pytorch/vision

Implement AutoAugment for Detection

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#6,224 opened on Jun 30, 2022

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 (19 comments) (0 reactions) (1 assignee)Python (15,050 stars) (6,858 forks)batch import
help wantedmodule: transforms

Description

🚀 The feature

Implement Learning Data Augmentation Strategies for Object Detection Refers to: #3817

Motivation, pitch

Good to have augmentation in Torchvision

Alternatives

No response

Additional context

No response

cc @vfdev-5 @datumbox

Contributor guide

Tech stack
python
Domain
machine learning
Issue type
feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
4
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
3-5 days
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
blocked
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
clear
Prerequisites
PythonPyTorchObject detection conceptsAugmentation methods
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
15
Research direction
Implement AutoAugment for detection as described in the referenced paper. Begin by reviewing the existing AutoAugment implementation for classification (likely in torchvision/transforms/autoaugment.py) and the discussion in issue #3817. Adapt the augmentation policies to work with object detection transforms, such as those in torchvision/transforms/functional.py. Check the assignee's progress and any linked branches for coordination.