Related to <a class="issue-link js-issue-link" data-error-text="Failed to load title"

Add RandomCrop transform about torchio HOT 1 CLOSED

fepegar commented on May 28, 2024

Add RandomCrop transform

from torchio.

Comments (1)

fepegar commented on May 28, 2024

This can actually be achieved using an ImageSampler:

torchio/torchio/data/sampler/sampler.py

Lines 12 to 15 in 6080a6f

    
           class ImageSampler(IterableDataset): 
        
               def __init__(self, sample, patch_size): 
        
                   self.sample = sample 
        
                   self.patch_size = np.array(to_tuple(patch_size, n=3), dtype=np.uint16)

from torchio.

Related Issues (20)

Add pythonic slicing support to torchio.Image
Proposal of a new way for DDP, Distributed Sampler, and Queue to work HOT 3
Tests for queue are failing on Windows HOT 1
Pad modifies labels unexpectedly HOT 4
Torchio Transformation Does not Working properly HOT 2
`masked_select` on Z-Normalization slower than indexing HOT 2
GridSampler without subject for validation HOT 3
Resize sometimes adds a dimension to LabelMap images HOT 5
Documentation is not built
Patch Based Training With Queue Is Not Working Properly HOT 1
Error when using a lambda function as masking_method in ZNormalization HOT 2
Combined Affine/Elastic augmentations HOT 1
The rotation given by Random Affine not accurate HOT 5
(Optional) state_dict for each transform (reproducibility) HOT 2
Wrong link to docs in Getting Started tutorial HOT 2
Suggestions the modifying default value of prefetch_factor and the argument to set it for minimize the blocking-bottleneck between fetch subject and generate patch in Queue HOT 1
Different transforms applied to CT and label HOT 11
The Affine matrix does not change after applying the augmentations HOT 3
Custom loader not used when loading data lazily HOT 2
Seed is not working HOT 2

Add RandomCrop transform about torchio HOT 1 CLOSED

Comments (1)

Related Issues (20)

Recommend Projects

React

Vue.js

Typescript

TensorFlow

Django

Laravel

D3

Recommend Topics

javascript

web

server

Machine learning

Visualization

Game

Recommend Org

Facebook

Microsoft

Google

Alibaba

D3

Tencent

	class ImageSampler(IterableDataset):
	def __init__(self, sample, patch_size):
	self.sample = sample
	self.patch_size = np.array(to_tuple(patch_size, n=3), dtype=np.uint16)