demo

Realsense Realtime Demo Using Pose-REN

ICVL

NYU

MSRA

Realsense Realtime Demo

We provide a realtime hand pose estimation demo using Intel Realsense device. Note that we just use a naive depth thresholding method to detect the hand. Therefore, the hand should be in the range of [0, 650mm] to run this demo. We tested this realtime demo with an Intel Realsense SR300.

Please use your right hand for this demo and try to avoid clustered background and redundant arm around the hand.

Python demo with librealsense [recommended]

First compile and install the librealsense and its python wrapper. After everything is working properly, just run the following python script for demo:

python src/demo/realsense_realtime_demo_librealsense2.py

By default this script uses pre-trained weights on ICVL dataset. You can change the pre-trained model by specifying the dataset.

python src/demo/realsense_realtime_demo_librealsense2.py  nyu/msra/icvl

Notes: The speed of this python demo is not optimal and it runs slower than the c++ demo.

C++ demo

First compile the codes:

cd src/demo/pose-ren-demo-cpp
mkdir build
cd build
cmake ..
make -j16

Run the demo by:

cd ..                 # redirect to src/demo/pose-ren-demo-cpp
./build/src/PoseREN   # run

By default it uses pre-trained weights on Hands17 dataset. You can change the pre-trained model by specifying the dataset.

./build/src/PoseREN  nyu/msra/icvl

Notes: This C++ demo is not fully developed and you may have to play with some dependency problems to make it works. It servers as a preliminary project to demonstrate how to use Pose-REN in C++.