number of support vectors using the bob.learn.libsvm.Machine class.
Would be useful to have this feature.https://gitlab.idiap.ch/bob/bob.learn.em/-/issues/2Compute the log likelihood blitz::Array<double, 2> - GMMMachine2022-02-11T15:08:31ZAndré AnjosCompute the log likelihood blitz::Array<double, 2> - GMMMachine*Created by: tiagofrepereira2012*
Would be nice in the ``bob::learn::em::GMMMachine`` to have a ``logLikelihood`` method that takes a ``blitz::Array<double, 2>`` as input and not only ``blitz::Array<double, 1>``.*Created by: tiagofrepereira2012*
Would be nice in the ``bob::learn::em::GMMMachine`` to have a ``logLikelihood`` method that takes a ``blitz::Array<double, 2>`` as input and not only ``blitz::Array<double, 1>``.https://gitlab.idiap.ch/bob/bob.learn.libsvm/-/issues/1Failing (crashing) nosetests in debug mode2017-10-21T19:07:03ZAndré AnjosFailing (crashing) nosetests in debug mode*Created by: siebenkopf*
When compiled in debug mode, the following nose test:
``` sh
$ bin/nosetests bob.learn.libsvm.test_machine:test_data_loading -vs
```
will crash with a:
``` sh
[Blitz++] Precondition failure: Module /remo...*Created by: siebenkopf*
When compiled in debug mode, the following nose test:
``` sh
$ bin/nosetests bob.learn.libsvm.test_machine:test_data_loading -vs
```
will crash with a:
``` sh
[Blitz++] Precondition failure: Module /remote/idiap.svm/group.torch5spro/externals/py27-debug/usr/include/blitz/array/slicing.cc line 303
Slice is out of range for array: index=270 rank=0
Possible range for index: [0, 269]
python: /remote/idiap.svm/group.torch5spro/externals/py27-debug/usr/include/blitz/array/slicing.cc:303: void blitz::Array<P_numtype, N_rank>::slice(int&, int, blitz::Array<P_numtype, N_rank2>&, blitz::TinyVector<int, N_rank>&, int) [with int N_rank2 = 2; P_numtype = double; int N_rank = 1]: Assertion `0' failed.
Aborted
```
The issue seems to be located in https://github.com/bioidiap/bob.learn.libsvm/blob/master/bob/learn/libsvm/file.cpp#L492, where the k index is getting too high.
To reproduce the issue, checkout bob.learn.libsvm, bootstrap with the debug python version, e.g.:
``` sh
$ /idiap/group/torch5spro/externals/py27-debug/usr/bin/python bootstrap-buildout.py
```
and run the command above.
Happy debugging!https://gitlab.idiap.ch/bob/bob.learn.em/-/issues/1Precomputation of cached matrices in IVectorMachine can't be disabled2022-04-27T20:17:11ZAndré AnjosPrecomputation of cached matrices in IVectorMachine can't be disabled*Created by: laurentes*
[originally posted on the bob-devel mailing list]
Creating an IVectorMachine object using an externally-computed T matrix is very slow.
With a 400x2048x38 TVM in a 250mb binary file, and its matching UBM in anot...*Created by: laurentes*
[originally posted on the bob-devel mailing list]
Creating an IVectorMachine object using an externally-computed T matrix is very slow.
With a 400x2048x38 TVM in a 250mb binary file, and its matching UBM in another binary file, loading the UBM in a GMMMachine is fine (this takes less than a second). But loading the TVM into a new IVectorMachine takes >8 hours using the 2.0 C++ API.
The IVectorMachine class is doing some premature precomputation. For example, just calling the constructor with the GMMMachine takes a very long time, precomputing arrays that will have to be discarded since the constructor doesn't even know the T matrix yet.
Currently, it is not possible to create an empty IVectorMachine() and then set the UBM and T matrix, because of the assertion in the setT method that requires the dimension to match the uninitialized m_t.
A suggestion would be that IVectorMachine's precomputation policy change to precompute-on-demand. That is, during initialization or after any parameter change, just set a flag indicating that precomputation is required; but do not actually do the precomputation until forward() is called.https://gitlab.idiap.ch/bob/bob.learn.activation/-/issues/1Problem Setting up bob.learn.activation 2.0.22017-08-21T07:54:19ZAndré AnjosProblem Setting up bob.learn.activation 2.0.2*Created by: ozgurdenizonur*
I have a ubuntu 12.04 box.
I have installed all the dependencies as specified in Bob install page. However I am getting the following error when I run the buildout file of facereclib. What am I missing?
...*Created by: ozgurdenizonur*
I have a ubuntu 12.04 box.
