Handwritten digit recognition

(probably) Last devlog before shipping
I added some tools to made adding training samples easier and faster. In the gui, there is a spinner to select which number you have drawn, and a button to save your image as a training sample in the correct folder. Each file is saved with the timestamp so that they do not overlap. With this i added a lot more training samples of each number.
Also i made the brush thing better. Before, it used to just set the pixel your mouse was on to white. Now, it has a better brush system with thickness and strength.

I made a panel in the GUI to see the live output as you draw. It shows the confidence values of each number (sigmoid the activations) as a bar graph kind of, as well as the actual predicted answer.
I also changed the structure of the network in the backend. I think i’m close to shipping

I finally got the github repo working despite some dubious ownership error?
Training the model every time you run it is stupid so i seperated the training code into another class called Train, so first you train the model which writes the weights of the trained model into a file. Then the file is read by the main thing and initialises the model with those weights.
I also worked on a readme

I made the minimum viable product (barely). This project is a thing where you draw a number and AI will try to guess it. The interface for now has only a 32x32 pixel canvas for drawing and a reset button and the AI output is given in the terminal. Later i will improve this. For the AI im using my own AI library and training it using a bunch of labeled images of numbers. At the moment i only have 1 image for each number but i will add more later this is only for testing.