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Linshizhi
ffmpeg.wasm-core
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4f8e65c4
Commit
4f8e65c4
authored
Aug 15, 2018
by
Sergey Lavrushkin
Committed by
Gyan Doshi
Aug 15, 2018
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doc/filters: Add entry for sr filter.
Signed-off-by:
Gyan Doshi
<
ffmpeg@gyani.pro
>
parent
67599812
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@@ -15403,6 +15403,65 @@ option may cause flicker since the B-Frames have often larger QP. Default is
@code{0} (not enabled).
@end table
@section sr
Scale the input by applying one of the super-resolution methods based on
convolutional neural networks.
Training scripts as well as scripts for model generation are provided in
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:
@table @samp
@item native
Native implementation of DNN loading and execution.
@item tensorflow
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
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.
@end table
@anchor{subtitles}
@section subtitles
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