Post-Processing Transform YAML References

The sections in this article are the available post-processing transforms.

BinaryPixelThresholdRule

• Type: Object
• Category: Postprocessing
• Description: Converts a binary segmentation mask to the image-level OK/NG result based on a percentage of pixels greater than the probability threshold.
• Properties:
  • probability_threshold:
    • Type: Number
    • Default: None
    • Minimum: 0
    • Maximum: 1
  • area_percent_threshold:
    • Type: Number
    • Default: None
    • Minimum: 0
    • Maximum: 1
  • always_apply:
    • Type: Boolean
    • Default: False
  • p:
    • Type: Number
    • Default: 1.0
    • Minimum: 0
    • Maximum: 1

FilterBBoxesDimensions

• Type: Object
• Category: Postprocessing
• Description: Transform that filters boxes of a particular class depending on the dimensions.
• Properties:
  • defect_map:
    • Type: String
  • height_threshold:
    • Type: Integer
    • Default: None
    • Minimum: 0
  • width_threshold:
    • Type: Integer
    • Default: None
    • Minimum: 0
  • to_ignore:
    • Type: Array
    • Items:
      • Type: String
  • filter_slim:
    • Type: Boolean
    • Default: True
  • filter_short:
    • Type: Boolean
    • Default: True
  • always_apply:
    • Type: Boolean
    • Default: False
  • p:
    • Type: Number
    • Default: 1.0
    • Minimum: 0
    • Maximum: 1

FilterMaskDimensions

• Type: Object
• Category: Postprocessing
• Description: Zeroes out mask values above 0 whose area is below a certain threshold. The threshold can be applied per category.
• Properties:
  • area_percent_threshold:
    • anyOf:
      • Type: Number
      • Default: 0.0
      • Minimum: 0
      • Maximum: 1
    • Type: Array
      • MinItems: 1
      • Default: [0.0]
      • Items:
        • Type: Number
        • Minimum: 0
  • always_apply:
    • Type: Boolean
    • Default: False
  • p:
    • Type: Number
    • Default: 1.0
    • Minimum: 0
    • Maximum: 1

FilterMaskScore

• Type: Object
• Category: Postprocessing
• Description: Zeroes out mask_scores that are below a certain threshold. The threshold can be applied per category.
• Properties:
  • score_threshold:
    • anyOf:
      • Type: Number
      • Default: 0.5
      • Minimum: 0
      • Maximum: 1
    • Type: Array
      • MinItems: 1
      • Default: [0.5]
      • Items:
      • Type: Number
      • Minimum: 0
  • always_apply:
    • Type: Boolean
    • Default: False
  • p:
    • Type: Number
    • Default: 1.0
    • Minimum: 0
    • Maximum: 1

ObjectDetectionToClassification

• Type: Object
• Category: Postprocessing
• Description: Transforms an Object Detection output into a Classification output by taking the bounding box with the highest score. If the key label is passed keyword argument, this transform will ignore it.
• Properties:
  • always_apply:
    • Type: Boolean
    • Default: False
  • p:
    • Type: Number
    • Default: 1.0
    • Minimum: 0
    • Maximum: 1

SegmentationToClassification

• Type: Object
• Category: Postprocessing
• Description: Transforms a multi-class Segmentation output into a Classification output. The Segmentation output can be in terms of both probabilities (using the mask_scores keyword argument) and indices (using mask keyword argument). If both mask and mask_scores are provided, we will going to use mask to compute this transform. If the key label is passed keyword argument, this transform will ignore it.
  Caution:

  This transform does not check for pixel connections before computing the predicted area
• Properties:
  • always_apply:
    • Type: Boolean
    • Default: False
  • p:
    • Type: Number
    • Default: 1.0
    • Minimum: 0
    • Maximum: 1

WarpPerspective

• Type: Object
• Category: Postprocessing
• Description: WarpPerspective performs 4 point transformation of a region in the input image. (Reference)
• Properties:
  • original_roi:
    • Type: array
    • Default: 0
    • Items:
      • Type: Number
      • Minimum: 0
      • Maximum: 1
  • dest_roi:
    • Type: Array
    • Default: 0
    • Items:
      • Type: Number
      • Minimum: 0
      • Maximum: 1
  • always_apply:
    • Type: Boolean
    • Default: False
  • p:
    • Type: Number
    • Default: 1.0
    • Minimum: 0
    • Maximum: 1