Wenbin Chen f4e0664fd1 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>
2024-03-19 14:48:58 +08:00
2024-03-19 04:10:48 +01:00
2022-03-17 18:35:41 -03:00
2024-02-23 00:17:21 +01:00
2023-03-01 21:59:10 +01:00
2024-02-21 18:24:17 +01:00
2022-07-13 00:31:42 +02:00

FFmpeg README

FFmpeg is a collection of libraries and tools to process multimedia content such as audio, video, subtitles and related metadata.

Libraries

  • libavcodec provides implementation of a wider range of codecs.
  • libavformat implements streaming protocols, container formats and basic I/O access.
  • libavutil includes hashers, decompressors and miscellaneous utility functions.
  • libavfilter provides means to alter decoded audio and video through a directed graph of connected filters.
  • libavdevice provides an abstraction to access capture and playback devices.
  • libswresample implements audio mixing and resampling routines.
  • libswscale implements color conversion and scaling routines.

Tools

  • ffmpeg is a command line toolbox to manipulate, convert and stream multimedia content.
  • ffplay is a minimalistic multimedia player.
  • ffprobe is a simple analysis tool to inspect multimedia content.
  • Additional small tools such as aviocat, ismindex and qt-faststart.

Documentation

The offline documentation is available in the doc/ directory.

The online documentation is available in the main website and in the wiki.

Examples

Coding examples are available in the doc/examples directory.

License

FFmpeg codebase is mainly LGPL-licensed with optional components licensed under GPL. Please refer to the LICENSE file for detailed information.

Contributing

Patches should be submitted to the ffmpeg-devel mailing list using git format-patch or git send-email. Github pull requests should be avoided because they are not part of our review process and will be ignored.

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