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From "Xiangrui (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SINGA-278) Convert trained caffe parameters to singa
Date Sat, 03 Dec 2016 03:19:59 GMT

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

Xiangrui updated SINGA-278:
---------------------------
    Description: 
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.

  was:
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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