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Commit 1be3c659 authored by Lucia D. Hradecka's avatar Lucia D. Hradecka
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update readme and docs

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1 merge request!12Make version 1.3.2 default
...@@ -313,7 +313,7 @@ However, you cannot define your own target types, as that would require re-imple ...@@ -313,7 +313,7 @@ However, you cannot define your own target types, as that would require re-imple
### A List of Implemented Transformations ### A List of Implemented Transformations
Point transformations: Intensity-based point transformations:
```python ```python
Normalize Normalize
NormalizeMeanStd NormalizeMeanStd
...@@ -324,14 +324,14 @@ RandomBrightnessContrast ...@@ -324,14 +324,14 @@ RandomBrightnessContrast
RandomGamma RandomGamma
``` ```
Local transformations: Intensity-based local transformations:
```python ```python
GaussianBlur GaussianBlur
RandomGaussianBlur RandomGaussianBlur
RemoveBackgroundGaussian RemoveBackgroundGaussian
``` ```
Geometric transformations: Geometric (spatial) transformations:
```python ```python
AffineTransform AffineTransform
Resize Resize
...@@ -347,6 +347,14 @@ RandomFlip ...@@ -347,6 +347,14 @@ RandomFlip
RandomCrop RandomCrop
``` ```
Other transformations:
```python
Contiguous
StandardizeDatatype
ConversionToFormat
```
### Runtime ### Runtime
Here, we present the execution times (mean ± standard deviation) of individual transformations from our library Here, we present the execution times (mean ± standard deviation) of individual transformations from our library
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...@@ -133,8 +133,8 @@ images of shape ``[150, 300, 300]``, ``[1, 150, 300, 300]``, as well as ``[4, 15 ...@@ -133,8 +133,8 @@ images of shape ``[150, 300, 300]``, ``[1, 150, 300, 300]``, as well as ``[4, 15
If you want to use a multi-channel :class:`mask` or :class:`float_mask`, you have to split it into If you want to use a multi-channel :class:`mask` or :class:`float_mask`, you have to split it into
a set of single-channel :class:`mask` or :class:`float_mask` targets, respectively, and input them a set of single-channel :class:`mask` or :class:`float_mask` targets, respectively, and input them
as stand-alone targets (see as stand-alone targets (see
`the respective section below <https://biovolumentations.readthedocs.io/1.3.1/examples.html#example-transforming-multiple-targets-of-the-same-type>`_. `the respective section below <https://biovolumentations.readthedocs.io/1.3.1/examples.html#example-transforming-multiple-targets-of-the-same-type>`_
below on transforming multiple masks with a single image). on transforming multiple masks with a single image).
The :class:`keypoints` target is represented as a list of tuples. Each tuple represents The :class:`keypoints` target is represented as a list of tuples. Each tuple represents
the absolute coordinates of a keypoint in the volume, so it must contain either 3 or 4 numbers the absolute coordinates of a keypoint in the volume, so it must contain either 3 or 4 numbers
...@@ -148,6 +148,9 @@ as keyword arguments of a call to the :class:`Compose` object. Consequently, the ...@@ -148,6 +148,9 @@ as keyword arguments of a call to the :class:`Compose` object. Consequently, the
dictionary using the same keys. The default key values are :class:`'image'`, :class:`'mask'`, :class:`'float_mask'`, dictionary using the same keys. The default key values are :class:`'image'`, :class:`'mask'`, :class:`'float_mask'`,
:class:`'keypoints'`, :class:`'bboxes'`, and :class:`'value'`. :class:`'keypoints'`, :class:`'bboxes'`, and :class:`'value'`.
Prior to applying any user-defined transformation, the :class:`mask` and :class:`float_mask` targets are type-casted to
integer and floating-point datatypes, respectively.
Importantly, there must always be an :class:`image`-type target in the sample. Importantly, there must always be an :class:`image`-type target in the sample.
You cannot define your own target types; that would require re-implementing all existing transforms. You cannot define your own target types; that would require re-implementing all existing transforms.
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