mlr_pipeopsaugment_random_resized_crop: Random Resized Crop Augmentation
In mlr3torch: Deep Learning with 'mlr3'
mlr_pipeops_augment_random_resized_crop R Documentation
Random Resized Crop Augmentation
Description
Calls torchvision::transform_random_resized_crop,
see there for more information on the parameters.
The preprocessing is applied to each element of a batch individually.
Format
R6Class inheriting from PipeOpTaskPreprocTorch.
Parameters
Id Type Default Levels Range
size untyped - -
scale untyped c(0.08, 1) -
ratio untyped c(3/4, 4/3) -
interpolation integer 2 [0, 3]
stages character - train, predict, both -
affect_columns untyped selector_all() -
mlr3torch documentation built on April 4, 2025, 3:03 a.m.
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| mlr_pipeops_augment_random_resized_crop | R Documentation |
Random Resized Crop Augmentation
Description
Calls torchvision::transform_random_resized_crop,
see there for more information on the parameters.
The preprocessing is applied to each element of a batch individually.
Format
R6Class inheriting from PipeOpTaskPreprocTorch.
Parameters
| Id | Type | Default | Levels | Range |
| size | untyped | - | - | |
| scale | untyped | c(0.08, 1) | - | |
| ratio | untyped | c(3/4, 4/3) | - | |
| interpolation | integer | 2 | [0, 3] |
|
| stages | character | - | train, predict, both | - |
| affect_columns | untyped | selector_all() | - | |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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