This week I set up the software necessary to label the input data for the YOLO algorithm. The ML model essentially takes in images as well as coordinates for where in the image it is detected associated to its label. In order to generate these coordinates accurately, it is necessary to use the YoloLabel software. With this created and the ML model set up, it is all ready to take in the cards to train the model effectively and then optimize it to be faster. We also got the cards figured out. With the trouble we were facing with the bitmapping, we got two backup plans so that if we can not figure out the bitmaps by Monday, we can use the backup designs of the cards to start printing them out and training our model.
I am a bit behind on schedule because we did not account for spring break but once we get the data printed out, I should be able to train the model quickly and be able to start working with the camera and transferring my model over to the system.
In the upcoming week, I hope to generate all the coordinates and labels for all of the input data pictures. I hope to then feed them into the model and start being able to perform object detection. I also hope to optimize the model by changing the logic to only look for cards that have been dealt to the user which can be determined by the game state.