This week, I was able to finish the initial implementation of the YOLOv8 OBB model. Unfortunately, I found that the dataset I found on Roboflow last week is no in the format that YOLO models expect. Inside of having a (x, y, w, h, theta, class label) ground truth for each object in an image, the dataset actually has the following ground truth (bbox coordinate 1, bbox coordinate 2, bbox coordinate 3, bbox coordinate 4, class label). In order to finish this, I need to re-annotate the dataset. I plan on finishing a script by the end of tonight to fix this problem.
Currently, I am a little behind schedule. To remedy this, I plan on continuing to work on implementing the training infrastructure tomorrow and Monday. My goal is to start training the model by Tuesday. This way I will have sufficient time to (i) debug my model implementation and (ii) write data augmentations to artificially increase the amount of data.
Next week, I plan to have the model trained for a reasonable number of epochs to determine what optimizations I need to do on it for the best performance on the training dataset.