tracel-ai/burn

Image quality metrics

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#4,312 opened on Jan 13, 2026

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featuregood first issue

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Description

Feature description

Add metrics for assessing image quality, including deep learning metrics.

Feature motivation

When training visual AI models the loss function may include various image metrics. Users would have to re-implement these image metrics unless readily available.

Examples

Take for example the impressive recent ml-sharp which uses at least PSNR, SSIM, LPIPS, DISTS.

Contributor guide

Research direction
Implement the A FINE image quality metric by porting the IQA PyTorch implementation to Burn's framework, following the pattern of previously closed metrics like LPIPS and DISTS.
Tech stack
rust
Domain
machine learningaicomputer vision
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.
1-2 days
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
Active
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Clear
Prerequisites
RustBurnDeep Learning
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
60