BaseAugTransform¶
- class mmcls.datasets.transforms.BaseAugTransform(magnitude_level=10, magnitude_range=None, magnitude_std=0.0, total_level=10, prob=0.5, random_negative_prob=0.5)[源代码]¶
用于组合式增强的数据变换基类
This class provides several common attributions and methods to support the magnitude level mapping and magnitude level randomness in
RandAugment
.- 参数
magnitude_range (Sequence[number], optional) – For augmentation have magnitude argument, maybe “magnitude”, “angle” or other, you can specify the magnitude level mapping range to generate the magnitude argument. For example, assume
total_level
is 10,magnitude_level=3
specify magnitude is 3 ifmagnitude_range=(0, 10)
while specify magnitude is 7 ifmagnitude_range=(10, 0)
. Defaults to None.magnitude_std (Number | str) –
Deviation of magnitude noise applied.
If positive number, the magnitude obeys normal distribution \(\mathcal{N}(magnitude, magnitude_std)\).
If 0 or negative number, magnitude remains unchanged.
If str “inf”, the magnitude obeys uniform distribution \(Uniform(min, magnitude)\).
Defaults to 0.
total_level (int | float) – Total level for the magnitude. Defaults to 10.
prob (float) – The probability for performing transformation therefore should be in range [0, 1]. Defaults to 0.5.
random_negative_prob (float) – The probability that turns the magnitude negative, which should be in range [0,1]. Defaults to 0.
- abstract transform(results)¶
The transform function. All subclass of BaseTransform should override this method.
This function takes the result dict as the input, and can add new items to the dict or modify existing items in the dict. And the result dict will be returned in the end, which allows to concate multiple transforms into a pipeline.