Pyramid Focus Augmentation: Medical Image Segmentation with Step Wise Focus
Project description
pyra-pytorch
This is a package supporting 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
Creating a PYRA augmented dataset:
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
Contact us:
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
pyra-pytorch-0.0.5.tar.gz
(4.1 kB
view details)
Built Distribution
File details
Details for the file pyra-pytorch-0.0.5.tar.gz
.
File metadata
- Download URL: pyra-pytorch-0.0.5.tar.gz
- Upload date:
- Size: 4.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.23.0 setuptools/46.4.0.post20200518 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.8.3
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3a7fdd7bb97ae347e18b96a385378af5282fa874661623e4e462f2ea67c70fe6 |
|
MD5 | 0710078621933e942433527f84c43d73 |
|
BLAKE2b-256 | 6f3e9ef0156838a116963409e73e7def263af150365583fa3382099ac3bd68ca |
File details
Details for the file pyra_pytorch-0.0.5-py3-none-any.whl
.
File metadata
- Download URL: pyra_pytorch-0.0.5-py3-none-any.whl
- Upload date:
- Size: 5.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.23.0 setuptools/46.4.0.post20200518 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.8.3
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 109dffa9162d05f3ce97ced1c87cefc3b7b67c007eda1b747e59f47fc6efe4e6 |
|
MD5 | 457350732e4625f826f94671aafe6259 |
|
BLAKE2b-256 | 0d73ab1cee58bb2d329402885caa693ca8c76f92a7f761a174c6a1a529b26654 |