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AI图片修复

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本方案整合了来自开源社区的高质量图像修复、去噪、上色等算法,并使用Stable Diffusion WebUI进行交互式图像修复。您可以根据需要调整参数,组合不同的处理方法,以达到最佳的修复效果。本文为您介绍如何在阿里云DSW中,进行交互式图像修复。

准备环境和资源

  • 创建工作空间,详情请参见创建工作空间

  • 创建DSW实例,其中关键参数配置如下。具体操作,请参见创建及管理DSW实例

    • 实例规格选择:ecs.gn7i-c8g1.2xlarge

    • 镜像选择:在官方镜像中选择stable-diffusion-webui-env:pytorch1.13-gpu-py310-cu117-ubuntu22.04

步骤一:在DSW中打开教程文件

  1. 进入PAI-DSW开发环境。

    1. 登录PAI控制台

    2. 在页面左上方,选择DSW实例所在的地域。

    3. 在左侧导航栏单击工作空间列表,在工作空间列表页面中单击默认工作空间名称,进入对应工作空间内。

    4. 在左侧导航栏,选择模型开发与训练>交互式建模(DSW)

    5. 单击需要打开的实例操作列下的打开,进入PAI-DSW实例开发环境。

  2. Notebook页签的Launcher页面,单击快速开始区域Tool下的DSW Gallery,打开DSW Gallery页面。image.png

  3. 在DSW Gallery页面中,搜索并找到用AI重燃亚运经典教程,单击教程卡片中的在DSW中打开

    单击后即会自动将本教程所需的资源和教程文件下载至DSW实例中,并在下载完成后自动打开教程文件。41d0fd0d16860a211e170c2688213ba8.png

步骤二:运行教程文件

在打开的教程文件image_restoration.ipynb文件中,您可以直接看到教程文本,您可以在教程文件中直接运行对应的步骤的命令,当成功运行结束一个步骤命令后,再顺次运行下个步骤的命令。b8217b563ccc9fd3b51421cd0136750c.png本教程包含的操作步骤以及每个步骤的执行结果如下。

  1. 导入待修复的照片。依次运行数据准备章节的命令,下载提供的亚运老照片并解压至input文件夹中。

    1. 安装工具。

      单击此处查看运行结果

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    2. 使用内网下载链接可以提升下载速度。

    3. 下载图片数据并解压至input目录。

      单击此处查看运行结果

      http://pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com/aigc-data/restoration/img/input.zip
      cn-hangzhou
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      Connecting to pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com (pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com)|100.118.28.49|:80... connected.
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  2. 针对给定的图片,您可以选择以下两种方式,或将它们进行组合,以进行老照片修复任务。

    基于源码修复图片

    在Gallery中,PAI集成了大量相关领域的开源算法和预训练模型,供您方便地进行一键式使用。您也可以在Notebook中进一步优化或开发您的老照片修复算法。根据模型处理方式的不同,PAI将老照片修复任务大致分为以下几个操作步骤:

    1. 图像去噪,即去除图像中的噪声、模糊等。支持以下两种算法,您可以任意选择一种来处理图像。

      Restormer

      1. 下载代码及预训练文件。下载解压完成后,您可以在./Restormer文件夹中查看该算法的源代码。

        单击此处查看运行结果

        http://pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com/aigc-data/restoration/repo/restormer.zip
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        Saving to: ‘restormer.zip’
        
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      2. 安装额外的环境包。

        单击此处查看运行结果

        Looking in indexes: https://mirrors.cloud.aliyuncs.com/pypi/simple
        Collecting natsort
          Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/ef/82/7a9d0550484a62c6da82858ee9419f3dd1ccc9aa1c26a1e43da3ecd20b0d/natsort-8.4.0-py3-none-any.whl (38 kB)
        Installing collected packages: natsort
        Successfully installed natsort-8.4.0
        WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv
        
        [notice] A new release of pip is available: 23.0.1 -> 23.2.1
        [notice] To update, run: python3 -m pip install --upgrade pip
      3. 根据需要运行合适的推理任务,包括去运动模糊、去focus模糊、去雨滴等。您可以参考Notebook中的相关参数来进行设置。通过指定输入文件夹或输出文件夹,您可以运行相关算法来进行图像修复任务。命令执行成功后,您可以在./results/{task_name}中查看修复后的图像结果。

        单击此处查看运行结果

        ==> Running Motion_Deblurring with weights /mnt/workspace/Restormer/Motion_Deblurring/pretrained_models/motion_deblurring.pth
         
