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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>
15 lines
957 B
Makefile
15 lines
957 B
Makefile
OBJS-$(CONFIG_DNN) += dnn/dnn_interface.o
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OBJS-$(CONFIG_DNN) += dnn/dnn_backend_native.o
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OBJS-$(CONFIG_DNN) += dnn/dnn_backend_native_layers.o
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OBJS-$(CONFIG_DNN) += dnn/dnn_backend_native_layer_pad.o
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OBJS-$(CONFIG_DNN) += dnn/dnn_backend_native_layer_conv2d.o
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OBJS-$(CONFIG_DNN) += dnn/dnn_backend_native_layer_depth2space.o
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OBJS-$(CONFIG_DNN) += dnn/dnn_backend_native_layer_maximum.o
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OBJS-$(CONFIG_DNN) += dnn/dnn_backend_native_layer_mathbinary.o
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OBJS-$(CONFIG_DNN) += dnn/dnn_backend_native_layer_mathunary.o
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DNN-OBJS-$(CONFIG_LIBTENSORFLOW) += dnn/dnn_backend_tf.o
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DNN-OBJS-$(CONFIG_LIBOPENVINO) += dnn/dnn_backend_openvino.o
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OBJS-$(CONFIG_DNN) += $(DNN-OBJS-yes)
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