Post-Processing Transform YAML References

Article summary

Did you find this summary helpful?

Thank you for your feedback

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

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

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

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

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

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

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

Was this article helpful?

Table of contents