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PyTorch implementation of conditional random field for multiclass semantic segmenation.

Project description

crfseg: CRF layer for segmentation in PyTorch

Conditional random field (CRF) is a classical graphical model which allows to make structured predictions in such tasks as image semantic segmentation or sequence labeling.

You can learn about it in papers:


pip install crfseg


Can be easily used as differentiable (and moreover learnable) postprocessing layer of your NN for segmentation.

import torch
import torch.nn as nn
from crfseg import CRF

model = nn.Sequential(
    nn.Identity(),  # your NN

batch_size, n_channels, spatial = 10, 1, (100, 100)
x = torch.zeros(batch_size, n_channels, *spatial)
log_proba = model(x)

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