Classification	Object Detection	Pose Estimation

1. A linux machine, I tested this build on x86_64
2. Front Cam or USB Cam connected to your computer with drivers preinstalled
3. Optional - EdgeTPU for NN acceleration

Links attached for your reference

1. OpenCV
2. Upgrade GCC - Upgrade your gcc and g++ to the latest version. Don't worry they are always backward compatible.

$ sudo apt install libgtk2.0-dev
$ sudo apt search libgtk2.0-dev

1. Clone the Repository

$ git clone https://github.com/Eashwar93/coral_edgetpu_video_inference.git
$ cd coral_edgetpu_video_inference/scripts

2. Upgrade your cmake to the latest version and again don't worry they are backward compatible.

$ bash install_cmake.sh

3. Build the repostitory

$ cd ..
$ mkdir build && cd build
$ cmake ..
$ make
$ cd ..

1. If you have a Coral USB Accelerator you can run any of the following scripts else skip to Step 2. The first script runs classification on a video stream,the second runs Object Detection and the third runs human pose estimation

$ bash scripts/classification/classify_edgetpu.sh
$ bash scripts/detection/detect_edgetpu.sh
$ bash scripts/pose_estimation/pose_edgetpu_480x640.sh

2. The following scripts can be run on computers without any accelerators:

$ bash scripts/classification/classify_cpu.sh
$ bash scripts/detection/detect_cpu.sh
$ bash scripts/pose_estimation/pose_cpu_353x481.sh

I apprently made use of Coral USB Accelerator and below are the results for your reference. Click here to see the GIF Demos.

1. google-coral/edgetpu
2. Namburger/edgetpu-detection-camera

1. A medium article on how to use Google TPU's and why do we need them.
2. ROS wrapper to take advantage of the the TPU for Robot Naviagtion.