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OpenVINO is a Deep Learning Deployment Toolkit at https://github.com/openvinotoolkit/openvino, it supports CPU, GPU and heterogeneous plugins to accelerate deep learning inferencing. Please refer to https://github.com/openvinotoolkit/openvino/blob/master/build-instruction.md to build openvino (c library is built at the same time). Please add option -DENABLE_MKL_DNN=ON for cmake to enable CPU path. The header files and libraries are installed to /usr/local/deployment_tools/inference_engine/ with default options on my system. To build FFmpeg with openvion, take my system as an example, run with: $ export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/deployment_tools/inference_engine/lib/intel64/:/usr/local/deployment_tools/inference_engine/external/tbb/lib/ $ ../ffmpeg/configure --enable-libopenvino --extra-cflags=-I/usr/local/deployment_tools/inference_engine/include/ --extra-ldflags=-L/usr/local/deployment_tools/inference_engine/lib/intel64 $ make Here are the features provided by OpenVINO inference engine: - support more DNN model formats It supports TensorFlow, Caffe, ONNX, MXNet and Kaldi by converting them into OpenVINO format with a python script. And torth model can be first converted into ONNX and then to OpenVINO format. see the script at https://github.com/openvinotoolkit/openvino/tree/master/model-optimizer/mo.py which also does some optimization at model level. - optimize at inference stage It optimizes for X86 CPUs with SSE, AVX etc. It also optimizes based on OpenCL for Intel GPUs. (only Intel GPU supported becuase Intel OpenCL extension is used for optimization) Signed-off-by: Guo, Yejun <yejun.guo@intel.com> Signed-off-by: Pedro Arthur <bygrandao@gmail.com>
FFmpeg README
FFmpeg is a collection of libraries and tools to process multimedia content such as audio, video, subtitles and related metadata.
Libraries
libavcodecprovides implementation of a wider range of codecs.libavformatimplements streaming protocols, container formats and basic I/O access.libavutilincludes hashers, decompressors and miscellaneous utility functions.libavfilterprovides a mean to alter decoded Audio and Video through chain of filters.libavdeviceprovides an abstraction to access capture and playback devices.libswresampleimplements audio mixing and resampling routines.libswscaleimplements 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,ismindexandqt-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.