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paddleseg.transforms

Compose

CLASS paddleseg.transforms.Compose(transforms, to_rgb=True)

Do transformation on input data with corresponding pre-processing and augmentation operations.
The shape of input data to all operations is [height, width, channels].

Args

  • transforms (list): A list contains data pre-processing or augmentation.
  • to_rgb (bool, optional): If converting image to RGB color space. Default: True.

Raises

  • TypeError: When 'transforms' is not a list.
  • ValueError: when the length of 'transforms' is less than 1.

RandomHorizontalFlip

CLASS paddleseg.transforms.RandomHorizontalFlip(prob=0.5)

Flip an image horizontally with a certain probability.

Args

  • prob (float, optional): A probability of horizontally flipping. Default: 0.5.

RandomVerticalFlip

CLASS paddleseg.transforms.RandomVerticalFlip(prob=0.1)

Flip an image vertically with a certain probability.

Args

  • prob (float, optional): A probability of vertical flipping. Default: 0.1.

Resize

CLASS paddleseg.transforms.Resize(target_size=(512, 512), interp='LINEAR')

Resize an image.

Args

  • target_size (list|tuple, optional): The target size of image. Default: (512, 512).
  • interp (str, optional): The interpolation mode of resize is consistent with opencv. ['NEAREST', 'LINEAR', 'CUBIC', 'AREA', 'LANCZOS4', 'RANDOM']. Note that when it is 'RANDOM', a random interpolation mode would be specified. Default: "LINEAR".

Raises

  • TypeError: When 'target_size' type is neither list nor tuple.
  • ValueError: When "interp" is out of pre-defined methods ('NEAREST', 'LINEAR', 'CUBIC', 'AREA', 'LANCZOS4', 'RANDOM').

ResizeByLong

CLASS paddleseg.transforms.ResizeByLong(long_size)

Resize the long side of an image to given size, and then scale the other side proportionally.

Args

  • long_size (int): The target size of long side.

ResizeRangeScaling

CLASS paddleseg.transforms.ResizeRangeScaling(min_value=400, max_value=600)

Resize the long side of an image into a range, and then scale the other side proportionally.

Args

  • min_value (int, optional): The minimum value of long side after resize. Default: 400.
  • max_value (int, optional): The maximum value of long side after resize. Default: 600.

ResizeStepScaling

CLASS paddleseg.transforms.ResizeStepScaling(min_scale_factor=0.75, max_scale_factor=1.25, scale_step_size=0.25)

Scale an image proportionally within a range.

Args

  • min_scale_factor** (float, optional): The minimum scale. Default: 0.75.
  • max_scale_factor (float, optional): The maximum scale. Default: 1.25.
  • scale_step_size (float, optional): The scale interval. Default: 0.25.

Raises

  • ValueError: When min_scale_factor is smaller than max_scale_factor.

Normalize

CLASS paddleseg.transforms.Normalize(mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5))

Normalize an image.

Args

  • mean (list, optional): The mean value of a data set. Default: [0.5, 0.5, 0.5].
  • std (list, optional): The standard deviation of a data set. Default: [0.5, 0.5, 0.5].

Raises

  • ValueError: When mean/std is not list or any value in std is 0.

Padding

CLASS paddleseg.transforms.Padding(target_size, im_padding_value=(127.5, 127.5, 127.5), label_padding_value=255)

Add bottom-right padding to a raw image or annotation image.

Args

  • target_size (list|tuple): The target size after padding.
  • im_padding_value (list, optional): The padding value of raw image. Default: [127.5, 127.5, 127.5].
  • label_padding_value (int, optional): The padding value of annotation image. Default: 255.

Raises

  • TypeError: When target_size is neither list nor tuple.
  • ValueError: When the length of target_size is not 2.

RandomPaddingCrop

CLASS paddleseg.transforms.RandomPaddingCrop(crop_size=(512, 512), im_padding_value=(127.5, 127.5, 127.5), label_padding_value=255)

Crop a sub-image from a raw image and annotation image randomly. If the target cropping size
is larger than original image, then the bottom-right padding will be added.

Args

  • crop_size (tuple, optional): The target cropping size. Default: (512, 512).
  • im_padding_value (list, optional): The padding value of raw image. Default: [127.5, 127.5, 127.5].
  • label_padding_value (int, optional): The padding value of annotation image. Default: 255.

Raises

  • TypeError: When crop_size is neither list nor tuple.
  • ValueError: When the length of crop_size is not 2.

RandomBlur

CLASS paddleseg.transforms.RandomBlur(prob=0.1)

Blurring an image by a Gaussian function with a certain probability.

Args

  • prob (float, optional): A probability of blurring an image. Default: 0.1.

RandomRotation

CLASS paddleseg.transforms.RandomRotation(max_rotation=15, im_padding_value=(127.5, 127.5, 127.5), label_padding_value=255)

Rotate an image randomly with padding.

Args

  • max_rotation (float, optional): The maximum rotation degree. Default: 15.
  • im_padding_value (list, optional): The padding value of raw image. Default: [127.5, 127.5, 127.5].
  • label_padding_value (int, optional): The padding value of annotation image. Default: 255.

RandomScaleAspect

CLASS paddleseg.transforms.RandomScaleAspect(min_scale=0.5, aspect_ratio=0.33)

Crop a sub-image from an original image with a range of area ratio and aspect and
then scale the sub-image back to the size of the original image.

Args

  • min_scale (float, optional): The minimum area ratio of cropped image to the original image. Default: 0.5.
  • aspect_ratio (float, optional): The minimum aspect ratio. Default: 0.33.

RandomDistort

CLASS paddleseg.transforms.RandomDistort(brightness_range=0.5, brightness_prob=0.5, contrast_range=0.5, contrast_prob=0.5, saturation_range=0.5, saturation_prob=0.5, hue_range=18, hue_prob=0.5)

Distort an image with random configurations.

Args

  • brightness_range (float, optional): A range of brightness. Default: 0.5.
  • brightness_prob (float, optional): A probability of adjusting brightness. Default: 0.5.
  • contrast_range (float, optional): A range of contrast. Default: 0.5.
  • contrast_prob (float, optional): A probability of adjusting contrast. Default: 0.5.
  • saturation_range (float, optional): A range of saturation. Default: 0.5.
  • saturation_prob (float, optional): A probability of adjusting saturation. Default: 0.5.
  • hue_range (int, optional): A range of hue. Default: 18.
  • hue_prob (float, optional): A probability of adjusting hue. Default: 0.5.