MXNET-650 [Perl] Gluon ModelZoo, Gluon examples #11642
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@tlby |
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| GetOptions( | ||
| ## my Pembroke Welsh Corgi Kyuubi, enjoing Solar eclipse of August 21, 2017 | ||
| 'image=s' => \(my $image = 'https://scontent-sea1-1.cdninstagram.com/vp/'. |
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😆
How long does this pic persist on the CDN of instagram? Will the link expire?
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@szha I am not sure.
But I'll be glad if I can put this image on mxnet data server. Besides that I have a few blog posts that I want in future to have added as a tutorials for perl api
http://blogs.perl.org/users/sergey_kolychev/, they do contain some images and data files that would be nice to have on mxnet data server as well.
I'll be writing new blog post soon announcing ModelZoo for perl and I'll use images from https://www.facebook.com/sergey.kolychev.39/posts/10155737425303434.
Can you help me with putting these images/data files to the server ?
Or may be I can get a write access somehow so I'll not bother you with this ?
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http://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/dataset/kyuubi_blacksquare.jpg
http://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/dataset/kyuubi_mural.jpg
http://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/dataset/kyuubi_dali.jpg
http://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/dataset/kyuubi_starry.jpg
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@szha Thank you! I'll update the file with new uri. When you have time could you, please, upload the images from that facebook post as well ? I'll then change stock images with Kyuubi's images for the style transfer example cause they are quite a bit cutier :-) |
…my cute dog. optimized image_classification.pl script a bit.
…) to provide consistence in the loss tests.
* MXNET-650 1) Added Gluon Contrib modules 2) Added Gluon Model Zoo 3) Added Gluon image classification and style transfer examples 4) Miscellaneous bugfixes and improvements. * added license. * a few typos/bugfix/doc improvement. * switched default images for the style transfer example for images of my cute dog. optimized image_classification.pl script a bit. * fixed readme. * using static seed in the perl space as well (shiffling in NDArrayIter) to provide consistence in the loss tests. * additional pythonification.
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