Anki 2.1 is the upcoming version of the popular spaced repetition software. If you want to write plugins, you might want to have the option to run Anki 2.1 from source for debugging purposes. Here I will outline, how I set up my system to build and run Anki from source.
You can style your cards in Anki with CSS, that’s nothing new. But we can also use some not so obvious CSS to add visual cues to help us remember stuff on our cards.
VSCode has become a powerful editor for Python. Here I share my setup, to develop Anki addons using VSCode.
Anki uses a SQLite database to keep track of your reviews and cards. I always wanted to use R to create some graphs and visualize my learning process. Here is some code, to get you started as well!
Tired of copying and pasting various CSS snippets across multiple cards? By using the CSS
@include, you can share the same CSS file across multiple cards.
You’ll most likely have a general idea of a “pixel”. But what happens to a pixel when we try to scale up a complete image? Do we get a big pixel? And what size does a pixel have? We will have a basic look and try to get a more accurate idea of pixels. We will also learn, that some manipulations are required in order to magnify or rotate pictures.
Have you ever seen a dialog, asking you for a bit depth when saving an image? Here we will take a short stroll into the storage of image information and see, how a computer needs to transform information in order to store it on disc. We will talk about artifacts and problems that could arise, if no appropriate bit depth is chosen. Finally, we will check out histograms to assess the quality of an image.
Often times you are interested in features of a certain color. We will look at how to extract the different aspects of color models in ImageJ and see how we can use the Color Threshold option to select features based on their visual appearance.
When you start working with digital images, some fundamentals should be known. Here we will take a look at color spaces and models — ways to represent and break up the “contents” of a color. This knowledge can come in handy, when you want to do automatic feature detection in an image. Maybe you are interested in red precipitates or want to distinguish a purple cell from a green one? Or maybe you are just interested in some basics about images without complicated formulas.