I have installed all the dependencies as specified in Bob install page. However I am getting the following error when I run the buildout file of facereclib. What am I missing?
Reading configuration from /tmp/easy_install-7hbZYP/bob.learn.activation-2.0.2/setup.cfg
Adding new section [easy_install] to /tmp/easy_install-7hbZYP/bob.learn.activation-2.0.2/setup.cfg
Writing /tmp/easy_install-7hbZYP/bob.learn.activation-2.0.2/setup.cfg
Running bob.learn.activation-2.0.2/setup.py bdist_egg --dist-dir /tmp/easy_install-7hbZYP/bob.learn.activation-2.0.2/egg-dist-tmp-RigeNu
error: None
bob.buildout.extension: An error occurred when trying to install bob.learn.activation 2.0.2. Look above this message for any errors that were output by easy_install.
While:
Installing scripts.
Getting distribution for 'bob.learn.em'.
Getting distribution for 'bob.learn.activation'.
Error: Couldn't install: bob.learn.activation 2.0.2
https://gitlab.idiap.ch/bob/bob.ip.flandmark/-/issues/6Documentation for example in user-guide refers to get_file() that does not exist2020-04-28T07:22:47ZAndré AnjosDocumentation for example in user-guide refers to get_file() that does not exist*Created by: skbidiap*
See documentation here: http://pythonhosted.org/bob.ip.flandmark/guide.html*Created by: skbidiap*
See documentation here: http://pythonhosted.org/bob.ip.flandmark/guide.htmlSushil BHATTACHARJEESushil BHATTACHARJEEhttps://gitlab.idiap.ch/bob/bob.ip.flandmark/-/issues/5OpenCV 3.0 compatability2017-10-21T02:48:13ZAndré AnjosOpenCV 3.0 compatability*Created by: jhochenbaum*
This error is mostly related to the flandmarks package but I there are some minor incompatibilities with the most recent stable build of opencv, OpenCV 3.0. In fact these issues have existed on the git tip for ...*Created by: jhochenbaum*
This error is mostly related to the flandmarks package but I there are some minor incompatibilities with the most recent stable build of opencv, OpenCV 3.0. In fact these issues have existed on the git tip for some time, though the release finally moved to the stable version so it's probably time to address them. I think this is mostly do to the fact that OpenCV has moved from the old c/cv syntax to c++/cv2 (a transition that started a long time ago), and that they are no longer going to support cv.
In any case, when building bob.ip.flandmark "cvaux.h" thrown an error -- I managed to get around this by commenting out the #include of cvaux.h in bob/ip/flandmark/flandmark_detector.h -- which seemed to do the trick, though I haven't been able to fully test yet as I'm working through other issues with the new bob 2.0 packaging scheme.
See below
======================
In file included from /usr/local/include/opencv/cvaux.h:56:0,
from bob/ip/flandmark/flandmark_detector.h:16,
from bob/ip/flandmark/flandmark_detector.cpp:17:
/usr/local/include/opencv2/legacy.hpp:1749:53: error: ‘cv::EM’ has not been declared
CvEMParams( int nclusters, int cov_mat_type=cv::EM::COV_MAT_DIAGONAL,
^
/usr/local/include/opencv2/legacy.hpp:1750:36: error: ‘cv::EM’ has not been declared
int start_step=cv::EM::START_AUTO_STEP,
^
/usr/local/include/opencv2/legacy.hpp:1766:1: error: expected class-name before ‘{’ token
{
^
/usr/local/include/opencv2/legacy.hpp:1769:34: error: ‘cv::EM’ has not been declared
enum { COV_MAT_SPHERICAL=cv::EM::COV_MAT_SPHERICAL,
^
/usr/local/include/opencv2/legacy.hpp:1770:34: error: ‘cv::EM’ has not been declared
COV_MAT_DIAGONAL =cv::EM::COV_MAT_DIAGONAL,
^
/usr/local/include/opencv2/legacy.hpp:1771:34: error: ‘cv::EM’ has not been declared
COV_MAT_GENERIC =cv::EM::COV_MAT_GENERIC };
^
/usr/local/include/opencv2/legacy.hpp:1774:29: error: ‘cv::EM’ has not been declared
enum { START_E_STEP=cv::EM::START_E_STEP,
^
/usr/local/include/opencv2/legacy.hpp:1775:29: error: ‘cv::EM’ has not been declared
START_M_STEP=cv::EM::START_M_STEP,
^
/usr/local/include/opencv2/legacy.hpp:1776:32: error: ‘cv::EM’ has not been declared
START_AUTO_STEP=cv::EM::START_AUTO_STEP };
^
/usr/local/include/opencv2/legacy.hpp:1824:5: error: ‘EM’ in namespace ‘cv’ does not name a type
