Skip to main content

No project description provided

Project description

Final2x-core

MacOS x64 MacOS arm64 Windows x64 Windows arm64 Linux x64 codecov CI-test CI-build Release PyPI version GitHub

Final2x-core is a cross-platform image super-resolution CLI tool for Final2x.

Use

usage: Final2x-core [-h] [-j JSON]

when -j is not specified, the config.yaml file in the directory will be read automatically

optional arguments:
  -h, --help            show this help message and exit
  -j JSON, --JSON JSON  JSON str for config

Config

Pass the config json string to the program through the -j parameter.

PLEASE NOTE: the config is JSON, remove the // comments before use.

{
  "gpuid": 0, // GPU id, >= -1 (-1 for CPU, may not work for some models.)
  "inputpath": [
    // Input image paths, should be a list.
    "path/to/img1.jpg", 
    "path/to/img2.png"
  ],
  "model": "RealCUGAN-pro", // model name
  "modelscale": 2, // model upscale factor
  "modelnoise": -1, // DENOISE level
  "outputpath": "path/to/output", // output path
  "targetscale": 2.0, 
  // Target upscale factor, upscale multiple times to achieve the target upscale factor.
  // If not invalid, use modelscale.
  "tta": false // Test Time Augmentation, default false
}

SUPPORTED MODEL LIST:

  • RealCUGAN-se:

    • model: "RealCUGAN-se"
    • scale: 2
      • noise: -1, 0, 1, 2, 3
    • scale: 3, 4
      • noise: -1, 0, 3
  • RealCUGAN-pro:

    • model: "RealCUGAN-pro"
    • scale: 2, 3
    • noise: -1, 0, 3
  • RealESRGAN-animevideov3:

    • gpuid : >= 0
    • model: "RealESRGAN-animevideov3"
    • scale: 2, 3, 4
  • RealESRGAN:

    • gpuid : >= 0
    • model: "RealESRGAN"
    • scale: 4
  • RealESRGAN-anime:

    • gpuid : >= 0
    • model: "RealESRGAN-anime"
    • scale: 4
  • Waifu2x-cunet:

    • model: "Waifu2x-cunet"
    • scale: 1
      • noise: 0, 1, 2, 3
    • scale: 2
      • noise: -1, 0, 1, 2, 3
  • Waifu2x-upconv_7_anime_style_art_rgb:

    • model: "Waifu2x-upconv_7_anime_style_art_rgb"
    • scale: 2
    • noise: -1, 0, 1, 2, 3
  • Waifu2x-upconv_7_photo:

    • model: "Waifu2x-upconv_7_photo"
    • scale: 2
    • noise: -1, 0, 1, 2, 3
  • SRMD:

    • gpuid : >= 0
    • model: "SRMD"
    • scale: 2, 3, 4
    • noise: -1, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10

Build

Github Action

The project just only been tested in Ubuntu 18+ and Debian 9+ environments on Linux, so if the project does not work on your system, please try building it.

Reference

The following references were used in the development of this project:

ncnn - ncnn is a high-performance neural network inference framework developed by Tencent AI Lab.

nihui/realcugan-ncnn-vulkan - This project provided the core implementation of the Real-CUGAN algorithm using the ncnn and Vulkan libraries.

xinntao/Real-ESRGAN-ncnn-vulkan - This project provided the core implementation of the Real-ESRGAN algorithm using the ncnn and Vulkan libraries.

nihui/waifu2x-ncnn-vulkan - This project provided the core implementation of the Waifu2x algorithm using the ncnn and Vulkan libraries.

nihui/srmd-ncnn-vulkan - This project provided the core implementation of the SRMD algorithm using the ncnn and Vulkan libraries.

realcugan-ncnn-py - This project provided the Python Binding for realcugan-ncnn-vulkan with PyBind11

realesrgan-ncnn-py - This project provided the Python Binding for realesrgan-ncnn-vulkan with PyBind11

waifu2x-ncnn-py - This project provided the Python Binding for waifu2x-ncnn-vulkan with PyBind11

srmd-ncnn-py - This project provided the Python Binding for srmd-ncnn-vulkan with PyBind11

License

This project is licensed under the BSD 3-Clause - see the LICENSE file for details.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

Final2x-core-0.0.2.tar.gz (11.4 kB view details)

Uploaded Source

File details

Details for the file Final2x-core-0.0.2.tar.gz.

File metadata

  • Download URL: Final2x-core-0.0.2.tar.gz
  • Upload date:
  • Size: 11.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.4

File hashes

Hashes for Final2x-core-0.0.2.tar.gz
Algorithm Hash digest
SHA256 4e81252a46a1465eea880ef542e4e2d9e27fa7e6a9fa263c1374d91053408c9e
MD5 f33354ce3187e1661cee0969aa3e9ef3
BLAKE2b-256 6e4602082f3303b50de7fd3cf5bef31d7c6a0a2b9763e2c4e8c0f466f3ed16d3

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page