ffmpeg | branch: master | Guo, Yejun <yejun....@intel.com> | Mon May 25 16:16:22 2020 +0800| [9bcf2aa47756c253238903f3e5ef6c96d927cfe6] | committer: Guo, Yejun
vf_dnn_processing.c: add dnn backend openvino We can try with the srcnn model from sr filter. 1) get srcnn.pb model file, see filter sr 2) convert srcnn.pb into openvino model with command: python mo_tf.py --input_model srcnn.pb --data_type=FP32 --input_shape [1,960,1440,1] --keep_shape_ops See the script at https://github.com/openvinotoolkit/openvino/tree/master/model-optimizer We'll see srcnn.xml and srcnn.bin at current path, copy them to the directory where ffmpeg is. I have also uploaded the model files at https://github.com/guoyejun/dnn_processing/tree/master/models 3) run with openvino backend: ffmpeg -i input.jpg -vf format=yuv420p,scale=w=iw*2:h=ih*2,dnn_processing=dnn_backend=openvino:model=srcnn.xml:input=x:output=srcnn/Maximum -y srcnn.ov.jpg (The input.jpg resolution is 720*480) Also copy the logs on my skylake machine (4 cpus) locally with openvino backend and tensorflow backend. just for your information. $ time ./ffmpeg -i 480p.mp4 -vf format=yuv420p,scale=w=iw*2:h=ih*2,dnn_processing=dnn_backend=tensorflow:model=srcnn.pb:input=x:output=y -y srcnn.tf.mp4 … frame= 343 fps=2.1 q=31.0 Lsize= 2172kB time=00:00:11.76 bitrate=1511.9kbits/s speed=0.0706x video:1973kB audio:187kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.517637% [aac @ 0x2f5db80] Qavg: 454.353 real 2m46.781s user 9m48.590s sys 0m55.290s $ time ./ffmpeg -i 480p.mp4 -vf format=yuv420p,scale=w=iw*2:h=ih*2,dnn_processing=dnn_backend=openvino:model=srcnn.xml:input=x:output=srcnn/Maximum -y srcnn.ov.mp4 … frame= 343 fps=4.0 q=31.0 Lsize= 2172kB time=00:00:11.76 bitrate=1511.9kbits/s speed=0.137x video:1973kB audio:187kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.517640% [aac @ 0x31a9040] Qavg: 454.353 real 1m25.882s user 5m27.004s sys 0m0.640s Signed-off-by: Guo, Yejun <yejun....@intel.com> Signed-off-by: Pedro Arthur <bygran...@gmail.com> > http://git.videolan.org/gitweb.cgi/ffmpeg.git/?a=commit;h=9bcf2aa47756c253238903f3e5ef6c96d927cfe6 --- doc/filters.texi | 10 +++++++++- libavfilter/vf_dnn_processing.c | 5 ++++- 2 files changed, 13 insertions(+), 2 deletions(-) diff --git a/doc/filters.texi b/doc/filters.texi index 67892e0afb..c13b4efacf 100644 --- a/doc/filters.texi +++ b/doc/filters.texi @@ -9291,13 +9291,21 @@ 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} + +@item openvino +OpenVINO backend. To enable this backend you +need to build and install the OpenVINO for C library (see +@url{https://github.com/openvinotoolkit/openvino/blob/master/build-instruction.md}) and configure FFmpeg with +@code{--enable-libopenvino} (--extra-cflags=-I... --extra-ldflags=-L... might +be needed if the header files and libraries are not installed into system path) + @end table Default value is @samp{native}. @item model Set path to model file specifying network architecture and its parameters. -Note that different backends use different file formats. TensorFlow and native +Note that different backends use different file formats. TensorFlow, OpenVINO and native backend can load files for only its format. Native model file (.model) can be generated from TensorFlow model file (.pb) by using tools/python/convert.py diff --git a/libavfilter/vf_dnn_processing.c b/libavfilter/vf_dnn_processing.c index cf589acedf..4b31808abf 100644 --- a/libavfilter/vf_dnn_processing.c +++ b/libavfilter/vf_dnn_processing.c @@ -58,10 +58,13 @@ typedef struct DnnProcessingContext { #define OFFSET(x) offsetof(DnnProcessingContext, x) #define FLAGS AV_OPT_FLAG_FILTERING_PARAM | AV_OPT_FLAG_VIDEO_PARAM static const AVOption dnn_processing_options[] = { - { "dnn_backend", "DNN backend", OFFSET(backend_type), AV_OPT_TYPE_INT, { .i64 = 0 }, 0, 1, FLAGS, "backend" }, + { "dnn_backend", "DNN backend", OFFSET(backend_type), AV_OPT_TYPE_INT, { .i64 = 0 }, INT_MIN, INT_MAX, FLAGS, "backend" }, { "native", "native backend flag", 0, AV_OPT_TYPE_CONST, { .i64 = 0 }, 0, 0, FLAGS, "backend" }, #if (CONFIG_LIBTENSORFLOW == 1) { "tensorflow", "tensorflow backend flag", 0, AV_OPT_TYPE_CONST, { .i64 = 1 }, 0, 0, FLAGS, "backend" }, +#endif +#if (CONFIG_LIBOPENVINO == 1) + { "openvino", "openvino backend flag", 0, AV_OPT_TYPE_CONST, { .i64 = 2 }, 0, 0, FLAGS, "backend" }, #endif { "model", "path to model file", OFFSET(model_filename), AV_OPT_TYPE_STRING, { .str = NULL }, 0, 0, FLAGS }, { "input", "input name of the model", OFFSET(model_inputname), AV_OPT_TYPE_STRING, { .str = NULL }, 0, 0, FLAGS }, _______________________________________________ ffmpeg-cvslog mailing list ffmpeg-cvslog@ffmpeg.org https://ffmpeg.org/mailman/listinfo/ffmpeg-cvslog To unsubscribe, visit link above, or email ffmpeg-cvslog-requ...@ffmpeg.org with subject "unsubscribe".