cv::EM emObj;
^
/usr/local/include/opencv2/legacy.hpp: In member function ‘double CvEM::getLikelihood() const’:
/usr/local/include/opencv2/legacy.hpp:1806:58: error: ‘emObj’ was not declared in this scope
CV_WRAP inline double getLikelihood() const { return emObj.isTrained() ? logLikelihood : DBL_MAX; }
^
/usr/local/include/opencv2/legacy.hpp: At global scope:
/usr/local/include/opencv2/legacy.hpp:2621:1: error: expected class-name before ‘{’ token
{
^
/usr/local/include/opencv2/legacy.hpp:2666:17: error: ‘GenericDescriptorMatcher’ was not declared in this scope
virtual Ptr<GenericDescriptorMatcher> clone( bool emptyTrainData=false ) const;
^
/usr/local/include/opencv2/legacy.hpp:2666:41: error: template argument 1 is invalid
virtual Ptr<GenericDescriptorMatcher> clone( bool emptyTrainData=false ) const;
^
/usr/local/include/opencv2/legacy.hpp:2694:1: error: expected class-name before ‘{’ token
{
^
/usr/local/include/opencv2/legacy.hpp:2735:17: error: ‘GenericDescriptorMatcher’ was not declared in this scope
virtual Ptr<GenericDescriptorMatcher> clone( bool emptyTrainData=false ) const;
^
/usr/local/include/opencv2/legacy.hpp:2735:41: error: template argument 1 is invalid
virtual Ptr<GenericDescriptorMatcher> clone( bool emptyTrainData=false ) const;
^
error: command 'x86_64-linux-gnu-gcc' failed with exit status 1
In file included from /usr/local/include/opencv/cvaux.h:56:0,
from bob/ip/flandmark/flandmark_detector.h:16,
from bob/ip/flandmark/flandmark.cpp:20:
/usr/local/include/opencv2/legacy.hpp:1749:53: error: ‘cv::EM’ has not been declared
CvEMParams( int nclusters, int cov_mat_type=cv::EM::COV_MAT_DIAGONAL,
^
/usr/local/include/opencv2/legacy.hpp:1750:36: error: ‘cv::EM’ has not been declared
int start_step=cv::EM::START_AUTO_STEP,
^
/usr/local/include/opencv2/legacy.hpp:1766:1: error: expected class-name before ‘{’ token
{
^
/usr/local/include/opencv2/legacy.hpp:1769:34: error: ‘cv::EM’ has not been declared
enum { COV_MAT_SPHERICAL=cv::EM::COV_MAT_SPHERICAL,
^
/usr/local/include/opencv2/legacy.hpp:1770:34: error: ‘cv::EM’ has not been declared
COV_MAT_DIAGONAL =cv::EM::COV_MAT_DIAGONAL,
^
/usr/local/include/opencv2/legacy.hpp:1771:34: error: ‘cv::EM’ has not been declared
COV_MAT_GENERIC =cv::EM::COV_MAT_GENERIC };
^
/usr/local/include/opencv2/legacy.hpp:1774:29: error: ‘cv::EM’ has not been declared
enum { START_E_STEP=cv::EM::START_E_STEP,
^
/usr/local/include/opencv2/legacy.hpp:1775:29: error: ‘cv::EM’ has not been declared
START_M_STEP=cv::EM::START_M_STEP,
^
/usr/local/include/opencv2/legacy.hpp:1776:32: error: ‘cv::EM’ has not been declared
START_AUTO_STEP=cv::EM::START_AUTO_STEP };
^
/usr/local/include/opencv2/legacy.hpp:1824:5: error: ‘EM’ in namespace ‘cv’ does not name a type
cv::EM emObj;
^
/usr/local/include/opencv2/legacy.hpp: In member function ‘double CvEM::getLikelihood() const’:
/usr/local/include/opencv2/legacy.hpp:1806:58: error: ‘emObj’ was not declared in this scope
CV_WRAP inline double getLikelihood() const { return emObj.isTrained() ? logLikelihood : DBL_MAX; }
^
/usr/local/include/opencv2/legacy.hpp: At global scope:
/usr/local/include/opencv2/legacy.hpp:2621:1: error: expected class-name before ‘{’ token
{
^
/usr/local/include/opencv2/legacy.hpp:2666:17: error: ‘GenericDescriptorMatcher’ was not declared in this scope
virtual Ptr<GenericDescriptorMatcher> clone( bool emptyTrainData=false ) const;
^
/usr/local/include/opencv2/legacy.hpp:2666:41: error: template argument 1 is invalid
virtual Ptr<GenericDescriptorMatcher> clone( bool emptyTrainData=false ) const;
^
/usr/local/include/opencv2/legacy.hpp:2694:1: error: expected class-name before ‘{’ token
{
^
/usr/local/include/opencv2/legacy.hpp:2735:17: error: ‘GenericDescriptorMatcher’ was not declared in this scope
virtual Ptr<GenericDescriptorMatcher> clone( bool emptyTrainData=false ) const;
^
/usr/local/include/opencv2/legacy.hpp:2735:41: error: template argument 1 is invalid
virtual Ptr<GenericDescriptorMatcher> clone( bool emptyTrainData=false ) const;
^
While:
Installing.
