التخصيص المتقدم#

from ultralytics.models.yolo.detect import DetectionTrainer

trainer = DetectionTrainer(overrides={...})
trainer.train()
trained_model = trainer.best  # ⁨الحصول على أفضل نموذج⁩

from ultralytics.models.yolo.detect import DetectionTrainer

class CustomTrainer(DetectionTrainer):
    def get_model(self, cfg=None, weights=None, verbose=True):
        """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 a custom loss function for the model."""

class CustomTrainer(DetectionTrainer):
    def get_model(self, cfg=None, weights=None, verbose=True):
        """Returns a customized detection model instance configured with specified config and weights."""
        return MyCustomModel(...)

# ⁨رد نداء لتسجيل أوزان النموذج⁩
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)  # ⁨يُضاف إلى ردود النداء الحالية⁩
trainer.train()

from ultralytics import YOLO
from ultralytics.models.yolo.detect import DetectionTrainer

# ⁨إنشاء مدرب مخصص⁩
class MyCustomTrainer(DetectionTrainer):
    def get_model(self, cfg=None, weights=None, verbose=True):
        """Custom code implementation."""

# ⁨تهيئة نموذج YOLO⁩
model = YOLO("yolo26n.pt")

# ⁨التدريب باستخدام مدرب مخصص⁩
results = model.train(trainer=MyCustomTrainer, data="coco8.yaml", epochs=3)