tf-openpose

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.

Install

You need dependencies below.

python3
tensorflow 1.3
opencv 3
protobuf

Models

Inference Time

Dataset	Model	Description	Inference Time 1 core cpu
Coco	cmu	CMU's original version. Same network, same weights.	3.65s / img
Coco	dsconv	Same as the cmu version except for the depthwise separable convolution of mobilenet.	0.44s / img
Coco	mobilenet
Coco	lcnn

Training

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

References

License

Zumbalamambo/tf-openpose

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