        100%|███████████████████████████████████████████| 10/10 [00:28<00:00,  2.81s/it]
        
        Restored images are saved at results/Motion_Deblurring
        
         ==> Running Single_Image_Defocus_Deblurring with weights /mnt/workspace/Restormer/Defocus_Deblurring/pretrained_models/single_image_defocus_deblurring.pth
         
        100%|███████████████████████████████████████████| 10/10 [00:26<00:00,  2.64s/it]
        
        Restored images are saved at results/Single_Image_Defocus_Deblurring
        
         ==> Running Deraining with weights /mnt/workspace/Restormer/Deraining/pretrained_models/deraining.pth
         
        100%|███████████████████████████████████████████| 10/10 [00:26<00:00,  2.65s/it]
        
        Restored images are saved at results/Deraining
        
         ==> Running Real_Denoising with weights /mnt/workspace/Restormer/Denoising/pretrained_models/real_denoising.pth
         
        100%|███████████████████████████████████████████| 10/10 [00:24<00:00,  2.48s/it]
        
        Restored images are saved at results/Real_Denoising
        
         ==> Running Gaussian_Gray_Denoising with weights /mnt/workspace/Restormer/Denoising/pretrained_models/gaussian_gray_denoising_blind.pth
         
        100%|███████████████████████████████████████████| 10/10 [00:24<00:00,  2.45s/it]
        
        Restored images are saved at results/Gaussian_Gray_Denoising
        
         ==> Running Gaussian_Color_Denoising with weights /mnt/workspace/Restormer/Denoising/pretrained_models/gaussian_color_denoising_blind.pth
         
        100%|███████████████████████████████████████████| 10/10 [00:24<00:00,  2.50s/it]
        
        Restored images are saved at results/Gaussian_Color_Denoising

      NAFNet

      1. 下载代码及预训练文件(基于ModelScope)。下载解压完成后,您可以在对应文件夹中查看该算法的源代码。

        单击此处查看运行结果

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        WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv
        
        [notice] A new release of pip is available: 23.0.1 -> 23.2.1
        [notice] To update, run: python3 -m pip install --upgrade pip
        http://pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com/aigc-data/restoration/repo/nafnet.zip
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          inflating: NAFNet/pretrain_model/cv_nafnet_image-denoise_sidd/data/SIDD_example/0003_001_S6_00100_00060_3200_H/0003_GT_SRGB_011.PNG  
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           creating: NAFNet/pretrain_model/cv_nafnet_image-denoise_sidd/data/SIDD_example/0001_001_S6_00100_00060_3200_L/
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      2. 根据需要运行合适的推理任务,包括去模糊、去噪和去运动模糊。命令执行成功后,您可以在./results/{task_name}中查看修复后的图像结果。

