Human Pose Estimation with Iterative Error Feedback (IEF)
This package is an implementation of the algorithm described in our paper (pdf) for estimating human pose in natural images.
- Python 2.7
- OpenCV python interface (python-opencv)
Currently, it is necessary to use caffe version at the link. A patch that you can apply to your own caffe repository will be provided shortly in the future.
This package has been tested on Ubuntu 14.04.
- Download IEF models and supporting code:
In the main code directory launch ipython and run,
from src import test_demo as td #Define pose-predictor class ief = td.PoseIEF() #Name of the image imName = 'src/test_images/elvis.jpg' #Point (x,y) on the torso of the person whose pose is to be estimated bodyPt = (108, 98) #Predict the pose pose,_ = ief.predict(imName, bodyPt) #Visualize the result import scipy.misc as scm im = scm.imread(imName) td.vis.plot_pose_stickmodel(im, pose.squeeze().transpose((1,0)))
Note: This code only runs 1 image in a single batch and is hence runs slower than what can be achieved with larger batch sizes.
Downloading MPII Annotations in python
See the wiki page.
The README will be shortly updated with more details.