XPixelGroup/BasicSR

Health v2 · maintenance only

Adoption not part of the score

8367 stars · 1407 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

BasicSR is an open-source PyTorch toolbox for image and video restoration tasks such as super-resolution, denoising, deblurring, and JPEG artifact removal. It includes implementations of many state-of-the-art models like EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR, BasicVSR, SwinIR, and ECBSR, with training and testing pipelines.

Use cases

• upscale low-resolution images with deep learning
• remove noise from photos using neural networks
• deblur blurry images or video frames
• restore compressed JPEG images
• train a custom super-resolution model in PyTorch
• enhance video quality frame by frame
• benchmark image restoration models

When to choose

• you need a PyTorch framework for training or evaluating image/video restoration models
• you want ready implementations of classic and SOTA super-resolution architectures
• you need both image and video restoration in one toolbox

When to avoid

• you need a simple one-click GUI upscaler rather than a research toolbox
• your task is unrelated to restoration (e.g., generation-only or classification)
• you need non-PyTorch frameworks like TensorFlow or ONNX-only inference

Facets

library · maturity stable

machine-learning deep-learning image-processing video-processing computer-vision image-processing deep-learning machine-learning python cross-platform super-resolution image-restoration pytorch denoising deblurring esrgan swinir video-restoration model-zoo training-framework gpu

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markdown · JSON · MCP: product_card(name="XPixelGroup/BasicSR")