Cool project, any specific reason you went with YOLOv7?

I know you aren't going to release the dataset but I'd be interesting in any info you are willing to share on augmentations you used and how you generated the synthetic imagery, and what sort of lift you got out of it.

Some of the design choices of YOLOv7 make more sense to me in the choices of default augmentations and the structures of the very large versions of the networks. I find I can push it to marginally better recall. It’s slower than Ultralytics’ V8 but if you want to do stuff like offline processing of satellite imagery for instance or get 1fps on occupancy of a parking lot that kind of performance really doesn’t matter.

Any specific changes with the new release?

new dataset, new classes and model is yolov8 because most people prefer it. Also open weights.