8000 GitHub - j-sripad/Tiramisu-pytorch: The Implementation of "One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation"
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This repository contains the implementation of "The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation" in pytorch.

Paper

Note

  • The decoder part of this implementation is bit different from that of the paper.

Architecture

Alt text

Usage


from tiramisu import Tiramisu_Segmentation 
net = Tiramisu_Segmentation(layer_tiramisu=103,nclasses=1,input_features=1,growth_rate=16)
""" Arguments : layer_tiramisu - 57, 47 or 103 input_features - input image channels nclasses - number of classes growth_rate - growth rate (filters to begin with for convolution - generally 16) """

Dataset

Examples

  • Example 1

  • Example 2

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The Implementation of "One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation"

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