from ultralytics import YOLO
from ultralytics import settings
from roboflow import Roboflow

rf = Roboflow(api_key="V6C1HgdOhbGH9M0SqFog")
project = rf.workspace("ata220180t").project("220180t_carlogos")
version = project.version(5)
dataset = version.download("yolov8")

settings.update({"wandb": True,
                "comet": False,
                "tensorboard": False}
                 )


model = YOLO("yolov8s.pt")  
# result = model.train(data="220180T_carlogos-5/data.yaml",
#                      epochs=30,
#                      save_period=1,
#                      batch=50,
#                      device= "cpu",
#                      project='Car-Logos',
#                      plots=True,
#                      freeze=5,
#                      lr0= 1e-7,
#                      optimizer = "Adam" ,
#                      cls = 0.1,
#                      )


model = YOLO("Car-Logos/train17/weights/best.pt")
validation_results = model.val(data="220180T_carlogos.v5i.yolov8-obb/data.yaml", device="cpu")

model.save("car_logos.pt")