[FFmpeg-cvslog] avfilter/vf_dnn_processing.c: add frame size change support for planar yuv format
Guo, Yejun
git at videolan.org
Thu Mar 12 12:32:46 EET 2020
ffmpeg | branch: master | Guo, Yejun <yejun.guo at intel.com> | Fri Feb 21 20:40:07 2020 +0800| [e35f96685312c70f7c1cfaadeb966bce1976eb1b] | committer: Guo, Yejun
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 at intel.com>
Reviewed-by: Pedro Arthur <bygrandao at gmail.com>
> http://git.videolan.org/gitweb.cgi/ffmpeg.git/?a=commit;h=e35f96685312c70f7c1cfaadeb966bce1976eb1b
---
doc/filters.texi | 9 +++++++++
libavfilter/vf_dnn_processing.c | 37 ++++++++++++++++++++++++++++++-------
2 files changed, 39 insertions(+), 7 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
+ at 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
+ at item
+Handle the Y channel with espcn.pb (see @ref{sr} filter), which changes frame size, for format yuv420p (planar YUV formats supported):
+ at example
+./ffmpeg -i 480p.jpg -vf format=yuv420p,dnn_processing=dnn_backend=tensorflow:model=espcn.pb:input=x:output=y -y tmp.espcn.jpg
+ at 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.
diff --git a/libavfilter/vf_dnn_processing.c b/libavfilter/vf_dnn_processing.c
index f9458f03b2..7f40f85dad 100644
--- a/libavfilter/vf_dnn_processing.c
+++ b/libavfilter/vf_dnn_processing.c
@@ -51,6 +51,8 @@ typedef struct DnnProcessingContext {
struct SwsContext *sws_gray8_to_grayf32;
struct SwsContext *sws_grayf32_to_gray8;
+ struct SwsContext *sws_uv_scale;
+ int sws_uv_height;
} DnnProcessingContext;
#define OFFSET(x) offsetof(DnnProcessingContext, x)
@@ -274,6 +276,18 @@ static int prepare_sws_context(AVFilterLink *outlink)
outlink->h,
AV_PIX_FMT_GRAY8,
0, NULL, NULL, NULL);
+
+ if (inlink->w != outlink->w || inlink->h != outlink->h) {
+ const AVPixFmtDescriptor *desc = av_pix_fmt_desc_get(fmt);
+ int sws_src_h = AV_CEIL_RSHIFT(inlink->h, desc->log2_chroma_h);
+ int sws_src_w = AV_CEIL_RSHIFT(inlink->w, desc->log2_chroma_w);
+ int sws_dst_h = AV_CEIL_RSHIFT(outlink->h, desc->log2_chroma_h);
+ int sws_dst_w = AV_CEIL_RSHIFT(outlink->w, desc->log2_chroma_w);
+ ctx->sws_uv_scale = sws_getContext(sws_src_w, sws_src_h, AV_PIX_FMT_GRAY8,
+ sws_dst_w, sws_dst_h, AV_PIX_FMT_GRAY8,
+ SWS_BICUBIC, NULL, NULL, NULL);
+ ctx->sws_uv_height = sws_src_h;
+ }
return 0;
default:
//do nothing
@@ -404,13 +418,21 @@ static av_always_inline int isPlanarYUV(enum AVPixelFormat pix_fmt)
static int copy_uv_planes(DnnProcessingContext *ctx, AVFrame *out, const AVFrame *in)
{
- const AVPixFmtDescriptor *desc = av_pix_fmt_desc_get(in->format);
- int uv_height = AV_CEIL_RSHIFT(in->height, desc->log2_chroma_h);
- for (int i = 1; i < 3; ++i) {
- int bytewidth = av_image_get_linesize(in->format, in->width, i);
- av_image_copy_plane(out->data[i], out->linesize[i],
- in->data[i], in->linesize[i],
- bytewidth, uv_height);
+ if (!ctx->sws_uv_scale) {
+ av_assert0(in->height == out->height && in->width == out->width);
+ const AVPixFmtDescriptor *desc = av_pix_fmt_desc_get(in->format);
+ int uv_height = AV_CEIL_RSHIFT(in->height, desc->log2_chroma_h);
+ for (int i = 1; i < 3; ++i) {
+ int bytewidth = av_image_get_linesize(in->format, in->width, i);
+ av_image_copy_plane(out->data[i], out->linesize[i],
+ in->data[i], in->linesize[i],
+ bytewidth, uv_height);
+ }
+ } else {
+ sws_scale(ctx->sws_uv_scale, (const uint8_t **)(in->data + 1), in->linesize + 1,
+ 0, ctx->sws_uv_height, out->data + 1, out->linesize + 1);
+ sws_scale(ctx->sws_uv_scale, (const uint8_t **)(in->data + 2), in->linesize + 2,
+ 0, ctx->sws_uv_height, out->data + 2, out->linesize + 2);
}
return 0;
@@ -455,6 +477,7 @@ static av_cold void uninit(AVFilterContext *ctx)
sws_freeContext(context->sws_gray8_to_grayf32);
sws_freeContext(context->sws_grayf32_to_gray8);
+ sws_freeContext(context->sws_uv_scale);
if (context->dnn_module)
(context->dnn_module->free_model)(&context->model);
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