        单击此处查看运行结果

        2023-09-04 11:47:14,618 - modelscope - INFO - PyTorch version 1.13.1+cu117 Found.
        2023-09-04 11:47:14,619 - modelscope - INFO - Loading ast index from /root/.cache/modelscope/ast_indexer
        2023-09-04 11:47:14,619 - modelscope - INFO - No valid ast index found from /root/.cache/modelscope/ast_indexer, generating ast index from prebuilt!
        2023-09-04 11:47:14,695 - modelscope - INFO - Loading done! Current index file version is 1.8.4, with md5 80fa9349fc3e7b04fcfad511918062b1 and a total number of 902 components indexed
        /mnt/workspace/NAFNet
        2023-09-04 11:47:15,604 - modelscope - INFO - initiate model from /mnt/workspace/NAFNet/pretrain_model/cv_nafnet_image-deblur_gopro
        2023-09-04 11:47:15,604 - modelscope - INFO - initiate model from location /mnt/workspace/NAFNet/pretrain_model/cv_nafnet_image-deblur_gopro.
        2023-09-04 11:47:15,605 - modelscope - INFO - initialize model from /mnt/workspace/NAFNet/pretrain_model/cv_nafnet_image-deblur_gopro
        2023-09-04 11:47:16,267 - modelscope - INFO - Loading NAFNet model from /mnt/workspace/NAFNet/pretrain_model/cv_nafnet_image-deblur_gopro/pytorch_model.pt, with param key: [params].
        2023-09-04 11:47:16,368 - modelscope - INFO - load model done.
        2023-09-04 11:47:16,400 - modelscope - INFO - load image denoise model done
        Total Image:  10
        2023-09-04 11:47:17,517 - modelscope - WARNING - task image-deblurring input definition is missing
        2023-09-04 11:47:18,893 - modelscope - WARNING - task image-deblurring output keys are missing
        0/10 saved at results/nafnet_deblur/64.jpg
        1/10 saved at results/nafnet_deblur/2.jpg
        2/10 saved at results/nafnet_deblur/34.jpg
        3/10 saved at results/nafnet_deblur/54.jpg
        4/10 saved at results/nafnet_deblur/40.jpg
        5/10 saved at results/nafnet_deblur/10.jpg
        6/10 saved at results/nafnet_deblur/70.jpg
        7/10 saved at results/nafnet_deblur/4.png
        8/10 saved at results/nafnet_deblur/20.jpg
        9/10 saved at results/nafnet_deblur/50.jpg
        2023-09-04 11:47:23,689 - modelscope - INFO - PyTorch version 1.13.1+cu117 Found.
        2023-09-04 11:47:23,690 - modelscope - INFO - Loading ast index from /root/.cache/modelscope/ast_indexer
        2023-09-04 11:47:23,755 - modelscope - INFO - Loading done! Current index file version is 1.8.4, with md5 80fa9349fc3e7b04fcfad511918062b1 and a total number of 902 components indexed
        /mnt/workspace/NAFNet
        2023-09-04 11:47:24,316 - modelscope - INFO - initiate model from /mnt/workspace/NAFNet/pretrain_model/cv_nafnet_image-denoise_sidd
        2023-09-04 11:47:24,316 - modelscope - INFO - initiate model from location /mnt/workspace/NAFNet/pretrain_model/cv_nafnet_image-denoise_sidd.
        2023-09-04 11:47:24,317 - modelscope - INFO - initialize model from /mnt/workspace/NAFNet/pretrain_model/cv_nafnet_image-denoise_sidd
        2023-09-04 11:47:24,627 - modelscope - INFO - Loading NAFNet model from /mnt/workspace/NAFNet/pretrain_model/cv_nafnet_image-denoise_sidd/pytorch_model.pt, with param key: [params].
        2023-09-04 11:47:24,685 - modelscope - INFO - load model done.
        2023-09-04 11:47:24,707 - modelscope - INFO - load image denoise model done
        Total Image:  10
        0/10 saved at results/nafnet_denoise/64.jpg
        1/10 saved at results/nafnet_denoise/2.jpg
        2/10 saved at results/nafnet_denoise/34.jpg
        3/10 saved at results/nafnet_denoise/54.jpg
        4/10 saved at results/nafnet_denoise/40.jpg
        5/10 saved at results/nafnet_denoise/10.jpg
        6/10 saved at results/nafnet_denoise/70.jpg
        7/10 saved at results/nafnet_denoise/4.png
        8/10 saved at results/nafnet_denoise/20.jpg
        9/10 saved at results/nafnet_denoise/50.jpg
        2023-09-04 11:47:30,906 - modelscope - INFO - PyTorch version 1.13.1+cu117 Found.
        2023-09-04 11:47:30,907 - modelscope - INFO - Loading ast index from /root/.cache/modelscope/ast_indexer
        2023-09-04 11:47:30,969 - modelscope - INFO - Loading done! Current index file version is 1.8.4, with md5 80fa9349fc3e7b04fcfad511918062b1 and a total number of 902 components indexed
        /mnt/workspace/NAFNet
        2023-09-04 11:47:31,522 - modelscope - INFO - initiate model from /mnt/workspace/NAFNet/pretrain_model/cv_nafnet_image-deblur_reds
        2023-09-04 11:47:31,522 - modelscope - INFO - initiate model from location /mnt/workspace/NAFNet/pretrain_model/cv_nafnet_image-deblur_reds.
        2023-09-04 11:47:31,523 - modelscope - INFO - initialize model from /mnt/workspace/NAFNet/pretrain_model/cv_nafnet_image-deblur_reds
        2023-09-04 11:47:32,187 - modelscope - INFO - Loading NAFNet model from /mnt/workspace/NAFNet/pretrain_model/cv_nafnet_image-deblur_reds/pytorch_model.pt, with param key: [params].
        2023-09-04 11:47:32,296 - modelscope - INFO - load model done.
        2023-09-04 11:47:32,320 - modelscope - INFO - load image denoise model done
        Total Image:  10
        2023-09-04 11:47:33,402 - modelscope - WARNING - task image-deblurring input definition is missing
        2023-09-04 11:47:34,753 - modelscope - WARNING - task image-deblurring output keys are missing
        0/10 saved at results/nafnet_de_motion_blur/64.jpg
        1/10 saved at results/nafnet_de_motion_blur/2.jpg
        2/10 saved at results/nafnet_de_motion_blur/34.jpg
        3/10 saved at results/nafnet_de_motion_blur/54.jpg
        4/10 saved at results/nafnet_de_motion_blur/40.jpg
        5/10 saved at results/nafnet_de_motion_blur/10.jpg
        6/10 saved at results/nafnet_de_motion_blur/70.jpg
        7/10 saved at results/nafnet_de_motion_blur/4.png
        8/10 saved at results/nafnet_de_motion_blur/20.jpg
        9/10 saved at results/nafnet_de_motion_blur/50.jpg
    2. 图像超分,即提升图像分辨率和清晰度。支持以下几种算法,您可以任意选择一种来处理图像。

