Support
Supported configuration options.
Used throughout the code to ensure consistency. These should be kept in sync with the corresponding configuration options in the Pydantic models.
SupportedActivation
Bases: StrEnum
Supported activation functions.
- None, no activation will be used.
- Sigmoid
- Softmax
- Tanh
- ReLU
- LeakyReLU
All activations are defined in PyTorch.
See: https://pytorch.org/docs/stable/nn.html#loss-functions
SupportedAlgorithm
Bases: StrEnum
Algorithms available in CAREamics.
These definitions are the same as the keyword name of the algorithm
configurations.
CARE = 'care'
class-attribute
instance-attribute
Content-aware image restoration, a supervised algorithm used for a variety of tasks.
DENOISPLIT = 'denoisplit'
class-attribute
instance-attribute
An image splitting and denoising approach based on ladder VAE architectures.
HDN = 'hdn'
class-attribute
instance-attribute
Hierarchical Denoising Network, an unsupervised denoising algorithm
MICROSPLIT = 'microsplit'
class-attribute
instance-attribute
A micro-level image splitting approach based on ladder VAE architectures.
MUSPLIT = 'musplit'
class-attribute
instance-attribute
An image splitting approach based on ladder VAE architectures.
N2N = 'n2n'
class-attribute
instance-attribute
Noise2Noise algorithm, a self-supervised denoising scheme based on comparing noisy images of the same sample.
N2V = 'n2v'
class-attribute
instance-attribute
Noise2Void algorithm, a self-supervised approach based on blind denoising.
PN2V = 'pn2v'
class-attribute
instance-attribute
Probabilistic Noise2Void. A extension of Noise2Void is not restricted to Gaussian noise models or Gaussian intensity predictions.
SupportedArchitecture
Bases: StrEnum
Supported architectures.
LVAE = 'LVAE'
class-attribute
instance-attribute
Ladder Variational Autoencoder used for muSplit and denoiSplit.
UNET = 'UNet'
class-attribute
instance-attribute
UNet architecture used with N2V, CARE and Noise2Noise.
SupportedData
Bases: StrEnum
Supported data types.
Attributes:
-
ARRAY(str) –Array data.
-
TIFF(str) –TIFF image data.
-
CZI(str) –CZI image data.
-
ZARR(str) –Zarr data.
-
CUSTOM(str) –Custom data.
get_extension(data_type)
classmethod
Get file extension of corresponding data type.
Parameters:
-
data_type(str or SupportedData) –Data type.
Returns:
-
str–Corresponding extension.
get_extension_pattern(data_type)
classmethod
Get Path.rglob and fnmatch compatible extension.
Parameters:
-
data_type(SupportedData) –Data type.
Returns:
-
str–Corresponding extension pattern.
SupportedLogger
SupportedLoss
SupportedNormalization
Bases: StrEnum
Normalization strategies supported by Careamics.
MEAN_STD = 'mean_std'
class-attribute
instance-attribute
Mean and std normalization strategy.
MINMAX = 'min_max'
class-attribute
instance-attribute
Min-max normalization strategy.
NONE = 'none'
class-attribute
instance-attribute
No normalization strategy.
QUANTILE = 'quantile'
class-attribute
instance-attribute
Quantile normalization strategy.
SupportedOptimizer
SupportedPixelManipulation
Bases: StrEnum
Supported Noise2Void pixel manipulations.
- Uniform: Replace masked pixel value by a (uniformly) randomly selected neighbor pixel value.
- Median: Replace masked pixel value by the mean of the neighborhood.