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Init Image Transformation

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This article describes how to use the Init Image Transformation component in Azure Machine Learning designer, to initialize image transformation to specify how you want image to be transformed.

How to configure Init Image Transformation

  1. Add the Init Image Transformation component to your pipeline in the designer.

  2. For Resize, specify whether to resize the input PIL Image to the given size. If you choose 'True', you can specify the desired output image size in Size, by default 256.

  3. For Center crop, specify whether to crop the given PIL Image at the center. If you choose 'True', you can specify the desired output image size of the crop in Crop size, by default 224.

  4. For Pad, specify whether to pad the given PIL Image on all sides with the pad value 0. If you choose 'True', you can specify padding (how many pixels to add) on each border in Padding.

  5. For Color jitter, specify whether to randomly change the brightness, contrast and saturation of an image.

  6. For Grayscale, specify whether to convert image to grayscale.

  7. For Random resized crop, specify whether to crop the given PIL Image to random size and aspect ratio. A crop of random size (range from 0.08 to 1.0) of the original size and a random aspect ratio (range from 3/4 to 4/3) of the original aspect ratio is made. This crop is finally resized to given size. This is commonly used in training the Inception networks. If you choose 'True', you can specify the expected output size of each edge in Random size, by default 256.

  8. For Random crop, specify whether to crop the given PIL Image at a random location. If you choose 'True', you can specify the desired output size of the crop in Random crop size, by default 224.

  9. For Random horizontal flip, specify whether to horizontally flip the given PIL Image randomly with probability 0.5.

  10. For Random vertical flip, specify whether to vertically flip the given PIL Image randomly with probability 0.5.

  11. For Random rotation, specify whether to rotate the image by angle. If you choose 'True', you can specify in range of degrees by setting Random rotation degrees, which means (-degrees, +degrees), by default 0.

  12. For Random affine, specify whether to random affine transformation of the image keeping center invariant. If you choose 'True', you can specify in range of degrees to select from in Random affine degrees, which means (-degrees, +degrees), by default 0.

  13. For Random grayscale, specify whether to randomly convert image to grayscale with probability 0.1.

  14. For Random perspective, specify whether to performs Perspective transformation of the given PIL Image randomly with probability 0.5.

  15. Connect to Apply Image Transformation component, to apply the transformation specified above to the input image dataset.

  16. Submit the pipeline.

Results

After transformation is completed, you can find transformed images in the output of Apply Image Transformation component.

Technical notes

Refer to https://pytorch.org/vision/stable/transforms.html for more info about image transformation.

Component parameters

Name Range Type Default Description
Resize Any Boolean True Resize the input PIL Image to the given size
Size >=1 Integer 256 Specify the desired output size
Center crop Any Boolean True Crops the given PIL Image at the center
Crop size >=1 Integer 224 Specify the desired output size of the crop
Pad Any Boolean False Pad the given PIL Image on all sides with the given "pad" value
Padding >=0 Integer 0 Padding on each border
Color jitter Any Boolean False Randomly change the brightness, contrast and saturation of an image
Grayscale Any Boolean False Convert image to grayscale
Random resized crop Any Boolean False Crop the given PIL Image to random size and aspect ratio
Random size >=1 Integer 256 Expected output size of each edge
Random crop Any Boolean False Crop the given PIL Image at a random location
Random crop size >=1 Integer 224 Desired output size of the crop
Random horizontal flip Any Boolean True Horizontally flip the given PIL Image randomly with a given probability
Random vertical flip Any Boolean False Vertically flip the given PIL Image randomly with a given probability
Random rotation Any Boolean False Rotate the image by angle
Random rotation degrees [0,180] Integer 0 Range of degrees to select from
Random affine Any Boolean False Random affine transformation of the image keeping center invariant
Random affine degrees [0,180] Integer 0 Range of degrees to select from
Random grayscale Any Boolean False Randomly convert image to grayscale with probability 0.1
Random perspective Any Boolean False Performs Perspective transformation of the given PIL Image randomly with probability 0.5
Random erasing Any Boolean False Randomly selects a rectangle region in an image and erases its pixels with probability 0.5

Output

Name Type Description
Output image transformation TransformationDirectory Output image transformation that can be connected to Apply Image Transformation component.

Next steps

See the set of components available to Azure Machine Learning.