tegra-caffe

@Building and Running @{

This sample uses Caffe to classify the kinds of objects that appear in the camera stream.

Prerequisites

• You have followed Steps 1-3 in @ref mmapi_build.
• You have a working USB camera module.

To build and run

1. Set up the Caffe environment.

   a) Install packages from APT with the following commands:

    $ sudo add-apt-repository universe
    $ sudo add-apt-repository multiverse
    $ sudo apt-get update
    $ sudo apt-get install libboost-all-dev libprotobuf-dev libleveldb-dev libsnappy-dev
    $ sudo apt-get install libhdf5-serial-dev protobuf-compiler libgflags-dev libgoogle-glog-dev
    $ sudo apt-get install liblmdb-dev libblas-dev libatlas-base-dev
   

   b) Download Caffe source package from the following website:

    https://github.com/BVLC/caffe
   
   And copy the package to `$HOME` directory on the target board
   with the following command:
   
       $ mkdir -pv $HOME/Work/caffe
       $ cp caffe-master.zip $HOME/Work/caffe/
       $ cd $HOME/Work/caffe/ && unzip caffe-master.zip
   

   c) Build Caffe source with the following commands:

    $ cd $HOME/Work/caffe/caffe-master
   Locate and edit `Makefile.config.example`.
   
   Uncomment the following line to enable cuDNN acceleration:
   
        USE_CUDNN := 1
   
    Add two lines to CUDA architecture setting:
   
        -gencode arch=compute_53,code=sm_53 \
        -gencode arch=compute_62,code=sm_62
   And modify the following two lines. Then save and close the file.
   
        INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial
        LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/lib/aarch64-linux-gnu/hdf5/serial
   Then enter:
   
        $ cp Makefile.config.example Makefile.config
        $ make -j4
   
   The library libcaffe.so is generated in the `build/lib` directory.
   

2. Compile the OpenCV consumer library. This library is needed for Caffe and must be compiled on the target board.

   $ cd 11_camera_object_identification/opencv_consumer_lib
   

   Check the Makefile to ensure the following variables are set correctly:

    CUDA_DIR:=/usr/local/cuda
    CAFFE_DIR:=$HOME/Work/caffe/caffe-master
   

   Then enter:

    $ make
   

   This command generates the library libopencv_consumer.so in the current directory.

3. Download the Caffe model binaries with the following commands:

   $ sudo apt-get install python-pip
   $ sudo pip install pyyaml six
   $ cd $HOME/Work/caffe/caffe-master
   $ ./scripts/download_model_binary.py  models/bvlc_reference_caffenet/
   

   Get the ImageNet labels file with the following command:

    $ ./data/ilsvrc12/get_ilsvrc_aux.sh
   

4. Build and run the sample with the following commands:

   $ cd 11_camera_object_identification
   $ make
   $ export LD_LIBRARY_PATH=$HOME/Work/caffe/caffe-master/build/lib:/usr/local/cuda/lib64
   $ ./camera_v4l2_cuda -d /dev/video0 -s 640x480 -f YUYV -n 30
   

@}