Tensorflow Introduction and 3D Object Recognition

Zhiang Chen

zxc251@case.edu

1. Useful Python Packages and Tools

• numpy
  • The input and output of tensorflow network(computational graph) is numpy.ndarray
  • Integrating C/C++
  • Effecient n-dimensional array function (filter,reshaping)
  • Easy to learn
• matplotlib.pyplot
• Jupyter Notebook
  • Web editor for Python and other programming languages(Octave, R, ...)
  • Notes and Codes
  • Debugging in several cells
  • Easy to install (pip/pip3 install ipython) and learn

2. Tensorflow

Though there is no strict rule to build and train a network with Tensorflow, 6 steps are highly recommended. https://github.com/ZhiangChen/deep_learning/blob/master/27_objects/lenet5/lenet5.ipynb

3. 3D Object Recognition

ROS & Tensorflow

• rospy is a Python2 package for ROS. The rospy client API enables Python programmers to quickly interface with ROS Topics, Services, Actions, and Parameters.
• Tensorflow for Python2

ROS Package: auto_recognition2

auto_recognition2/evaluate_image2