[Caffe] Try out Caffe with Python code

This document is just a testing record to try out on Caffe with Python code. I refer to this blog. For using Python, we can easily to access every data flow blob in layers, including diff blob, weight blob and bias blob. It is so convenient for us to understand the change of training phase's weights and what have done in each step.

[Caffe] How to use Caffe to solve the regression problem?

There is a question coming up to my mind recently. How to use Caffe to solve the regression problem? We used to see a bunch of examples related to image recognition with labels and they are classification problem. In my experience, I have done this problem using TensorFlow, not Caffe. But, I think in theory they are both the same. The key point is using EuclideanLossLayer as the final Loss Layer and it's the detail from the official web site:

[Debug] Debugging Python and C++ exposed by boost together

During the studying of Caffe, I was curious about how Caffe provides Python interface and what kind of tool uses for wrapping. Then, the answer is Boost.Python. I think for C++ developer, it is worth time to learn and I will study it sooner. In this post, I want to introduce the debugging skill which I found in this post and I believe these are very useful such as debugging Caffe with Python Layer. Here is the link:
https://stackoverflow.com/questions/38898459/debugging-python-and-c-exposed-by-boost-together

[Caffe] Install Caffe and the depended packages

This article is just for me to quickly record the all the steps to install the depended packages for Caffe. So, be careful that it maybe is not good for you to walk through them in your environment. ^_^

# Install CCMAKE

$ sudo apt-get install cmake-curses-gui