      RealESRGAN

      1. 下载代码及预训练文件。下载解压完成后,您可以在./Real-ESRGAN文件夹中查看该算法的源代码。

        单击此处查看运行结果

        http://pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com/aigc-data/restoration/repo/realesrgan.zip
        cn-hangzhou
        --2023-09-05 01:29:05--  http://pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com/aigc-data/restoration/repo/realesrgan.zip
        Resolving pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com (pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com)... 100.118.28.50, 100.118.28.49, 100.118.28.44, ...
        Connecting to pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com (pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com)|100.118.28.50|:80... connected.
        HTTP request sent, awaiting response... 200 OK
        Length: 151719684 (145M) [application/zip]
        Saving to: ‘realesrgan.zip’
        
        realesrgan.zip      100%[===================>] 144.69M  11.3MB/s    in 13s     
        
        2023-09-05 01:29:17 (11.5 MB/s) - ‘realesrgan.zip’ saved [151719684/151719684]
        
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      2. 根据需要运行合适的推理任务。命令执行成功后,您可以在./results/{task_name}中查看修复后的图像结果。

        单击此处查看运行结果

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      SwinIR

      1. 下载代码及预训练文件。下载解压完成后,您可以在./SwinIR文件夹中查看该算法的源代码。

        单击此处查看运行结果

        http://pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com/aigc-data/restoration/repo/swinir.zip
        cn-hangzhou
        --2023-09-05 01:34:02--  http://pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com/aigc-data/restoration/repo/swinir.zip
        Resolving pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com (pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com)... 100.118.28.44, 100.118.28.49, 100.118.28.45, ...
        Connecting to pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com (pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com)|100.118.28.44|:80... connected.
        HTTP request sent, awaiting response... 200 OK
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      2. 根据需要运行合适的推理任务。命令执行成功后,您可以在./results/{task_name}中查看修复后的图像结果。

