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Created with Raphaël 2.2.08Apr7131Mar30292524217Feb15141310987529Jan2726107522Dec2118171615138754330Nov282524201918131110976529Oct2813128210Sep28Aug21131131Jul7223Jun1917161510430May29282730Apr292524221429Mar96224Feb1714Jan29Oct21Jun78May716Apr5414Feb9Oct26Sep19Jul18May17161564313Apr114Mar13121110922Feb211211531Jan16105Dec4328Nov27232221134322Sep117Jul66Jun52128May23819Apr923Feb222013918Jan16151413421Dec25Nov223Oct11543218Sep161510531Aug2221209Jul7Jun4May4Apr9Mar8719Feb18529Jan2322211426Nov1929Oct12125Sep230Jun292625221918171632129May20Integrated PolaThermal datasetMerge branch 'slow-dancing' into 'master'Improved documentation of the multiPIE databaseCreated interface for CASIA-Africa databaseMerge branch 'slow-dancing' into 'master'Removing duplicated testsMerge branch 'pytest' into 'master'[conda] nose is still needed at test time because bob.bio.base test utils imports itReplace nose with pytestMerge branch 'mark-slow-tests' into 'master'[tests] Mark tensorflow tests as slowstop testing deprecated bob.db databasesAdd pyproject.toml for PEP 517Merge branch 'tf-arcface' into 'master'New baselineMerge branch 'mxnet-demanding' into 'master'Enable memory_demanding mode (samplewise processing) for MXNet modelsMerge branch 'tf-arcface' into 'master'The scoring in the LFW protocols are sparseChanged the sampleloaderForced face crops dump files in float64. In this way we can have the EXACT same results from verify.py. This was the case before. This was changed somewhere in the pipelineMerge branch 'tf-arcface' into 'master'Made the pretraining network optionalFixed issue with InceptionNetowrksIncluded two new baselinesImprovements in the arcface trainerRenamed the transformer name to be more genericChanged the default scalerPatched the 112x112 cropMerge branch 'crop' into 'master'Changed 112x112 cropChanged 112x112 face croptf-trainingtf-trainingMerge branch 'tf-training' into 'master'TF2 trainingMerge branch 'tf-training' of gitlab.idiap.ch:bob/bob.bio.face into tf-trainingUpdated --help optionUpdateUpdate TFTrainingScript that trains different angular models using different backbones[black]
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