libavfi/dnn: add LibTorch as one of DNN backend

PyTorch is an open source machine learning framework that accelerates
the path from research prototyping to production deployment. Official
website: https://pytorch.org/. We call the C++ library of PyTorch as
LibTorch, the same below.

To build FFmpeg with LibTorch, please take following steps as
reference:
1. download LibTorch C++ library in
 https://pytorch.org/get-started/locally/,
please select C++/Java for language, and other options as your need.
Please download cxx11 ABI version:
 (libtorch-cxx11-abi-shared-with-deps-*.zip).
2. unzip the file to your own dir, with command
unzip libtorch-shared-with-deps-latest.zip -d your_dir
3. export libtorch_root/libtorch/include and
libtorch_root/libtorch/include/torch/csrc/api/include to $PATH
export libtorch_root/libtorch/lib/ to $LD_LIBRARY_PATH
4. config FFmpeg with ../configure --enable-libtorch \
 --extra-cflag=-I/libtorch_root/libtorch/include \
 --extra-cflag=-I/libtorch_root/libtorch/include/torch/csrc/api/include \
 --extra-ldflags=-L/libtorch_root/libtorch/lib/
5. make

To run FFmpeg DNN inference with LibTorch backend:
./ffmpeg -i input.jpg -vf \
dnn_processing=dnn_backend=torch:model=LibTorch_model.pt -y output.jpg

The LibTorch_model.pt can be generated by Python with torch.jit.script()
api. https://pytorch.org/tutorials/advanced/cpp_export.html. This is
pytorch official guide about how to convert and load torchscript model.
Please note, torch.jit.trace() is not recommanded, since it does
not support ambiguous input size.

Signed-off-by: Ting Fu <ting.fu@intel.com>
Signed-off-by: Wenbin Chen <wenbin.chen@intel.com>
Reviewed-by: Guo Yejun <yejun.guo@intel.com>

1 files changed, 4 insertions, 1 deletions

diff --git a/configure b/configure
index 2b4c4ec9a2..e019d1b996 100755
--- a/configure
+++ b/configure
@@ -281,6 +281,7 @@ External library support:
   --enable-libtheora       enable Theora encoding via libtheora [no]
   --enable-libtls          enable LibreSSL (via libtls), needed for https support
                            if openssl, gnutls or mbedtls is not used [no]
+  --enable-libtorch        enable Torch as one DNN backend [no]
   --enable-libtwolame      enable MP2 encoding via libtwolame [no]
   --enable-libuavs3d       enable AVS3 decoding via libuavs3d [no]
   --enable-libv4l2         enable libv4l2/v4l-utils [no]
@@ -1905,6 +1906,7 @@ EXTERNAL_LIBRARY_LIST="
     libtensorflow
     libtesseract
     libtheora
+    libtorch
     libtwolame
     libuavs3d
     libv4l2
@@ -2785,7 +2787,7 @@ cbs_vp9_select="cbs"
 deflate_wrapper_deps="zlib"
 dirac_parse_select="golomb"
 dovi_rpu_select="golomb"
-dnn_suggest="libtensorflow libopenvino"
+dnn_suggest="libtensorflow libopenvino libtorch"
 dnn_deps="avformat swscale"
 error_resilience_select="me_cmp"
 evcparse_select="golomb"
@@ -6884,6 +6886,7 @@ enabled libtensorflow     && require libtensorflow tensorflow/c/c_api.h TF_Versi
 enabled libtesseract      && require_pkg_config libtesseract tesseract tesseract/capi.h TessBaseAPICreate
 enabled libtheora         && require libtheora theora/theoraenc.h th_info_init -ltheoraenc -ltheoradec -logg
 enabled libtls            && require_pkg_config libtls libtls tls.h tls_configure
+enabled libtorch          && check_cxxflags -std=c++17 && require_cpp libtorch torch/torch.h "torch::Tensor" -ltorch -lc10 -ltorch_cpu -lstdc++ -lpthread
 enabled libtwolame        && require libtwolame twolame.h twolame_init -ltwolame &&
                              { check_lib libtwolame twolame.h twolame_encode_buffer_float32_interleaved -ltwolame ||
                                die "ERROR: libtwolame must be installed and version must be >= 0.3.10"; }