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Gardenia is a face alignment project using Convolutional Neural Network.

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gardenia

Gardenia is a face alignment project using Convolutional Neural Network. The project illstrate the training and testing process on 300W dataset.

Installation

Tutorial

We need first to prepare the data, suppose the original data root path are data/. Run

scripts/prepare.sh

To crop the testset and augment the trainset, and we will get the data/augment/train.txt, data/train_mean.blob and data/crop/test.txt. After preparing the data, we can run

scripts/train.sh

to train our model. The prototxt are set done on proto folder.

After training a model, suppose the model path to be $MODEL, run

scripts/inference.sh # You may need to set some options in inference.sh to predict labels 
scripts/evalution.sh # report mean err on 300W dataset and CED curve.

The inference.sh will use trainded model to predict shapes, the pretrainded can be downloaded from [here] (http://pan.baidu.com/s/1cBOph8). Feel free to put an issue if you encounter problems.

Speed

Tested on Ubuntu 16.04, Nvidia TITAN X, without cudnn, without image load and data processing.

proto num of layers average forward speed average backward speed
v3 11 17.5707 ms / 1 sample 38.4078 ms / 1 sample
v4 16 20.783 ms / 1 sample 41.3371 ms / 1 sample
v5 26 22.3556 ms / 1 sample 54.5015 ms / 1 sample
v6 36 25.0671 ms / 1 sample 54.6937 ms / 1 sample
v7 41 26.0211 ms / 1 sample 55.7797 ms / 1 sample

Citation

@inproceedings{xu2016learning,
  title={Learning Facial Point Response for Alignment by Purely Convolutional Network},
  author={Xu, Zhenqi and Deng, Weihong and Hu, Jiani},
  booktitle={Asian Conference on Computer Vision},
  pages={248--263},
  year={2016},
  organization={Springer}
}

You can get a pdf copy from https://pan.baidu.com/s/1qXKo85Q

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Gardenia is a face alignment project using Convolutional Neural Network.

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