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Xintao
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README_CN.md
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README_CN.md
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1. Real-ESRGAN的[Colab Demo](https://colab.research.google.com/drive/1k2Zod6kSHEvraybHl50Lys0LerhyTMCo?usp=sharing) <a href="https://colab.research.google.com/drive/1k2Zod6kSHEvraybHl50Lys0LerhyTMCo?usp=sharing"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="google colab logo"></a>.
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2. Real-ESRGAN的 **动漫视频** 的[Colab Demo](https://colab.research.google.com/drive/1yNl9ORUxxlL4N0keJa2SEPB61imPQd1B?usp=sharing) <a href="https://colab.research.google.com/drive/1yNl9ORUxxlL4N0keJa2SEPB61imPQd1B?usp=sharing"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="google colab logo"></a>.
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3. **支持Intel/AMD/Nvidia显卡**的绿色版exe文件： [Windows版](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.3.0/realesrgan-ncnn-vulkan-20211212-windows.zip) / [Linux版](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.3.0/realesrgan-ncnn-vulkan-20211212-ubuntu.zip) / [macOS版](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.3.0/realesrgan-ncnn-vulkan-20211212-macos.zip)，详情请移步[这里](#便携版（绿色版）可执行文件)。NCNN的实现在 [Real-ESRGAN-ncnn-vulkan](https://github.com/xinntao/Real-ESRGAN-ncnn-vulkan)。
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3. **支持Intel/AMD/Nvidia显卡**的绿色版exe文件： [Windows版](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesrgan-ncnn-vulkan-20220424-windows.zip) / [Linux版](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesrgan-ncnn-vulkan-20220424-ubuntu.zip) / [macOS版](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesrgan-ncnn-vulkan-20220424-macos.zip)，详情请移步[这里](#便携版（绿色版）可执行文件)。NCNN的实现在 [Real-ESRGAN-ncnn-vulkan](https://github.com/xinntao/Real-ESRGAN-ncnn-vulkan)。
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Real-ESRGAN 的目标是开发出**实用的图像/视频修复算法**。<br>
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我们在 ESRGAN 的基础上使用纯合成的数据来进行训练，以使其能被应用于实际的图片修复的场景（顾名思义：Real-ESRGAN）。
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### 便携版（绿色版）可执行文件
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你可以下载**支持Intel/AMD/Nvidia显卡**的绿色版exe文件： [Windows版](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.3.0/realesrgan-ncnn-vulkan-20211212-windows.zip) / [Linux版](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.3.0/realesrgan-ncnn-vulkan-20211212-ubuntu.zip) / [macOS版](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.3.0/realesrgan-ncnn-vulkan-20211212-macos.zip)。
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你可以下载**支持Intel/AMD/Nvidia显卡**的绿色版exe文件： [Windows版](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesrgan-ncnn-vulkan-20220424-windows.zip) / [Linux版](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesrgan-ncnn-vulkan-20220424-ubuntu.zip) / [macOS版](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesrgan-ncnn-vulkan-20220424-macos.zip)。
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绿色版指的是这些exe你可以直接运行（放U盘里拷走都没问题），因为里面已经有所需的文件和模型了。它不需要 CUDA 或者 PyTorch运行环境。<br>
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1. realesrgan-x4plus（默认）
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2. reaesrnet-x4plus
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3. realesrgan-x4plus-anime（针对动漫插画图像优化，有更小的体积）
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4. RealESRGANv2-animevideo-xsx2 (针对动漫视频, X2)
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5. RealESRGANv2-animevideo-xsx4 (针对动漫视频, X4)
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4. realesr-animevideov3 (针对动漫视频)
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你可以通过`-n`参数来使用其他模型，例如`./realesrgan-ncnn-vulkan.exe -i 二次元图片.jpg -o 二刺螈图片.png -n realesrgan-x4plus-anime`
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Usage: realesrgan-ncnn-vulkan.exe -i infile -o outfile [options]...
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-h show this help
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-v verbose output
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-i input-path input image path (jpg/png/webp) or directory
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-o output-path output image path (jpg/png/webp) or directory
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-s scale upscale ratio (4, default=4)
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-s scale upscale ratio (can be 2, 3, 4. default=4)
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-t tile-size tile size (>=32/0=auto, default=0) can be 0,0,0 for multi-gpu
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-m model-path folder path to pre-trained models(default=models)
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-n model-name model name (default=realesrgan-x4plus, can be realesrgan-x4plus | realesrgan-x4plus-anime | realesrnet-x4plus)
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-g gpu-id gpu device to use (default=0) can be 0,1,2 for multi-gpu
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-m model-path folder path to the pre-trained models. default=models
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-n model-name model name (default=realesr-animevideov3, can be realesr-animevideov3 | realesrgan-x4plus | realesrgan-x4plus-anime | realesrnet-x4plus)
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-g gpu-id gpu device to use (default=auto) can be 0,1,2 for multi-gpu
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-j load:proc:save thread count for load/proc/save (default=1:2:2) can be 1:2,2,2:2 for multi-gpu
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-x enable tta mode
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-x enable tta mode"
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-f format output image format (jpg/png/webp, default=ext/png)
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-v verbose output
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```
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由于这些exe文件会把图像分成几个板块，然后来分别进行处理，再合成导出，输出的图像可能会有一点割裂感（而且可能跟PyTorch的输出不太一样）
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这些exe文件均基于[Tencent/ncnn](https://github.com/Tencent/ncnn)以及[nihui](https://github.com/nihui)的[realsr-ncnn-vulkan](https://github.com/nihui/realsr-ncnn-vulkan)，感谢！
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---
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## :wrench: 依赖以及安装
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@@ -233,7 +230,7 @@ python inference_realesrgan.py -n RealESRGAN_x4plus_anime_6B -i inputs
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```console
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Usage: python inference_realesrgan.py -n RealESRGAN_x4plus -i infile -o outfile [options]...
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A common command: python inference_realesrgan.py -n RealESRGAN_x4plus -i infile --outscale 3.5 --half --face_enhance
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A common command: python inference_realesrgan.py -n RealESRGAN_x4plus -i infile --outscale 3.5 --face_enhance
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-h show this help
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-i --input Input image or folder. Default: inputs
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@@ -243,7 +240,7 @@ A common command: python inference_realesrgan.py -n RealESRGAN_x4plus -i infile
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--suffix Suffix of the restored image. Default: out
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-t, --tile Tile size, 0 for no tile during testing. Default: 0
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--face_enhance Whether to use GFPGAN to enhance face. Default: False
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--half Whether to use half precision during inference. Default: False
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--fp32 Whether to use half precision during inference. Default: False
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--ext Image extension. Options: auto | jpg | png, auto means using the same extension as inputs. Default: auto
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```
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