/deep-learning-for-human-part-discovery-in-images

Implementation with Chainer

Primary LanguagePython

Deep Learning for Human Part Discovery in Images - Chainer implementation

NOTE: This is not official implementation. Original paper is Deep Learning for Human Part Discovery in Images.

Requirements

  • Python 2.7.11+

    • Chainer 1.10+
    • numpy 1.9+
    • scipy 0.16+
    • six
    • matplotlib
    • tqdm
    • cv2 (opencv)

Data preparation

bash prepare.sh

This script downloads VOC 2010 dataset (http://host.robots.ox.ac.uk/pascal/VOC/voc2010/VOCtrainval_03-May-2010.tar) and the authors' original dataset (http://www2.informatik.uni-freiburg.de/~oliveira/datasets/Sitting.tar.gz).

Start training

python train.py -g 0 -b 5 -e 3000 -l on -s on

Possible options

python train.py --help

GPU memory requirement

Now in prep.

Result

Now in prep.

Visualize Prediction

python visualize.py -f PATH_TO_IMAGE_FILE

LICENSE

MIT LICENSE.

Author

shiba24, August 2016.