README.md
March 4, 2018 ยท View on GitHub
What's this
- Facial Landmark Detection with Caffe CNN.
- Implementation of the two nets from different paper.
- Net1: Approaching human level facial landmark localization by deep learning
- Net2: TCNN: Facial Landmark Detection with Tweaked Convolutional Neural Networks
How to prepare dataset
- Please download CelebA dataset
- change input path to your dataset path in train.prototxt file.
How to training
Please run these command in the root of this project. Note: Please change parameter in train.prototxt. such as process num and buffer2memory!
- set env
export PYTHONPATH=`pwd`/common/:$PYTHONPATH
- train net1
caffe train --solver=training/net1/solver.prototxt --gpu=0
- train net2
caffe train --solver=training/net2/vanilla_adam_solver.prototxt --gpu=0
How to testing or predict
cd testing
python test.py ../model/net1/_iter_100000.caffemodel ../training/net1/deploy.prototxt
Please replace correct path of caffe model and deploy file in above command.
How to do a benchmark
cd benchmark
python test.py ../model/net1/_iter_100000.caffemodel ../training/net1/deploy.prototxt
Please replace correct path of caffe model and deploy file in above command.
After do that, you will get mean error of your model.