In this article, I discuss a simple Tensorflow operation implemented in C++. While the example mostly builds upon the official documentation, it includes trainable parameters and the gradient computation is implemented in C++, as well. As such, the example is slightly more complex compared to the simple
ZeroOut operation discussed in the documentation.
This article presents an implementation of Felzenszwalb and Huttenlocher’s  graph-based image segmentation algorithm. The implementation is compared to the original implementation by Felzenszwalb in terms of Boundary Recall, Undersegmentation Error and Explained Variation, as used for evaluating superpixel algorithms. In addition, qualitative results are provided. The implementation is publicly available on GitHub.
Running C++ projects on Travis CI may be challenging depending on the libraries used. Here I briefly describe how to run OpenCV and Google GLog on Travis CI.