KAIR

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KAIR is an open-source image restoration toolbox built with PyTorch. It provides training and testing codes for various image restoration models, including DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, and SwinIR.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is KAIR?

KAIR is a comprehensive image restoration toolbox implemented in PyTorch, offering a wide array of training and testing codes for popular image restoration models. It supports models like DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, and SwinIR, making it a versatile resource for researchers and developers. The toolbox facilitates tasks such as image denoising, super-resolution, and deblurring. It includes functionalities for downloading pre-trained models, distributed training with multiple GPUs, and performance analysis metrics like FLOPs and parameter counts. KAIR is actively maintained with regular news updates on new model releases and features, providing a robust platform for advancing image restoration techniques.

Best used for

Ideal for researchers and developers who need to implement and evaluate state-of-the-art image restoration algorithms, train custom models, and compare performance metrics. Especially valuable for those working on image denoising, super-resolution, and deblurring tasks within a PyTorch environment.

Common actions

restore images

denoise images

super-resolve images

deblur images

train image models

test image models

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Capabilities

Key features

Image denoising
Image super-resolution
Image deblurring
Distributed training
Pre-trained models
Performance metrics
Face enhancement

Target Audience

researchersdevelopersmachine learning engineersstudents

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What image restoration tasks does KAIR support?

KAIR supports a variety of image restoration tasks including image denoising, super-resolution, and deblurring. It provides codes for models like DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, and SwinIR, covering a broad spectrum of restoration challenges.

Can KAIR be used for training custom models?

Yes, KAIR provides training codes for various models, allowing users to train their own image restoration models. It also supports distributed training with multiple GPUs, making it suitable for large-scale model development and experimentation.

Does KAIR offer pre-trained models?

Yes, KAIR includes a utility to download pre-trained models for different restoration tasks and architectures. This allows users to quickly test and evaluate models without needing to train them from scratch.

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