Slightly adapted example for adding new operations in Tensorflow taken from the official documentation. The files should be copied to
tensorflow/core/user_ops. The new operation is compiled using
bazel build -c opt //tensorflow/core/user_ops:zero_out.so from the Tensorflow root. The generated
.so file can usually be found by searching
bazel-bin. This code does not include the corresponding gradient function yet.
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.
Example demonstrating how to use SQLiteCpp for working with SQLite databases from C++.