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Project description
Final2x-core
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
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.
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