DLTK/DLTK

Apply the same transformation to image and mask in elastic_transform ?

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#31 opened on Jul 25, 2018

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 (2 comments) (0 reactions) (0 assignees)Python (1,386 stars) (410 forks)batch import
enhancementgood first issuehelp wanted

Description

In augmentation, elastic_transform, it only applies a random transform on one input image array. I would think to be used for training, the image and mask pair should be transform in the same way. However, this single-input-image, single-output-image method makes it very inconvenient. Could we deform a list of images (np.arrays) using the same transformation in this method ? Thanks!

Contributor guide

Tech stack
pythonnumpy
Domain
machine learningdata
Issue type
feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
1-3 hours
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
stale
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
clear
Prerequisites
familiarity with numpybasic image augmentation concepts
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
70
Research direction
The issue requests modifying the elastic transform function to apply the same transformation to a list of images (e.g., image and mask). Look at the current implementation of elastic transform in the repository (likely in a file like augment.py). Identify the random displacement field generation step and refactor the function to accept a list of arrays, applying the same field to all. Review any existing comments for guidance.