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Super-resolution processing for anime images based on WASM; 基于WASM的动漫图片超分辨率处理
| Date | Stars |
|---|---|
| 2026-07-24 | 261 |
| 2026-07-25 | 261 |
| 2026-07-28 | 261 |
| 2026-07-30 | 261 |
| 2026-08-06 | 261 |
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# RealCUGAN-ncnn-webassembly [中文](https://github.com/hanFengSan/realcugan-ncnn-webassembly/blob/main/README_CN.md) This project uses Web Assembly technology to run the Real-CUGAN model based on ncnn. [Real-CUGAN](https://github.com/bilibili/ailab/tree/main/Real-CUGAN) is an AI super resolution model for anime images, trained in a million scale anime dataset, using the same architecture as Waifu2x-CUNet. It supports 2x\3x\4x super resolving. For different enhancement strength, now 2x Real-CUGAN supports 5 model weights, 3x/4x Real-CUGAN supports 3 model weights. The code implementation deeply refers to [realcugan-ncnn-vulkan](https://github.com/nihui/realcugan-ncnn-vulkan) and [ncnn-webassembly-nanodet](https://github.com/nihui/ncnn-webassembly-nanodet). # Usage Website： https://real-cugan.animesales.xyz/ iOS: is not currently supported. Android: please open in a browser app. PC/Mac/Linux: recommend using the latest version of Chrome or Firefox. # How to build 1. Install [emscripten](https://github.com/emscripten-core/emscripten): ```shell git clone https://github.com/emscripten-core/emsdk.git cd emsdk ./emsdk install 3.1.13 ./emsdk activate 3.1.13 source emsdk/emsdk_env.sh # or add it to .zshrc etc. ``` 2. build: ```shell git clone https://github.com/hanfengsan/realcugan-ncnn-webassembly.git cd realcugan-ncnn-webassembly git submodule update --init sh build.sh go run local_server.go ``` open in brower: http://localhost:8000
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:c8c650a116561733, topic:super-resolution, desc:super resolution, readme:super resolution