Sure, the role of neural network used in this project is recognizing hand written digits. The input is a 81x81 2D grid. There are a few fully-connected layers trying classify all these input pixels into 10 possible outputs and assign each output with a probability. The outputs are the 10 digits in our number system.

This model is trained using pytorch, a machine learning framework, and exported to onnx. The onnx file then gets used by a backend server written in python that will communicate with godot.

The math behind how fully-connected layers work is a little complicated. If you want to get into the details of how exactly machine “learns” you should go watch some youtube tutorials about back-propagation and statistic modeling.

The tricky part here is embedding an entire video (bad apple in this case) into the weights of the fully-connected layers. Training the model with custom-set limitations was really hard. This model’s accuracy at guessing a human’s handwriting correctly is only about 60% based on the augmented dataset that it was tested on.

I think it’s lemmy’s parsing issue that the “The” word and the repo link got merged

干嘛那么凶，别人就问一句问题

can someone confirm if this is the real oldest lemmy post?

the oldest commit on github seems like its made about 4 years ago