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DeepPose

NOTE: This is not official implementation. Original paper is DeepPose: Human Pose Estimation via Deep Neural Networks.

Requirements

I strongly recommend to use Anaconda environment. This repo may be able to be used in Python 2.7 environment, but I haven't tested.

Installation of dependencies

pip install chainer
pip install numpy
pip install scikit-image
# for python3
conda install -c https://conda.binstar.org/menpo opencv3
# for python2
conda install opencv

Dataset preparation

bash datasets/download.sh
python datasets/flic_dataset.py
python datasets/lsp_dataset.py
python datasets/mpii_dataset.py

MPII Dataset

Start training

Starting with the prepared shells is the easiest way. If you want to run train.py with your own settings, please check the options first by python scripts/train.py --help and modify one of the following shells to customize training settings.

For FLIC Dataset

bash shells/train_flic.sh

For LSP Dataset

bash shells/train_lsp.sh

For MPII Dataset

bash shells/train_mpii.sh

GPU memory requirement

Prediction

Will add some tools soon