API Reference¶
This page lists the available functions and classes of pysegcnn
.
Dataset¶
Custom dataset classes compliant to the PyTorch standard.
Supported datasets¶
The following open-source spaceborne multispectral image datasets are supported out-of-the-box:
Class for the Sparcs dataset. |
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Class for the Cloud-95 dataset by Mohajerani & Saeedi (2020). |
Models¶
Layers¶
Convolutional neural network layers.
Basic convolutional block. |
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A convolution preserving the shape of its input. |
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Block of convolution, batchnorm, relu and 2x2 max pool. |
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Block of convolution, batchnorm, relu and 2x2 max unpool. |
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Block of convolution, batchnorm, relu and nearest neighbor upsampling. |
Encoder-Decoder architechture¶
Generic Encoder
and Decoder
classes to build an encoder-decoder
architecture.
Block of a convolutional encoder. |
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Block of a convolutional decoder. |
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Generic convolutional encoder. |
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Generic convolutional decoder. |