[FFmpeg-devel] [PATCH 2/2] convert_from_tensorflow.py: support conv2d with dilation

[Guo, Yejun]

> -----Original Message-----
> From: ffmpeg-devel [mailto:ffmpeg-devel-bounces at ffmpeg.org] On Behalf Of
> Pedro Arthur
> Sent: Wednesday, August 14, 2019 12:09 AM
> To: FFmpeg development discussions and patches <ffmpeg-devel at ffmpeg.org>
> Subject: Re: [FFmpeg-devel] [PATCH 2/2] convert_from_tensorflow.py: support
> conv2d with dilation
> 
> LGTM.
> Should push soon.

thanks.

> 
> BTW I just noticed that the tensorflow backend is failling to load SR
> filter models.
> 
> $ python tools/python/convert.py sr_models/srcnn.pb
> $ ./ffmpeg -i input.jpg -vf
> sr=model=srcnn.model:dnn_backend=tensorflow out_srcnn_tf.png
> 
> The above command fails.
> It seems commit ccbab41039af424237eaac5c302c293ab97540f8 is the
> problem. I thought I had tested it but clearly I made a mistake
> somewhere in the process.
> I suppose you have the .pb files to test it, but let me know if you need them.

yes, I have the .pb files. I missed the patch for such support. Will refine and send out soon.


> 
> Em sex, 9 de ago de 2019 às 12:25, Guo, Yejun <yejun.guo at intel.com>
> escreveu:
> >
> >
> >
> > > -----Original Message-----
> > > From: Guo, Yejun
> > > Sent: Tuesday, July 30, 2019 9:26 AM
> > > To: ffmpeg-devel at ffmpeg.org
> > > Cc: Guo, Yejun <yejun.guo at intel.com>
> > > Subject: [PATCH 2/2] convert_from_tensorflow.py: support conv2d with
> dilation
> > >
> > > conv2d with dilation > 1 generates tens of nodes in graph, it is not
> > > easy to parse each node one by one, so we do special tricks to parse
> > > the conv2d layer.
> > >
> > > Signed-off-by: Guo, Yejun <yejun.guo at intel.com>
> > > ---
> > >  tools/python/convert_from_tensorflow.py | 80
> > > ++++++++++++++++++++++++---------
> > >  1 file changed, 59 insertions(+), 21 deletions(-)
> >
> > this patch set asks for review, thanks.
> >
> > I've locally finished more patches to improve dnn module, plan to send more
> them set by set, since the patches have dependency.
> >
> > Just in case you are interested in these new patches, I've uploaded to
> https://github.com/guoyejun/ffmpeg/tree/dnn0809.
> > for your convenient, I also copy the oneline log here for each patch (from
> newer to older) with 4 patch sets.
> >
> > 7eced90 libavfilter/dnn: support multiple outputs for native mode
> > 28a7054 libavfilter/dnn/dnn_backend_native: find the input operand
> according to input name
> >
> > 256e657 FATE/dnn: add unit test for layer maximum
> > 8c616a0 libavfilter/dnn: add layer maximum for native mode.
> >
> > 8ec6c0c FATE/dnn: add unit test for dnn depth_to_space layer
> > 09ef108 libavfilter/dnn: separate depth_to_space layer from
> dnn_backend_native.c to a new file
> > c65b59d FATE/dnn: add unit test for dnn conv2d layer
> > a5d69a7 libavfilter/dnn: separate conv2d layer from dnn_backend_native.c to
> a new file
> >
> > 202d323 dnn: export operand info in python script and load in c code
> > 3c706a0 dnn: change .model file format to put layer number at the end of file
> > 0256731 dnn: introduce dnn operand (in c code) to hold operand infos within
> network
> >
> >
> > Besides continuous dnn improvement, I also plan to add two generic video
> filters for dnn.
> > - a generic filter to process the content of AVFrame with different dnn
> networks.
> > and so the current specific filters such as vf_sr (some changes needed) and
> vf_derain are no longer needed, since they can be
> > included in this specific filter. And of course, in practice I'll not remove them.
> >
> > - a generic filter to analyze the content of AVFrame to generate some side
> data with different dnn networks. The content of AVFrame does not change.
> > The application, which invokes the filter with a given dnn network, has the
> responsibility/knowledge to parse the side data (analyze result).
> >
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