class_docstr: Apply Random color jitter to the input image.
  It randomly distorts the hue, saturation, brightness of an image.
docstr: Args:
      strength (float): A number used to quantify the strength of the color distortion.
      p (float): probability of random application
code: def __init__(self, strength, prob):
      """
      Args:
          strength (float): A number used to quantify the strength of the color distortion.
          p (float): probability of random application
      """
      self.strength = strength
      self.p = prob
      self.color_jitter = pth_transforms.ColorJitter(
          0.8 * self.strength,
          0.8 * self.strength,
          0.8 * self.strength,
          0.2 * self.strength,
      )
      self.rnd_color_jitter = pth_transforms.RandomApply(
          [self.color_jitter], p=self.p
      )
  
file_path: vissl/vissl/data/ssl_transforms/img_pil_random_color_jitter.py
imports: import logging
  from typing import Any, Dict
  import torchvision.transforms
  from classy_vision.dataset.transforms import register_transform
  from classy_vision.dataset.transforms.classy_transform import ClassyTransform
label_desc: Use image node_id 1 to create a new ImgPilRandomColorJitter object from inherited base classes: ClassyTransform with example: obj = ImgPilRandomColorJitter(strength, prob)