devlog 6: I’M A GENIUS(not really but it worked). we finally inference-d with model after training its pretty good, though in the scans I’m gonna pre-process so that it doesn’t confuse grass and trees but its not too bad at that. also added unit test though not complete, renamed a few files, and added a new endpoint to get around downtime/hibernating backed. it took a bit too long for small devlog but next ill finish unit test, dockerfile, likely retrain(possibly with more bands), and optimize so i don’t get any OOM with PyTorch, model and google earth engine. but no hiccups besides i don’t really know what to do so i just did random stuff like unit test, and also visualizing so i can verify my self was a minor hiccup. I’m gonna deploy on backend and so i can run model and earth engine and see how resource intensive it is. maybe implement sentile-1 as well to get around clouds, as you can see the cloud leaves a void with no predictions and illegal loggers use that to advantage in Brazil and log in rainy season.