Openpose from CMU implemented using Tensorflow. It also provides several variants that have made some changes to the network structure for real-time processing on the CPU.

Original Repo(Caffe) : https://github.com/CMU-Perceptual-Computing-Lab/openpose

Features

[x] CMU's original network architecture and weights.

[] Post processing from network output.

[] Faster network variants using mobilenet, lcnn architecture.

[] ROS Support.

You need dependencies below.

• python3

• tensorflow 1.3

• opencv 3

• protobuf

CMU Perceptual Computing Lab has modified Caffe to provide data augmentation.

This includes

• scale : 0.7 ~ 1.3

• rotation : -40 ~ 40 degrees

• flip

• cropping

See : https://github.com/CMU-Perceptual-Computing-Lab/caffe_train

[1] https://github.com/CMU-Perceptual-Computing-Lab/openpose

[2] Training Codes : https://github.com/ZheC/Realtime_Multi-Person_Pose_Estimation

[3] Custom Caffe by Openpose : https://github.com/CMU-Perceptual-Computing-Lab/caffe_train

[2] Pretrained model : https://github.com/tensorflow/models/blob/master/slim/nets/mobilenet_v1.md

[1] Tensorpack : https://github.com/ppwwyyxx/tensorpack