        单击此处查看运行结果

        loading model from /mnt/workspace/SwinIR/pretrained_model/001_classicalSR_DF2K_s64w8_SwinIR-M_x4.pth
        /usr/local/lib/python3.10/dist-packages/torch/functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:3190.)
          return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]
        results//swinir_classical_sr_x4
        Testing 0 10                  
        Testing 1 2                   
        Testing 2 20                  
        Testing 3 34                  
        Testing 4 4                   
        Testing 5 40                  
        Testing 6 50                  
        Testing 7 54                  
        Testing 8 64                  
        Testing 9 70                  
        loading model from /mnt/workspace/SwinIR/pretrained_model/003_realSR_BSRGAN_DFO_s64w8_SwinIR-M_x4_GAN.pth
        /usr/local/lib/python3.10/dist-packages/torch/functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:3190.)
          return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]
        results//swinir_real_sr_x4
        Testing 0 10                  
        Testing 1 2                   
        Testing 2 20                  
        Testing 3 34                  
        Testing 4 4                   
        Testing 5 40                  
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        Testing 7 54                  
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        Testing 9 70                  
        loading model from /mnt/workspace/SwinIR/pretrained_model/004_grayDN_DFWB_s128w8_SwinIR-M_noise15.pth
        /usr/local/lib/python3.10/dist-packages/torch/functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:3190.)
          return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]
        results//swinir_gray_dn_noise15
        Testing 0 10                   - PSNR: 33.61 dB; SSIM: 0.9556; PSNRB: 0.00 dB;PSNR_Y: 0.00 dB; SSIM_Y: 0.0000; PSNRB_Y: 0.00 dB.
        Testing 1 2                    - PSNR: 33.54 dB; SSIM: 0.9048; PSNRB: 0.00 dB;PSNR_Y: 0.00 dB; SSIM_Y: 0.0000; PSNRB_Y: 0.00 dB.
        Testing 2 20                   - PSNR: 32.79 dB; SSIM: 0.9033; PSNRB: 0.00 dB;PSNR_Y: 0.00 dB; SSIM_Y: 0.0000; PSNRB_Y: 0.00 dB.
        Testing 3 34                   - PSNR: 32.80 dB; SSIM: 0.8973; PSNRB: 0.00 dB;PSNR_Y: 0.00 dB; SSIM_Y: 0.0000; PSNRB_Y: 0.00 dB.
        Testing 4 4                    - PSNR: 39.13 dB; SSIM: 0.9357; PSNRB: 0.00 dB;PSNR_Y: 0.00 dB; SSIM_Y: 0.0000; PSNRB_Y: 0.00 dB.
        Testing 5 40                   - PSNR: 31.12 dB; SSIM: 0.9500; PSNRB: 0.00 dB;PSNR_Y: 0.00 dB; SSIM_Y: 0.0000; PSNRB_Y: 0.00 dB.
        Testing 6 50                   - PSNR: 31.57 dB; SSIM: 0.9437; PSNRB: 0.00 dB;PSNR_Y: 0.00 dB; SSIM_Y: 0.0000; PSNRB_Y: 0.00 dB.
        Testing 7 54                   - PSNR: 36.47 dB; SSIM: 0.9115; PSNRB: 0.00 dB;PSNR_Y: 0.00 dB; SSIM_Y: 0.0000; PSNRB_Y: 0.00 dB.
        Testing 8 64                   - PSNR: 35.19 dB; SSIM: 0.9507; PSNRB: 0.00 dB;PSNR_Y: 0.00 dB; SSIM_Y: 0.0000; PSNRB_Y: 0.00 dB.
        Testing 9 70                   - PSNR: 31.88 dB; SSIM: 0.8856; PSNRB: 0.00 dB;PSNR_Y: 0.00 dB; SSIM_Y: 0.0000; PSNRB_Y: 0.00 dB.
        
        results//swinir_gray_dn_noise15 
        -- Average PSNR/SSIM(RGB): 33.81 dB; 0.9238
        loading model from /mnt/workspace/SwinIR/pretrained_model/005_colorDN_DFWB_s128w8_SwinIR-M_noise15.pth
        /usr/local/lib/python3.10/dist-packages/torch/functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:3190.)
          return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]
        results//swinir_color_dn_noise15
        Testing 0 10                   - PSNR: 36.38 dB; SSIM: 0.9705; PSNRB: 0.00 dB;PSNR_Y: 37.74 dB; SSIM_Y: 0.9749; PSNRB_Y: 0.00 dB.
        Testing 1 2                    - PSNR: 35.28 dB; SSIM: 0.9327; PSNRB: 0.00 dB;PSNR_Y: 37.29 dB; SSIM_Y: 0.9463; PSNRB_Y: 0.00 dB.
        Testing 2 20                   - PSNR: 35.06 dB; SSIM: 0.9315; PSNRB: 0.00 dB;PSNR_Y: 36.52 dB; SSIM_Y: 0.9432; PSNRB_Y: 0.00 dB.
        Testing 3 34                   - PSNR: 35.23 dB; SSIM: 0.9307; PSNRB: 0.00 dB;PSNR_Y: 36.58 dB; SSIM_Y: 0.9418; PSNRB_Y: 0.00 dB.
        Testing 4 4                    - PSNR: 39.07 dB; SSIM: 0.9320; PSNRB: 0.00 dB;PSNR_Y: 41.84 dB; SSIM_Y: 0.9568; PSNRB_Y: 0.00 dB.
        Testing 5 40                   - PSNR: 34.48 dB; SSIM: 0.9716; PSNRB: 0.00 dB;PSNR_Y: 35.83 dB; SSIM_Y: 0.9751; PSNRB_Y: 0.00 dB.
        Testing 6 50                   - PSNR: 34.92 dB; SSIM: 0.9648; PSNRB: 0.00 dB;PSNR_Y: 36.27 dB; SSIM_Y: 0.9702; PSNRB_Y: 0.00 dB.
        Testing 7 54                   - PSNR: 38.24 dB; SSIM: 0.9331; PSNRB: 0.00 dB;PSNR_Y: 39.60 dB; SSIM_Y: 0.9463; PSNRB_Y: 0.00 dB.
        Testing 8 64                   - PSNR: 37.77 dB; SSIM: 0.9678; PSNRB: 0.00 dB;PSNR_Y: 39.14 dB; SSIM_Y: 0.9733; PSNRB_Y: 0.00 dB.
        Testing 9 70                   - PSNR: 34.51 dB; SSIM: 0.9226; PSNRB: 0.00 dB;PSNR_Y: 35.85 dB; SSIM_Y: 0.9349; PSNRB_Y: 0.00 dB.
        
