ai-dawang/PlugNPlay-Modules

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

5105 stars · 368 forks observed · 2026-08-28

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

A curated collection of plug-and-play deep learning modules (convolutions, attention mechanisms, downsampling, and feature fusion blocks) implemented in Python for computer vision tasks. It aims to let researchers quickly insert these modules into their own models for image classification, detection, segmentation, super-resolution, and other 2D vision tasks.

Use cases

• add attention modules to my CNN to improve accuracy
• find plug-and-play feature fusion blocks for object detection
• improve YOLO model performance with new modules
• collect attention mechanism implementations for image segmentation
• boost super-resolution model with drop-in modules
• learn how to integrate modules from papers into my model

When to choose

• you want ready-made vision modules to drop into classification, detection, or segmentation models
• you are a researcher looking for inspiration and implementations of recent module papers
• you want Chinese-language guidance on 'module stitching' techniques for paper writing

When to avoid

• you need a maintained, tested library with stable APIs and a license
• you need production-grade, optimized implementations rather than research snippets
• you work mainly on 1D or 3D tasks, which are not yet covered

Facets

library · maturity active

deep-learning machine-learning image-processing computer-vision deep-learning computer-vision image-processing machine-learning tutorials python cross-platform plug-and-play-modules attention-mechanism convolution feature-fusion downsampling yolo model-improvement paper-reproduction chinese-community

Member repositories

For agents

markdown · JSON · MCP: product_card(name="ai-dawang/PlugNPlay-Modules")