No project description provided
Project description
Final2x-core
Final2x-core is a cross-platform image super-resolution CLI tool for Final2x. If you have any questions, please raise an issue in this repository.
Install
Download in Release or use pip (python >= 3.6, >=3.9 for MacOS arm64)
pip install Final2x-core
Use
usage: Final2x-core [-h] [-b BASE64] [-j JSON] [-y YAML] [-o]
when para is not specified, the config.yaml file in the directory will be read automatically
optional arguments:
-h, --help show this help message and exit
-b BASE64, --BASE64 BASE64
base64 string for config json
-j JSON, --JSON JSON JSON string for config
-y YAML, --YAML YAML yaml config file path
-l, --LOG save log
-o, --OP check install
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.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
File details
Details for the file Final2x-core-1.0.2.tar.gz
.
File metadata
- Download URL: Final2x-core-1.0.2.tar.gz
- Upload date:
- Size: 12.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.11.4
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | f577c5ad103d67045fda98eda42541c074959568a39b33f6b73db4acf6541148 |
|
MD5 | b1350f587d4b06f6fa498633fd6b2a39 |
|
BLAKE2b-256 | b013bf57debc2137be75a5c27fd342d89e19ecf47b3960f185de1192a000e4b9 |