|
|
|
|
# Ultralytics YOLO 🚀, GPL-3.0 license
|
|
|
|
|
|
|
|
|
|
from ultralytics.yolo.utils.torch_utils import get_flops, get_num_params
|
|
|
|
|
|
|
|
|
|
try:
|
|
|
|
|
import comet_ml
|
|
|
|
|
|
|
|
|
|
except (ModuleNotFoundError, ImportError):
|
|
|
|
|
comet_ml = None
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
def on_pretrain_routine_start(trainer):
|
|
|
|
|
experiment = comet_ml.Experiment(project_name=trainer.args.project or "YOLOv8")
|
|
|
|
|
experiment.log_parameters(vars(trainer.args))
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
def on_train_epoch_end(trainer):
|
|
|
|
|
experiment = comet_ml.get_global_experiment()
|
|
|
|
|
experiment.log_metrics(trainer.label_loss_items(trainer.tloss, prefix="train"), step=trainer.epoch + 1)
|
|
|
|
|
if trainer.epoch == 1:
|
|
|
|
|
for f in trainer.save_dir.glob('train_batch*.jpg'):
|
|
|
|
|
experiment.log_image(f, name=f.stem, step=trainer.epoch + 1)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
def on_fit_epoch_end(trainer):
|
|
|
|
|
experiment = comet_ml.get_global_experiment()
|
|
|
|
|
experiment.log_metrics(trainer.metrics, step=trainer.epoch + 1)
|
|
|
|
|
if trainer.epoch == 0:
|
|
|
|
|
model_info = {
|
|
|
|
|
"model/parameters": get_num_params(trainer.model),
|
|
|
|
|
"model/GFLOPs": round(get_flops(trainer.model), 3),
|
|
|
|
|
"model/speed(ms)": round(trainer.validator.speed[1], 3)}
|
|
|
|
|
experiment.log_metrics(model_info, step=trainer.epoch + 1)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
def on_train_end(trainer):
|
|
|
|
|
experiment = comet_ml.get_global_experiment()
|
|
|
|
|
experiment.log_model("YOLOv8", file_or_folder=trainer.best, file_name="best.pt", overwrite=True)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
callbacks = {
|
|
|
|
|
"on_pretrain_routine_start": on_pretrain_routine_start,
|
|
|
|
|
"on_train_epoch_end": on_train_epoch_end,
|
|
|
|
|
"on_fit_epoch_end": on_fit_epoch_end,
|
|
|
|
|
"on_train_end": on_train_end} if comet_ml else {}
|
