Added a data layer type where the crop is allowed to be rectangular rather than square.
Added a data layer type where the crop is allowed to be rectangular rather than square.
Integrated my regression and rectangular data and loss layers into boost branch.
Updated regression-related layers.  Not yet tested.
Initial DeepPose contribution.
Updated DeepPose script files.
Added script for downloading lsp.
Initial lsp build script.
Fixed a path bug for build LSP database script.  Added LSP database inspection script.
Fixed a path bug for DeepPose input database.
Check to make sure the iterator is valid.
Removed hardcoded labels size
Merge branch 'boost-eigen' of https://github.com/kmatzen/caffe into boost-eigen
Fixed some mistakes with the DeepPose net definition.
Refactored regression components so that weights are a separate output for the data layer and separate input for the loss layer.:
I think this is just about there for the regression implementation.
More DeepPose tweaks to use pretrained ImageNet result.
Weighted Euclidean loss layer now reports mean absolute error.
More DeepPose parameter tweaks.
Removing 28's from code, substituted for nLabels