We don't want to install sample sources. So delete them and install the
binaries instead. Also make sure that we're installing the python
samples and modules at correct location. Remove the tweaks from local
patch and copy in the recipe itself.
Signed-off-by: Anuj Mittal <anuj.mittal@intel.com>
* otherwise components depending on them won't be able to find them
Signed-off-by: Martin Jansa <Martin.Jansa@gmail.com>
Signed-off-by: Anuj Mittal <anuj.mittal@intel.com>
Refresh patches so that they apply cleanly on 2019r3.
Signed-off-by: Chin Huat Ang <chin.huat.ang@intel.com>
Signed-off-by: Anuj Mittal <anuj.mittal@intel.com>
Install clDNN to /usr/lib to resolve the following inference engine
error when running with GPU plugin:
[ ERROR ] Failed to create plugin libclDNNPlugin.so for device GPU
Please, check your environment
Cannot load library 'libclDNNPlugin.so': libclDNNPlugin.so: cannot open
shared object file: No such file or directory
/usr/src/debug/dldt-inference-engine/2019r2-r0/git/inference-engine/include/details/os/lin_shared_object_loader.h:36
/usr/src/debug/dldt-inference-engine/2019r2-r0/git/inference-engine/src/inference_engine/ie_core.cpp:277
Signed-off-by: Chin Huat Ang <chin.huat.ang@intel.com>
Signed-off-by: Anuj Mittal <anuj.mittal@intel.com>
* Release notes:
https://software.intel.com/en-us/articles/OpenVINO-RelNotes
* Enable unit tests to be built and tested using ptest mechanism.
* Include patches from Clear Linux for build fixes.
* Switch to using python3 and threading to using TBB. Switch ENABLE_OPENCV
to off so opencv from system is used.
* Remove do_install and patch Makefiles instead to install libraries correctly.
Signed-off-by: Anuj Mittal <anuj.mittal@intel.com>
This recipe builds the inference engine from opencv/dldt 2019 R1.1
release.
OpenVINO™ toolkit, short for Open Visual Inference and Neural network
Optimization toolkit, provides developers with improved neural network
performance on a variety of Intel® processors and helps further unlock
cost-effective, real-time vision applications.
The toolkit enables deep learning inference and easy heterogeneous
execution across multiple Intel® platforms (CPU, Intel® Processor Graphics)—providing
implementations across cloud architectures to edge device.
For more details, see:
https://01.org/openvinotoolkit
The recipe needs components from meta-oe so move it to
dynamic-layers/openembedded-layer. GPU plugin support needs intel-compute-runtime
which can be built by including clang layer in the mix as well.
CPU and GPU plugins have been sanity tested to work using
classification_sample. Further fine-tuning is still needed to improve
the performance.
Original patch by Anuj Mittal.
Signed-off-by: Chin Huat Ang <chin.huat.ang@intel.com>
Signed-off-by: Anuj Mittal <anuj.mittal@intel.com>
