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libavfilter: Removes stored DNN models. Adds support for native backend model file format in tf backend.

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Signed-off-by: Pedro Arthur <bygrandao@gmail.com>
This commit is contained in:
Sergey Lavrushkin
2018-09-06 14:33:06 +03:00
committed by Pedro Arthur
parent bc1097a2bf
commit bd10c1e9a8
10 changed files with 317 additions and 8000 deletions
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doc/filters.texi
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@@ -15593,7 +15593,17 @@ option may cause flicker since the B-Frames have often larger QP. Default is
@section sr
Scale the input by applying one of the super-resolution methods based on
convolutional neural networks.
convolutional neural networks. Supported models:
@itemize
@item
Super-Resolution Convolutional Neural Network model (SRCNN).
See @url{https://arxiv.org/abs/1501.00092}.
@item
Efficient Sub-Pixel Convolutional Neural Network model (ESPCN).
See @url{https://arxiv.org/abs/1609.05158}.
@end itemize
Training scripts as well as scripts for model generation are provided in
the repository at @url{https://github.com/HighVoltageRocknRoll/sr.git}.
@@ -15601,22 +15611,6 @@ the repository at @url{https://github.com/HighVoltageRocknRoll/sr.git}.
The filter accepts the following options:
@table @option
@item model
Specify which super-resolution model to use. This option accepts the following values:
@table @samp
@item srcnn
Super-Resolution Convolutional Neural Network model.
See @url{https://arxiv.org/abs/1501.00092}.
@item espcn
Efficient Sub-Pixel Convolutional Neural Network model.
See @url{https://arxiv.org/abs/1609.05158}.
@end table
Default value is @samp{srcnn}.
@item dnn_backend
Specify which DNN backend to use for model loading and execution. This option accepts
the following values:
@@ -15630,23 +15624,20 @@ TensorFlow backend. To enable this backend you
need to install the TensorFlow for C library (see
@url{https://www.tensorflow.org/install/install_c}) and configure FFmpeg with
@code{--enable-libtensorflow}
@end table
Default value is @samp{native}.
@item scale_factor
Set scale factor for SRCNN model, for which custom model file was provided.
Allowed values are @code{2}, @code{3} and @code{4}. Default value is @code{2}.
Scale factor is necessary for SRCNN model, because it accepts input upscaled
using bicubic upscaling with proper scale factor.
@item model_filename
@item model
Set path to model file specifying network architecture and its parameters.
Note that different backends use different file formats. TensorFlow backend
can load files for both formats, while native backend can load files for only
its format.
@item scale_factor
Set scale factor for SRCNN model. Allowed values are @code{2}, @code{3} and @code{4}.
Default value is @code{2}. Scale factor is necessary for SRCNN model, because it accepts
input upscaled using bicubic upscaling with proper scale factor.
@end table
@anchor{subtitles}