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Posted to dev@singa.apache.org by "wangwei (JIRA)" <ji...@apache.org> on 2017/01/11 06:46:58 UTC

[jira] [Resolved] (SINGA-278) Convert trained caffe parameters to singa

     [ https://issues.apache.org/jira/browse/SINGA-278?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

wangwei resolved SINGA-278.
---------------------------
    Resolution: Fixed
      Assignee: Xiangrui

> Convert trained caffe parameters to singa
> -----------------------------------------
>
>                 Key: SINGA-278
>                 URL: https://issues.apache.org/jira/browse/SINGA-278
>             Project: Singa
>          Issue Type: New Feature
>            Reporter: Xiangrui
>            Assignee: Xiangrui
>
> Convert trained parameters of caffe model to singa.
> Run vgg as an example. Some tricks should be noticed:
> 1. The order of image axes in caffe is height, width and channels due to opencv implementation, while it is width, height, channels in singa if you use python PIL.
> 2. Another problem caused by these two libraries is the order of channels, BGR(caffe, opencv) v.s. RGB(singa, PIL).
> 3. It needs to transpose the weight tensor in InnerProduct(Dense) layer.



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