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ultralytics 8.0.89 SAM predict and auto-annotate (#2298)

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Glenn Jocher
2023-04-28 00:36:50 +02:00
committed by GitHub
parent 3e118f6170
commit 243fc4b1fe
44 changed files with 2915 additions and 440 deletions
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22
ultralytics/yolo/data/base.py
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@ -24,17 +24,17 @@ class BaseDataset(Dataset):
Base dataset class for loading and processing image data.
Args:
img_path (str): Image path.
imgsz (int): Target image size for resizing. Default is 640.
cache (bool): Cache images in memory or on disk for faster loading. Default is False.
augment (bool): Apply data augmentation. Default is True.
hyp (dict): Dictionary of hyperparameters for data augmentation. Default is None.
prefix (str): Prefix for file paths. Default is an empty string.
rect (bool): Enable rectangular training. Default is False.
batch_size (int): Batch size for rectangular training. Default is None.
stride (int): Stride for rectangular training. Default is 32.
pad (float): Padding for rectangular training. Default is 0.5.
single_cls (bool): Use a single class for all labels. Default is False.
img_path (str): Path to the folder containing images.
imgsz (int, optional): Image size. Defaults to 640.
cache (bool, optional): Cache images to RAM or disk during training. Defaults to False.
augment (bool, optional): If True, data augmentation is applied. Defaults to True.
hyp (dict, optional): Hyperparameters to apply data augmentation. Defaults to None.
prefix (str, optional): Prefix to print in log messages. Defaults to ''.
rect (bool, optional): If True, rectangular training is used. Defaults to False.
batch_size (int, optional): Size of batches. Defaults to None.
stride (int, optional): Stride. Defaults to 32.
pad (float, optional): Padding. Defaults to 0.0.
single_cls (bool, optional): If True, single class training is used. Defaults to False.
classes (list): List of included classes. Default is None.
Attributes: