Bob 2.0 implementation of ISV training (U and D subspaces)
Algorithms have at least one input and one output. All algorithm endpoints are organized in groups. Groups are used by the platform to indicate which inputs and outputs are synchronized together. The first group is automatically synchronized with the channel defined by the block in which the algorithm is deployed.
Endpoint Name  Data Format  Nature 

ubm  tutorial/gmm/1  Input 
statistics  tutorial/gmm_statistics/1  Input 
client_id  system/text/1  Input 
isvbase  tpereira/isvbase/1  Output 
Parameters allow users to change the configuration of an algorithm when scheduling an experiment
Name  Description  Type  Default  Range/Choices 

isvtrainingiterations  uint32  10  
initseed  uint32  0  
subspacedimensionofu  uint32  50  
relevancefactor  float64  4.0 
The code for this algorithm in Python
The ruler at 80 columns indicate suggested POSIX line breaks (for readability).
The editor will automatically enlarge to accomodate the entirety of your input
Use keyboard shortcuts for search/replace and faster editing. For example, use CtrlF (PC) or CmdF (Mac) to search through this box
For a Gaussian Mixture Models (GMM) mean supervector space, computes the withinclass variability subspace (U subspace) described in [McCool2013]:
This algorithm relies on the Bob library.
The inputs are:
The outputs are subspace_u and subspace_d for the session and the client offset respectivelly.
[McCool2013] 

Updated  Name  Databases/Protocols  Analyzers  

pkorshunov/pkorshunov/isvasvpadfusioncomplete/1/asv_isvpad_lbp_hist_ratios_lrfusion_lrpa_aligned  avspoof/2@physicalaccess_antispoofing,avspoof/2@physicalaccess_verification_spoof,avspoof/2@physicalaccess_verify_train_spoof,avspoof/2@physicalaccess_verify_train,avspoof/2@physicalaccess_verification  pkorshunov/spoofscorefusionroc_hist/1  
pkorshunov/pkorshunov/isvasvpadfusioncomplete/1/asv_isvpad_gmmfusion_lrpa  avspoof/2@physicalaccess_antispoofing,avspoof/2@physicalaccess_verification_spoof,avspoof/2@physicalaccess_verify_train_spoof,avspoof/2@physicalaccess_verify_train,avspoof/2@physicalaccess_verification  pkorshunov/spoofscorefusionroc_hist/1  
pkorshunov/pkorshunov/isvspeakerverificationspoof/1/isvspeakerverificationspoofpa  avspoof/2@physicalaccess_verification_spoof,avspoof/2@physicalaccess_verification  pkorshunov/eerhter_postperf_iso_spoof/1  
pkorshunov/pkorshunov/isvspeakerverification/1/isvspeakerverificationlicit  avspoof/2@physicalaccess_verification  pkorshunov/eerhter_postperf_iso/1 
This table shows the number of times this algorithm has been successfully run using the given environment. Note this does not provide sufficient information to evaluate if the algorithm will run when submitted to different conditions.