diff options
| author | Guo, Yejun <yejun.guo@intel.com> | 2020-02-21 20:40:07 +0800 |
|---|---|---|
| committer | Guo, Yejun <yejun.guo@intel.com> | 2020-03-12 18:22:51 +0800 |
| commit | e35f96685312c70f7c1cfaadeb966bce1976eb1b (patch) | |
| tree | 2c0a10036a2461bf79c566d4c779e59107d9e7d8 /doc | |
| parent | bd50453894182af095c7d7578596e6ff6c58f852 (diff) | |
avfilter/vf_dnn_processing.c: add frame size change support for planar yuv format
The Y channel is handled by dnn, and also resized by dnn. The UV channels
are resized with swscale.
The command to use espcn.pb (see vf_sr) looks like:
./ffmpeg -i 480p.jpg -vf format=yuv420p,dnn_processing=dnn_backend=tensorflow:model=espcn.pb:input=x:output=y -y tmp.espcn.jpg
Signed-off-by: Guo, Yejun <yejun.guo@intel.com>
Reviewed-by: Pedro Arthur <bygrandao@gmail.com>
Diffstat (limited to 'doc')
| -rw-r--r-- | doc/filters.texi | 9 |
1 files changed, 9 insertions, 0 deletions
diff --git a/doc/filters.texi b/doc/filters.texi index 554eaff163..ff008b119f 100644 --- a/doc/filters.texi +++ b/doc/filters.texi @@ -9156,6 +9156,7 @@ ffmpeg -i INPUT -f lavfi -i nullsrc=hd720,geq='r=128+80*(sin(sqrt((X-W/2)*(X-W/2 @end example @end itemize +@anchor{dnn_processing} @section dnn_processing Do image processing with deep neural networks. It works together with another filter @@ -9217,6 +9218,12 @@ Handle the Y channel with srcnn.pb (see @ref{sr} filter) for frame with yuv420p ./ffmpeg -i 480p.jpg -vf format=yuv420p,scale=w=iw*2:h=ih*2,dnn_processing=dnn_backend=tensorflow:model=srcnn.pb:input=x:output=y -y srcnn.jpg @end example +@item +Handle the Y channel with espcn.pb (see @ref{sr} filter), which changes frame size, for format yuv420p (planar YUV formats supported): +@example +./ffmpeg -i 480p.jpg -vf format=yuv420p,dnn_processing=dnn_backend=tensorflow:model=espcn.pb:input=x:output=y -y tmp.espcn.jpg +@end example + @end itemize @section drawbox @@ -17374,6 +17381,8 @@ Default value is @code{2}. Scale factor is necessary for SRCNN model, because it input upscaled using bicubic upscaling with proper scale factor. @end table +This feature can also be finished with @ref{dnn_processing} filter. + @section ssim Obtain the SSIM (Structural SImilarity Metric) between two input videos. |