Saturday, February 17, 2018

Week 5

What did you do this past week?
I worked with my team to finish the first project for the course. We spent a lot of this week designing our API and outlining our documentation. This allowed us to get a good idea of what we want to do for the project the rest of the semester. I also spent some time learning React and also figuring out the best way to implement the rest of the website with Flask.

What's in your way?
I have been having trouble learning React. It is kind of tricky and I plan to get a book on it so I can get some more formal training. We also need to write a lot of Unit Tests for the next phase of the project. For the first project, we had some misunderstandings between the front-end and back-end teams in getting the website that we had all agreed upon.

What will you do next week?
I plan to write some unit tests for the back-end of our website. Also, we need to get a better workflow to use between our front-end and back-end so that we are more on the same level of thinking and we can better collaborate. This will allow our team to work in pairs without having to be together all the time but still make a cohesive product.

What's my experience of the class?
I really enjoy the class so far! This project has been great and I look forward to continuing the project in future iterations. I really liked the day of class where we acted as programmers and customers to present our work to other groups. That was a very informative experience that gave us some good ideas for the future of the website.

Pick-of-the-week!
I recommend looking at the Darknet for Python and using it with Yolo for object detection. Darknet streamlines the model training process, and Darkflow is a wrapper for Darknet which allows for use with Tensorflow and other Python libraries. Darknet itself was written in C, so the Python Darkflow library is a nice addition because it allows for use of Python.
You can find Darkflow here:
And Find Darknet here:
And the guy that made darknet has a crazy resume lol:

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