Facial keypoints extraction using Caffe
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README.md Update README.md Feb 24, 2015
facialkp.prototxt changes Feb 23, 2015
facialkp.sh changes Feb 23, 2015
facialkp_predict.prototxt changes Feb 23, 2015
fkp.py changes Feb 23, 2015
kaggle.py changes Feb 23, 2015
out.txt changes Feb 23, 2015
output.py changes Feb 23, 2015
solver.prototxt changes Feb 23, 2015
train.txt changes Feb 23, 2015


Kaggle Facial points detection using Caffe Deep Learning

Facial keypoints extraction using Caffe for kaggle competition https://www.kaggle.com/c/facial-keypoints-detection This problem is a classic multilabel regression problem to solve. The kaggle CSV file provides (96,96) pixel images and you have to predict 30 keypoints (x,y) coordinates of nose, eye_center etc. The challenge ataset is over 70% of the data is missing filled with NaNs.

#Description of Files

fkp.py -> to write and prepare all data to hd5
facialkp -> Run the caffe model
output.py -> Predict and plot graphs in simple 64 batches. it writes into csv
solver.prototxt – > Edit this for maximum iterations, gamma, learning rate etc.
facialkp.prototxt -> Layer file for training
facialkp_predict -> Layer file for predictions
kaggle.py -> writes kaggle output to upload (you have manually edit csv files to add header labels, if not it will not work.

How to run

python fkp.py //run to preapare all data
./facialkp.sh //run the caffe trainer
python output.py // predicts the results and dumps the results in csv
python kaggle.py // writes the kaggle output to kaggle.csv 


Caffe installed in CUDA enabled GPU
Scikit-learn and Skimage
HDF5 support in python

#Documentation Here: http://corpocrat.com/2015/02/24/facial-keypoints-extraction-using-deep-learning-with-caffe/