\class LogStreamConsumer \brief Convenience object used to facilitate use of C++ stream syntax when logging messages. Order of base classes is LogStre

Now only numpy is supported

YOLO A python interface which emulates a model-like behaviour by wrapping trainers.

Resize image and padding for detection, instance segmentation, pose

YOLOv5 Classification Dataset. Arguments root: Dataset path transform: torchvision transforms, used by default albu

YOLOv5 Classification Dataset. Arguments root: Dataset path transform: torchvision transforms, used by default albu

Exporter A class for exporting a model. Attributes: args (OmegaConf): Configuration for the exporter. save_dir (Path):

Dataloader that reuses workers Uses same syntax as vanilla DataLoader

Dataloader that reuses workers Uses same syntax as vanilla DataLoader

Updated Exponential Moving Average (EMA) from https://github.com/rwightman/pytorch-image-models Keeps a moving average of everything in the model

Mosaic augmentation. Args: imgsz (Sequence[int]): Image size after mosaic pipeline of single image. The shape order should be

Sampler that repeats forever Args: sampler (Sampler)

Sampler that repeats forever Args: sampler (Sampler)

Base Dataset. Args: img_path (str): image path. pipeline (dict): a dict of image transforms. label_path (str): label path,

This implementation is from mmyolo

The BaseModel class is a base class for all the models in the Ultralytics YOLO family.

BasePredictor A base class for creating predictors. Attributes: args (OmegaConf): Configuration for the predictor. save

BaseTrainer > A base class for creating trainers. Attributes: args (OmegaConf): Configuration for the trainer. check_re

BaseValidator A base class for creating validators. Attributes: dataloader (DataLoader): Dataloader to use for validation.

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