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didi-udacity-2017

Competition entry for didi-udacity 2017 challenge for autonomous driving you can follow the development process at: https://medium.com/@hengcherkeng/part-1-didi-udacity-challenge-2017-car-and-pedestrian-detection-using-lidar-and-rgb-fff616fc63e8#.x9mavqle3

  • There is no formal setting of team and division of task for now. We have study the problem first for one week.

  • Basically, target for week mar-13:

    • download kitti dataset and make code for read data
    • construct simple network based on cvpr paper[1] using tensorflow
    • fit train data and make demo video (on train set)

    [delivery] : initial code + demo video

This is results on training (not testing)

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competition entry for didi-udacity 2017 challenge for autonomous driving

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  • Python 84.2%
  • C++ 12.6%
  • Cuda 2.5%
  • Shell 0.7%