From e7e262261b0bd3c2add0611538164f6eee5b096d Mon Sep 17 00:00:00 2001 From: Olegs NIKISINS <onikisins@italix03.idiap.ch> Date: Thu, 24 Jan 2019 10:49:32 +0100 Subject: [PATCH] Added docs on MC data extraction from WMCA for AE fine-tuning --- doc/mc_autoencoder_pad.rst | 20 ++++++++++++++++++++ 1 file changed, 20 insertions(+) diff --git a/doc/mc_autoencoder_pad.rst b/doc/mc_autoencoder_pad.rst index f59cbdf1..e3919905 100644 --- a/doc/mc_autoencoder_pad.rst +++ b/doc/mc_autoencoder_pad.rst @@ -83,6 +83,26 @@ The training procedure is explained in the **Convolutional autoencoder** section .. include:: links.rst +2. Fine-tune N AEs on multi-channel data from WMCA (legacy name BATL) database +================================================================================= + +Following the training procedure of [NGM19]_, the autoencoders are next fine-tuned on the multi-channel (**MC**) data from WMCA. +In this example, MC training data is a stack of gray-scale, NIR, and Depth (BW-NIR-D) facial images. + +To prepare the training data one can use the following command: + + +.. code-block:: sh + + ./bin/spoof.py \ # spoof.py is used to run the preprocessor + batl-db-rgb-ir-d-grandtest \ # WMCA database instance allowing to load RGB-NIR-D channels + lbp-svm \ # required by spoof.py, but unused + --skip-extractor-training --skip-extraction --skip-projector-training --skip-projection --skip-score-computation --allow-missing-files \ # execute only preprocessing step + --grid idiap \ # use grid, only for Idiap users, remove otherwise + --preprocessor video-face-crop-align-bw-ir-d-channels-3x128x128 \ # preprocessor entry point + --sub-directory <PATH_TO_STORE_THE_RESULTS> # define your path here + +Once above script is completed, the MC data suitable for autoencoder fine-tuning is located in the folder ``<PATH_TO_STORE_THE_RESULTS>/preprocessed/``. -- GitLab