# Ultralytics YOLO 🚀, GPL-3.0 license from ultralytics.yolo.utils import LOGGER, TESTS_RUNNING from ultralytics.yolo.utils.torch_utils import get_flops, get_num_params try: import comet_ml assert not TESTS_RUNNING # do not log pytest assert comet_ml.__version__ # verify package is not directory except (ImportError, AssertionError): comet_ml = None def on_pretrain_routine_start(trainer): try: experiment = comet_ml.Experiment(project_name=trainer.args.project or 'YOLOv8') experiment.set_name(trainer.args.name) experiment.log_parameters(vars(trainer.args)) except Exception as e: LOGGER.warning(f'WARNING ⚠️ Comet installed but not initialized correctly, not logging this run. {e}') def on_train_epoch_end(trainer): experiment = comet_ml.get_global_experiment() if 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() if 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['inference'], 3)} experiment.log_metrics(model_info, step=trainer.epoch + 1) def on_train_end(trainer): experiment = comet_ml.get_global_experiment() if experiment: experiment.log_model('YOLOv8', file_or_folder=str(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 {}