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Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

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MXNet v1.9.1 Extension

This repo contains a slight tweak on MXNet version 1.9.1 that enables the ROIAlign operator to take inputs of data type other than just float32. Specifically, accepting uint8 as input is critical to the performance of the compressed video refinement detector.

Installation

Install OpenCV3.4

This build requires OpenCV version 3.4. Follow instructions online to install it, but replace the cmake command with this:

cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local/opencv3.4 -D INSTALL_C_EXAMPLES=ON -D INSTALL_PYTHON_EXAMPLES=ON -D OPENCV_GENERATE_PKGCONFIG=ON -D OPENCV_EXTRA_MODULES_PATH=~/opencv_build/opencv_contrib/modules -D BUILD_EXAMPLES=ON ..

Install MXNet

Clone this repo

git clone [email protected]:RyanHTran/mxnet.git

The build configuration is specified in config.cmake. Modify it if necessary for your installation.

Finally, build the package and install Python bindings

mkdir build && cd build
cmake -D OpenCV_DIR=/usr/local/opencv3.4/share/OpenCV/ -D BUILD_CPP_EXAMPLES=0 -D USE_CPP_PACKAGE=0 ..
cmake --build . --parallel 12 && cd .. && pip install -e ./python

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Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

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