Processing develop directory '/home/jordan/bob.ip.flandmark/.'.
An internal error occurred due to a bug in either zc.buildout or in a
recipe being used:
Traceback (most recent call last):
File "/home/jordan/bob.ip.flandmark/eggs/zc.buildout-2.2.1-py3.4.egg/zc/buildout/buildout.py", line 1942, in main
getattr(buildout, command)(args)
File "/home/jordan/bob.ip.flandmark/eggs/zc.buildout-2.2.1-py3.4.egg/zc/buildout/buildout.py", line 484, in install
installed_develop_eggs = self._develop()
File "/home/jordan/bob.ip.flandmark/eggs/zc.buildout-2.2.1-py3.4.egg/zc/buildout/buildout.py", line 726, in _develop
zc.buildout.easy_install.develop(setup, dest)
File "/home/jordan/bob.ip.flandmark/eggs/bob.buildout-0.4.8-py3.4.egg/bob/buildout/extension.py", line 242, in develop
zc.buildout.easy_install.call_subprocess(args)
File "/home/jordan/bob.ip.flandmark/eggs/zc.buildout-2.2.1-py3.4.egg/zc/buildout/easy_install.py", line 154, in call_subprocess
% repr(args)[1:-1])
Exception: Failed to run command:
'/usr/bin/python3', '/tmp/tmp124cbdgu', '-v', 'develop', '-mxN', '-d', '/home/jordan/bob.ip.flandmark/develop-eggs/tmp_9c84ih6build'
https://gitlab.idiap.ch/bob/bob.ip.flandmark/-/issues/4The returned landmarks are not in the default order of Bob2017-10-21T02:48:13ZAndré AnjosThe returned landmarks are not in the default order of Bob*Created by: siebenkopf*
The landmarks that are returned by the ``localize()`` function are given in (x,y) order, while the order in Bob is usually (y,x).
Interestingly, the second ``localizer(top, left, height, width)`` function acce...*Created by: siebenkopf*
The landmarks that are returned by the ``localize()`` function are given in (x,y) order, while the order in Bob is usually (y,x).
Interestingly, the second ``localizer(top, left, height, width)`` function accepts the parameters in the right order, but return landmarks in non-Bob-conform order.https://gitlab.idiap.ch/bob/bob.ip.facedetect/-/issues/3Online documentation incomplete2017-08-11T20:22:32ZAndré AnjosOnline documentation incomplete*Created by: siebenkopf*
Hi,
the stable version of the documentation (on pythonhosted) is incomplete:
http://pythonhosted.org/bob.ip.facedetect/py_api.html
@tiagofrepereira2012 I assume that you uploaded that with the new ``new_v...*Created by: siebenkopf*
Hi,
the stable version of the documentation (on pythonhosted) is incomplete:
http://pythonhosted.org/bob.ip.facedetect/py_api.html
@tiagofrepereira2012 I assume that you uploaded that with the new ``new_version.py`` script, i.e., without rebuilding the package. Now you might understand, why I am not in favor of the new version of that script.https://gitlab.idiap.ch/bob/bob.extension/-/issues/18Sphinx uploading wrongly reports "wheels"2017-08-11T22:23:18ZAndré AnjosSphinx uploading wrongly reports "wheels"*Created by: anjos*
A small detail, when the program "uplolad-sphinx.sh" operates, it reports it is uploading a "wheel" instead. Comment should be fixed:
```text
$ ./upload-sphinx.sh
Detected branch '* (detached from 985da30)
ma...*Created by: anjos*
A small detail, when the program "uplolad-sphinx.sh" operates, it reports it is uploading a "wheel" instead. Comment should be fixed:
```text
$ ./upload-sphinx.sh
Detected branch '* (detached from 985da30)
master' to be master branch -- uploading wheel to Idiap servers
```https://gitlab.idiap.ch/bob/bob.ip.facedetect/-/issues/1The URL of this package is wrong2017-08-11T20:22:32ZAndré AnjosThe URL of this package is wrong*Created by: anjos*
On `setup.py`. As a result, the PyPI link to here is broken.*Created by: anjos*
On `setup.py`. As a result, the PyPI link to here is broken.