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