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@mikonvergence mikonvergence released this 13 Dec 16:20
· 38 commits to main since this release

Major Changes 🔥

  • 🏭 Introducing CloudGenerator() which encapsulates a specific configuration, and generation probabilities (cloud_p and shadow_p). It is compatible as PyTorch module (you can plug it into augmentation pipelines, like torchvision or albumentations)
my_gen=CloudGenerator(WIDE_CONFIG,cloud_p=1.0,shadow_p=0.5)
my_gen(my_image) # will act just like add_cloud_and_shadow() but will preserve the same configuration!

  • 🌈 Channel-Specific Cloud Magnitude allows for channels to have slightly different cloud strengths (since this strength is generally dependent on carrier wavelength) by setting channel_magnitude_shift` to a non-zero value:

ch


  • 😷 Segmentation Mask Functionality allows you to call the segmentation_mask(cloud_mask,shadow_mask) method, which will return a segmentation mask for your generated clouds and shadows!

simple_seg

...you can even set a range thin_range to something like (0.05,0.5) to also differentiate between thin and thick clouds

thin_seg

and this is an example content of each label:

labels1


I hope these features prove useful! 🚀