Realtime object detection is one of areas in computer vision that is still quite challenging performance-wise. When it comes to mobile/embedded application, GPUs certainly make a whole lot of difference allowing to achieve practically useful speeds. For example, SSD model described below runs at ~8.5 FPS on GPU and 0.03 FPS in CPU-only mode on TX1 board.

Single Shot MultiBox Detector (SSD) is one of the fastest currently available approaches to object detection on images. It achieves accuracy comparable to Faster-RCNN while in most cases performing faster than YOLO model. SSD is created by Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg. and is published on arXiv in December 2015.

Installation

This assumes you are installing SSD on a clean JetPack 2.3.1 (containing Ubuntu 16.04 & CUDA 8.0).

SSD is implemented on top of modified version of Caffe framework. Instructions from BVLC does not fully work for TX1 so here is the process with few workarounds:

Getting SSD sources:

cd ~ubuntu # install git sudo apt-get update sudo apt-get install git # clone SSD git repo git clone https://github.com/weiliu89/caffe.git caffe-ssd cd caffe-ssd # switch to ssd branch git checkout ssd

Squeezing some extra speed out of TX1:

cd ~ubuntu # save current settings sudo ./jetson_clocks.sh --store default-clocks # load performance-optimized profile sudo ./jetson_clocks.sh # to get back to default power settings: # ./jetson_clocks.sh --restore default-clocks

Installing dependencies:

sudo apt-get install \ libprotobuf-dev libleveldb-dev libsnappy-dev \ libhdf5-serial-dev protobuf-compiler sudo apt-get install --no-install-recommends libboost-all-dev # install OpenCV libraries ~ubuntu/OpenCV4Tegra/ocv.sh

Editing Makefile.config :

cd ~ubuntu/caffe-ssd cp Makefile.conig.example Makefile.config

Uncomment line (5) # USE_CUDNN := 1 to be USE_CUDNN := 1

to be Edit line (90) INCLUDE_DIRS := ... to be INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial/

Editing Makefile :

Edit line (181) LIBRARIES += ... to be LIBRARIES += glog gflags protobuf boost_system boost_filesystem m hdf5_serial_hl hdf5_serial .

Compiling Caffe:

cd ~ununtu/caffe-ssd make -j4

Now get a cup of coffee, but small, compiling Caffe on TX1 doesn’t actually take that long.

Running

Wei Liu’s repo for SSD contains links to SSD models pre-trained on PASCAL VOC 2007+2012, MSCOCO and ILSVRC2015 datasets with VGG as base network.

In order to run model in test (inference) mode mode you also need a labels map and a model definition, which you can obtain by by running Wei Liu’s examples or by downloading them and a SSD300 trained on VOC0712 here.

In latter case, after downloading ssd-tx1.tar.gz :

# extract files tar -zxf ssd-tx1.tar.gz cd ssd-tx1 # run in test mode ~ubuntu/caffe-ssd/build/tools/caffe test \ --model = "test.prototxt" \ --weights = "VGG_VOC0712_SSD_300x300_iter_60000.caffemodel" \ --iterations = "536870911" \ --gpu 0

You also may want to configure which video device to use by editing test.prototxt . By default device /dev/video1 is used which maps to external USB camera, but only if it was plugged after the boot-up:

video_data_param { video_type : WEBCAM device_id : 1 <-- }

Don’t forget to enable turbo mode ( sudo ~ubuntu/jetson_clocks.sh ).

Enjoy!