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GenerateSoftSeg

class mmedit.datasets.transforms.GenerateSoftSeg(fg_thr=0.2, border_width=25, erode_ksize=3, dilate_ksize=5, erode_iter_range=(10, 20), dilate_iter_range=(3, 7), blur_ksizes=[(21, 21), (31, 31), (41, 41)])[source]

Generate soft segmentation mask from input segmentation mask.

Required key is “seg”, added key is “soft_seg”.

Parameters
  • fg_thr (float, optional) – Threshold of the foreground in the normalized input segmentation mask. Defaults to 0.2.

  • border_width (int, optional) – Width of border to be padded to the bottom of the mask. Defaults to 25.

  • erode_ksize (int, optional) – Fixed kernel size of the erosion. Defaults to 5.

  • dilate_ksize (int, optional) – Fixed kernel size of the dilation. Defaults to 5.

  • erode_iter_range (tuple, optional) – Iteration of erosion. Defaults to (10, 20).

  • dilate_iter_range (tuple, optional) – Iteration of dilation. Defaults to (3, 7).

  • blur_ksizes (list, optional) – List of (h, w) to be selected as the kernel_size of the gaussian blur. Defaults to [(21, 21), (31, 31), (41, 41)].

transform(results: dict) dict[source]

Transform function.

Parameters

results (dict) – A dict containing the necessary information and data for augmentation.

Returns

A dict containing the processed data and information.

Return type

dict

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