- Introduction
The HeadPose Estimator predicts face landmarks (68 points) and head pose (3d pose, yaw, roll, and pitch).
- Install
caffe
dlib18.17
(cd your dlib folder
cd python_example
./compile_dlib_python_module.bat
add dlib.so to the PYTHONPATH)
opencv
numpy, pandas
- Usage
Unzip dlib-18.17.zip
Creat folder "img" to store your testing img
Creat folder "result" to store your visualized results
Creat folder "pose" to store your estimated poses (yaw angles) for each img
Pycharm run dlib-18.17/python_examples/landmarkPredict.py (modify the caffe_root path and testList.txt if needed. testList.txt is a file containing the path of the testing images.)
- Train
Modify train.prototxt and train_solver.prototxt files, train the model using your own data.