        results//swinir_color_dn_noise15 
        -- Average PSNR/SSIM(RGB): 36.10 dB; 0.9457
        -- Average PSNR_Y/SSIM_Y: 37.67 dB; 0.9563
        loading model from /mnt/workspace/SwinIR/pretrained_model/006_colorCAR_DFWB_s126w7_SwinIR-M_jpeg10.pth
        /usr/local/lib/python3.10/dist-packages/torch/functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:3190.)
          return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]
        results//swinir_color_jpeg_car_jpeg10
        Testing 0 10                  
        Testing 1 2                   
        Testing 2 20                  
        Testing 3 34                  
        Testing 4 4                   
        Testing 5 40                  
        Testing 6 50                  
        Testing 7 54                  
        Testing 8 64                  
        Testing 9 70                  

      HAT

      1. 下载代码和预训练文件。下载解压完成后,您可以在./HAT文件夹中查看该算法的源代码。

        单击此处查看运行结果

        http://pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com/aigc-data/restoration/repo/hat.zip
        cn-hangzhou
        --2023-09-05 01:47:39--  http://pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com/aigc-data/restoration/repo/hat.zip
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        Connecting to pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com (pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com)|100.118.28.49|:80... connected.
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      2. 根据需要运行合适的推理任务。命令执行成功后,您可以在./results/{task_name}中查看修复后的图像结果。

        单击此处查看运行结果

        /mnt/workspace/HAT
        /usr/local/lib/python3.10/dist-packages/torch/functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:3190.)
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    3. 面部增强,即检测并修复老照片中的人脸。

      1. 下载代码和预训练文件。下载解压完成后,您可以在./CodeFormer文件夹中查看该算法的源代码。

        单击此处查看运行结果

        http://pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com/aigc-data/restoration/repo/codeformer.zip
        cn-hangzhou
        --2023-09-05 02:21:39--  http://pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com/aigc-data/restoration/repo/codeformer.zip
        Resolving pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com (pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com)... 100.118.28.44, 100.118.28.50, 100.118.28.49, ...
        Connecting to pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com (pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com)|100.118.28.44|:80... connected.
        HTTP request sent, awaiting response... 200 OK
        Length: 627352702 (598M) [application/zip]
        Saving to: ‘codeformer.zip’
        
        codeformer.zip      100%[===================>] 598.29M  12.1MB/s    in 55s     
        
        2023-09-05 02:22:34 (10.9 MB/s) - ‘codeformer.zip’ saved [627352702/627352702]
        
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      2. 根据需要运行合适的推理任务。命令执行成功后,您可以在./results/{task_name}中查看修复后的图像结果。

        单击此处查看运行结果

        Face detection model: retinaface_resnet50
        Background upsampling: False, Face upsampling: False
        [1/10] Processing: 10.jpg
        Grayscale input: True
        	detect 0 faces
        [2/10] Processing: 2.jpg
        	detect 14 faces
        [3/10] Processing: 20.jpg
        	detect 0 faces
        [4/10] Processing: 34.jpg
        Grayscale input: True
        	detect 3 faces
        [5/10] Processing: 4.png
        	detect 1 faces
        [6/10] Processing: 40.jpg
        Grayscale input: True
        	detect 1 faces
        [7/10] Processing: 50.jpg
        Grayscale input: True
        	detect 1 faces
        [8/10] Processing: 54.jpg
        Grayscale input: True
        	detect 1 faces
        [9/10] Processing: 64.jpg
        Grayscale input: True
        	detect 1 faces
        [10/10] Processing: 70.jpg
        Grayscale input: True
        	detect 9 faces
        
