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From "ASF subversion and git services (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SINGA-251) Implement image loader for pysinga
Date Wed, 05 Oct 2016 14:15:20 GMT

    [ https://issues.apache.org/jira/browse/SINGA-251?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15548830#comment-15548830
] 

ASF subversion and git services commented on SINGA-251:
-------------------------------------------------------

Commit 17ac160258093973602eda883562b39069504fc8 in incubator-singa's branch refs/heads/master
from [~zhaojing]
[ https://git-wip-us.apache.org/repos/asf?p=incubator-singa.git;h=17ac160 ]

SINGA-251 - Implement image loader for pysinga

Add ImageBatchIter in data.py, which prefetches images into mini-batches
and pre-processes images using user defined transform function.
The process is done in another process via multiprocessing

fixed a bug in merge layer which should replicate the gradients in the returned values

To test this feature,
please prepare a train.txt file which consists of multiple lines, where each line is , e.g.

image1.jpg, 0
image2.jpg, 3
image3.jpg, 1
...
The folder should be like

SINGA ROOT/
            train.txt
            images/
                    image1.jpg
                    image2.jpg
                    ...

Then you can run python python/singa/data.py (under the root dir of singa).
After that, you should see a list of images which are transformed from the images in images/
folder.


> Implement image loader for pysinga
> ----------------------------------
>
>                 Key: SINGA-251
>                 URL: https://issues.apache.org/jira/browse/SINGA-251
>             Project: Singa
>          Issue Type: New Feature
>            Reporter: wangwei
>
> Image loading and pre-processing typically takes a long time, which would become the
bottleneck of training when loading time > BP time.
> This ticket would implement an image loader which fetches the images and conducts pre-processing
using multi-threading via multiprocessing module from python.



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