Metadata-Version: 2.1
Name: pyra-pytorch
Version: 1.3.0
Summary: Pyramid Focus Augmentation: Medical Image Segmentation with Step Wise Focus
Home-page: https://github.com/vlbthambawita/pyra-pytorch
Author: Vajira Thambawita
Author-email: vlbthambawita@gmail.com
License: UNKNOWN
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](https://arxiv.org/pdf/2012.07430v1.pdf)) and the original github repository: [PYRA](https://vlbthambawita.github.io/PYRA/).
        
        
        
        
        
        ```latex
        @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,
        ```bash
        pip install pyra-pytorch
        ```
        
        ### Creating a PYRA augmented dataset:
        
        ```python
        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. 
        
        '''
        ```
        
        
        ### Creating a PYRA augmented dataset using path list files:
        
        ```python
        from pyra_pytorch import PYRADatasetFromPaths
        
        dataset = PYRADatasetFromPaths("path_to_the_file_with_image_paths", # file containing all image paths
                              "path_to_file_with_mask_paths", # file containing all mask paths - 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
                              )
        '''
        path_to_the_file_with_image_paths" --> A file with all paths of images. File should have one path (absolute path) per line. 
        
        path_to_file_with_mask_paths" --> A file with all paths of masks. The file should have one path (absolute path) per line. Please use the image names as prefix for mask's names to find correct mask for correct image.
        
        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. 
        
        '''
        ```
        
        
        ## Creating a PYRA augmented dataset using path list files:
        
        ```python
        from pyra_pytorch import PYRADatasetFromDF
        
        dataset = PYRADatasetFromDF(df, # A dataframe with two colomns: image_path and mask_path. Each column has absolute path of image and maks.
                              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
                              )
        '''
        df --> A dataframe with two colomns: image_path and mask_path. Each column has absolute path of image and maks.
        
        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](https://github.com/vlbthambawita/pyra-pytorch/blob/main/tutorial/load_data_with_PYRA.ipynb)
        
        
        # Contact us:
        
        vajira@simula.no | michael@simula.no
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
