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From "ASF subversion and git services (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SINGA-278) Convert trained caffe parameters to singa
Date Fri, 23 Dec 2016 03:44:58 GMT

    [ https://issues.apache.org/jira/browse/SINGA-278?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15771779#comment-15771779
] 

ASF subversion and git services commented on SINGA-278:
-------------------------------------------------------

Commit cb81caa9290b6a8d67c2643162e5198511a0d5fc in incubator-singa's branch refs/heads/master
from [~Xiangrui]
[ https://git-wip-us.apache.org/repos/asf?p=incubator-singa.git;h=cb81caa ]

SINGA-278 Convert trained caffe parameters to singa

Convert trained parameters of caffe model to singa.
Run vgg as an example.


> 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
>
> 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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