pyra-pytorch 0.0.3

Pyramid Focus Augmentation: Medical Image Segmentation with Step Wise Focus - Pytorch support dataset

pyra-pytorch

This is a package suporting Pytorch datasets. This implementation is based on the augmentation method discussed in the paper "Pyramid-Focus-Augmentation: Medical Image Segmentation with Step-Wise Focus" (PDF) and the original github repository: PYRA.

@article{thambawita2020pyramid,
  title={Pyramid-Focus-Augmentation: Medical Image Segmentation with Step-Wise Focus},
  author={Thambawita, Vajira and Hicks, Steven and Halvorsen, P{\aa}l and Riegler, Michael A},
  journal={arXiv preprint arXiv:2012.07430},
  year={2020}
}

How to use:

Install the package,

pip install pyra-pytorch

Create a dataset with gird sizes which are going to be used as augmentation in the training process. If you want to get only the original mask, then, you have to pass image size as the gird size.

from pyra_pytorch import PYRADataset

dataset = PYRADataset("./image_path", # image folder
                      "./masks_path", # mask folder - files´s names of this folder should have image names as prefix to find correct image and mask pairs.
                      img_size = 256,  # height and width of image to resize
                      grid_sizes=[2,4,8,16,32,64,128,256] , # Gird sizes to use as grid augmentation. Note that, the image size after resizing ()
                      transforms = None
                      )
'''
./image_path" --> image folder

./masks_path" --> mask folder - files´s names of this folder should have image names as prefix to find correct image and mask pairs.

img_size = 256 --> height and width of image to resize

grid_sizes=[2,4,8,16,32,64,128,256]  --> Gird sizes to use as grid augmentation. Note that, the image size after resizing (in this case, it is 256) shoud be divisible by these grid sizes.

transforms = None --> Other type of transformations using in Pytorch. 

'''

Sample ipython notebook

notebook

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