        All results are saved in results/codeformer_0.5
        Face detection model: retinaface_resnet50
        Background upsampling: True, Face upsampling: False
        [1/10] Processing: 10.jpg
        Grayscale input: True
        	detect 0 faces
        [2/10] Processing: 2.jpg
        	detect 14 faces
        [3/10] Processing: 20.jpg
        	detect 0 faces
        [4/10] Processing: 34.jpg
        Grayscale input: True
        	detect 3 faces
        [5/10] Processing: 4.png
        	detect 1 faces
        [6/10] Processing: 40.jpg
        Grayscale input: True
        	detect 1 faces
        [7/10] Processing: 50.jpg
        Grayscale input: True
        	detect 1 faces
        [8/10] Processing: 54.jpg
        Grayscale input: True
        	detect 1 faces
        [9/10] Processing: 64.jpg
        Grayscale input: True
        	detect 1 faces
        [10/10] Processing: 70.jpg
        Grayscale input: True
        	detect 9 faces
        
        All results are saved in results/codeformer_0.5_bgup
        Face detection model: retinaface_resnet50
        Background upsampling: True, Face upsampling: True
        [1/10] Processing: 10.jpg
        Grayscale input: True
        	detect 0 faces
        [2/10] Processing: 2.jpg
        	detect 14 faces
        [3/10] Processing: 20.jpg
        	detect 0 faces
        [4/10] Processing: 34.jpg
        Grayscale input: True
        	detect 3 faces
        [5/10] Processing: 4.png
        	detect 1 faces
        [6/10] Processing: 40.jpg
        Grayscale input: True
        	detect 1 faces
        [7/10] Processing: 50.jpg
        Grayscale input: True
        	detect 1 faces
        [8/10] Processing: 54.jpg
        Grayscale input: True
        	detect 1 faces
        [9/10] Processing: 64.jpg
        Grayscale input: True
        	detect 1 faces
        [10/10] Processing: 70.jpg
        Grayscale input: True
        	detect 9 faces
        
        All results are saved in results/codeformer_0.5_bgup_faceup
        Face detection model: retinaface_resnet50
        Background upsampling: True, Face upsampling: True
        [1/10] Processing: 10.jpg
        Grayscale input: True
        	detect 0 faces
        [2/10] Processing: 2.jpg
        	detect 14 faces
        [3/10] Processing: 20.jpg
        	detect 0 faces
        [4/10] Processing: 34.jpg
        Grayscale input: True
        	detect 3 faces
        [5/10] Processing: 4.png
        	detect 1 faces
        [6/10] Processing: 40.jpg
        Grayscale input: True
        	detect 1 faces
        [7/10] Processing: 50.jpg
        Grayscale input: True
        	detect 1 faces
        [8/10] Processing: 54.jpg
        Grayscale input: True
        	detect 1 faces
        [9/10] Processing: 64.jpg
        Grayscale input: True
        	detect 1 faces
        [10/10] Processing: 70.jpg
        Grayscale input: True
        	detect 9 faces
        
        All results are saved in results/codeformer_1.0_bgup_faceup
        Face detection model: retinaface_resnet50
        Background upsampling: True, Face upsampling: True
        [1/10] Processing: 10.jpg
        Grayscale input: True
        	detect 0 faces
        [2/10] Processing: 2.jpg
        	detect 14 faces
        [3/10] Processing: 20.jpg
        	detect 0 faces
        [4/10] Processing: 34.jpg
        Grayscale input: True
        	detect 3 faces
        	Input is a 16-bit image
        	Input is a 16-bit image
        [5/10] Processing: 4.png
        	detect 1 faces
        [6/10] Processing: 40.jpg
        Grayscale input: True
        	detect 1 faces
        [7/10] Processing: 50.jpg
        Grayscale input: True
        	detect 1 faces
        [8/10] Processing: 54.jpg
        Grayscale input: True
        	detect 1 faces
        [9/10] Processing: 64.jpg
        Grayscale input: True
        	detect 1 faces
        [10/10] Processing: 70.jpg
        Grayscale input: True
        	detect 9 faces
        
        All results are saved in results/codeformer_0.0_bgup_faceup
    4. 图像上色,有条件或无条件的进行老照片上色。

