Was going to answer this. I very much agree with the article, but deep learning is absolutely a game changer for computer vision.

I myself tried several time to “not use ML” for some easy computer vision tasks where traditional CV methods are supposed to work. Well I always end up in situations where they don’t work well without fine parameter tuning, and tuning the parameter for a situation breaks the model in other situations, so you start adding layers of complexity to automatically tune the parameters, but the parameter tuning system also has its own parameters... While a simple neural net is trained easily and is much more robust, saving a lot of time and complexity.

Another proof of that is that CV products only started meaningfully entering the market after ML became applicable to CV (after 2015 for complex tasks, or earlier for simpler stuff like MNIST).