Human Pose Estimation with TensorFlow

Here you can find the implementation of the CNN-based human body part detectors, presented in the DeeperCut paper:

Eldar Insafutdinov, Leonid Pishchulin, Bjoern Andres, Mykhaylo Andriluka, and Bernt Schiele DeeperCut: A Deeper, Stronger, and Faster Multi-Person Pose Estimation Model In European Conference on Computer Vision (ECCV), 2016 For more information visit http://pose.mpi-inf.mpg.de

Python 2/3 is required to run this code. First of all, you should install TensorFlow as described in the official documentation. We recommended to use virtualenv.

You will also need to install the following Python packages:

$ pip install scipy scikit-image matplotlib pyyaml easydict

When running training or prediction scripts, please make sure to set the environment variable TF_CUDNN_USE_AUTOTUNE to 0 (see this ticket for explanation).

If your machine has multiple GPUs, you can select which GPU you want to run on by setting the environment variable, eg. CUDA_VISIBLE_DEVICES=0.

Demo code

# Download pre-trained model files
cd models/mpii
./download_models.sh
cd -

# Run demo of single person pose estimation
TF_CUDNN_USE_AUTOTUNE=0 python demo/singleperson.py

# Run demo of single person pose estimation for multi-images
TF_CUDNN_USE_AUTOTUNE=0 python demo/singleperson_images.py

Yarp demo

• Add the following lines into bashrc

export SKELETON2D=~/<path_to_pose-tensorflow>
export POSE_PARAM_PATH=$SKELETON2D
export PATH=$PATH:$SKELETON2D/demo

• Run the yarp module

skeleton2D.py --des /skeleton2D --gpu 0.7

Training models

Please follow these instructions

Citation

Please cite Deep(er)Cut in your publications if it helps your research:

@article{insafutdinov2016deepercut,
    author = {Eldar Insafutdinov and Leonid Pishchulin and Bjoern Andres and Mykhaylo Andriluka and Bernt Schiele},
    url = {http://arxiv.org/abs/1605.03170}
    title = {DeeperCut: A Deeper, Stronger, and Faster Multi-Person Pose Estimation Model},
    year = {2016}
}

@inproceedings{pishchulin16cvpr,
    title = {DeepCut: Joint Subset Partition and Labeling for Multi Person Pose Estimation},
    booktitle = {CVPR'16},
    url = {},
    author = {Leonid Pishchulin and Eldar Insafutdinov and Siyu Tang and Bjoern Andres and Mykhaylo Andriluka and Peter Gehler and Bernt Schiele}
}