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semi-auto-anno's Introduction

Semi-Automatic 3D Hand Pose Annotation

Author: Markus Oberweger [email protected]

Requirements:

  • OS:
    • Ubuntu 14.04
  • via Ubuntu package manager:
    • python2.7
    • python-matplotlib
    • python-scipy
    • python-pil
    • python-numpy
    • python-vtk6
    • python-opencv2
    • python-qt4
    • python-pip
  • via pip install:
    • progressbar
    • psutil
    • theano (0.8)

For a description of our method see:

M. Oberweger, G. Riegler, P. Wohlhart, and V. Lepetit. Efficiently Creating 3D Training Data for Fine Hand Pose Estimation. In Conference on Computer Vision and Pattern Recognition (CVPR), 2016.

Setup:

  • Read the included manual on how to use our method
  • Put dataset files into ./data
  • Download SIFTFlow and put it into ./src/etc/sift_flow
  • Goto ./src and see the main file main_blender_semiauto.py how to handle the API
  • Goto ./src and see the main files main_labeling_pose.py and main_labeling_detect.py how to do the annotation for your own dataset

semi-auto-anno's People

Contributors

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