고급 사용자 지정

from ultralytics.models.yolo.detect import DetectionTrainer

trainer = DetectionTrainer(overrides={...})
trainer.train()
trained_model = trainer.best  # get best model

from ultralytics.models.yolo.detect import DetectionTrainer


class CustomTrainer(DetectionTrainer):
    def get_model(self, cfg, weights):
        """Loads a custom detection model given configuration and weight files."""
        ...


trainer = CustomTrainer(overrides={...})
trainer.train()

from ultralytics.models.yolo.detect import DetectionTrainer
from ultralytics.nn.tasks import DetectionModel


class MyCustomModel(DetectionModel):
    def init_criterion(self):
        """Initializes the loss function and adds a callback for uploading the model to Google Drive every 10 epochs."""
        ...


class CustomTrainer(DetectionTrainer):
    def get_model(self, cfg, weights):
        """Returns a customized detection model instance configured with specified config and weights."""
        return MyCustomModel(...)


# callback to upload model weights
def log_model(trainer):
    """Logs the path of the last model weight used by the trainer."""
    last_weight_path = trainer.last
    print(last_weight_path)


trainer = CustomTrainer(overrides={...})
trainer.add_callback("on_train_epoch_end", log_model)  # Adds to existing callback
trainer.train()

from ultralytics.models.yolo.detect import DetectionTrainer


class CustomTrainer(DetectionTrainer):
    def get_model(self, cfg, weights):
        """Loads a custom detection model given configuration and weight files."""
        ...


trainer = CustomTrainer(overrides={...})
trainer.train()
trained_model = trainer.best  # get best model

from ultralytics.models.yolo.detect import DetectionTrainer


# callback to upload model weights
def log_model(trainer):
    """Logs the path of the last model weight used by the trainer."""
    last_weight_path = trainer.last
    print(last_weight_path)


trainer = DetectionTrainer(overrides={...})
trainer.add_callback("on_train_epoch_end", log_model)  # Adds to existing callbacks
trainer.train()

from ultralytics.models.yolo.detect import DetectionTrainer


class CustomDetectionTrainer(DetectionTrainer):
    def get_model(self, cfg, weights):
        """Loads a custom detection model."""
        ...


trainer = CustomDetectionTrainer(overrides={...})
trainer.train()