      无条件上色

      1. 下载代码和预训练文件,并安装ModelScope环境。下载解压完成后,您可以在./Colorization文件夹中查看该算法的源代码。

        单击此处查看运行结果

        Looking in indexes: https://mirrors.cloud.aliyuncs.com/pypi/simple
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        Requirement already satisfied: pycparser in /usr/local/lib/python3.10/dist-packages (from cffi>=1.12->cryptography>=2.6.0->aliyun-python-sdk-core>=2.13.12->oss2->modelscope) (2.21)
        WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv
        
        [notice] A new release of pip is available: 23.0.1 -> 23.2.1
        [notice] To update, run: python3 -m pip install --upgrade pip
        http://pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com/aigc-data/restoration/repo/color.zip
        cn-hangzhou
        --2023-09-05 02:30:04--  http://pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com/aigc-data/restoration/repo/color.zip
        Resolving pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com (pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com)... 100.118.28.45, 100.118.28.44, 100.118.28.50, ...
        Connecting to pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com (pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com)|100.118.28.45|:80... connected.
        HTTP request sent, awaiting response... 200 OK
        Length: 1659285229 (1.5G) [application/zip]
        Saving to: ‘color.zip’
        
        color.zip           100%[===================>]   1.54G  12.9MB/s    in 2m 10s  
        
        2023-09-05 02:32:14 (12.2 MB/s) - ‘color.zip’ saved [1659285229/1659285229]
        
        Archive:  color.zip
           creating: Colorization/
           creating: Colorization/.ipynb_checkpoints/
         extracting: Colorization/.ipynb_checkpoints/demo-checkpoint.py  
           creating: Colorization/pretrain/
           creating: Colorization/pretrain/cv_ddcolor_image-colorization/
          inflating: Colorization/pretrain/cv_ddcolor_image-colorization/pytorch_model.pt  
          inflating: Colorization/pretrain/cv_ddcolor_image-colorization/.mdl  
          inflating: Colorization/pretrain/cv_ddcolor_image-colorization/.msc  
          inflating: Colorization/pretrain/cv_ddcolor_image-colorization/README.md  
           creating: Colorization/pretrain/cv_ddcolor_image-colorization/resources/
          inflating: Colorization/pretrain/cv_ddcolor_image-colorization/resources/ddcolor_arch.jpg  
          inflating: Colorization/pretrain/cv_ddcolor_image-colorization/resources/demo2.jpg  
          inflating: Colorization/pretrain/cv_ddcolor_image-colorization/resources/demo3.jpg  
          inflating: Colorization/pretrain/cv_ddcolor_image-colorization/resources/demo.jpg  
          inflating: Colorization/pretrain/cv_ddcolor_image-colorization/configuration.json  
           creating: Colorization/pretrain/cv_csrnet_image-color-enhance-models/
          inflating: Colorization/pretrain/cv_csrnet_image-color-enhance-models/pytorch_model.pt  
         extracting: Colorization/pretrain/cv_csrnet_image-color-enhance-models/.mdl  
          inflating: Colorization/pretrain/cv_csrnet_image-color-enhance-models/.msc  
          inflating: Colorization/pretrain/cv_csrnet_image-color-enhance-models/README.md  
          inflating: Colorization/pretrain/cv_csrnet_image-color-enhance-models/configuration.json  
           creating: Colorization/pretrain/cv_csrnet_image-color-enhance-models/data/
          inflating: Colorization/pretrain/cv_csrnet_image-color-enhance-models/data/csrnet_1.png  
          inflating: Colorization/pretrain/cv_csrnet_image-color-enhance-models/data/1.png  
           creating: Colorization/pretrain/cv_unet_image-colorization/
          inflating: Colorization/pretrain/cv_unet_image-colorization/pytorch_model.pt  
         extracting: Colorization/pretrain/cv_unet_image-colorization/.mdl  
          inflating: Colorization/pretrain/cv_unet_image-colorization/.msc  
          inflating: Colorization/pretrain/cv_unet_image-colorization/README.md  
          inflating: Colorization/pretrain/cv_unet_image-colorization/configuration.json  
           creating: Colorization/pretrain/cv_unet_image-colorization/description/
          inflating: Colorization/pretrain/cv_unet_image-colorization/description/demo2.jpg  
          inflating: Colorization/pretrain/cv_unet_image-colorization/description/demo3.png  
          inflating: Colorization/pretrain/cv_unet_image-colorization/description/demo.jpg  
          inflating: Colorization/pretrain/cv_unet_image-colorization/description/deoldify_arch.png  
          inflating: Colorization/demo.py    
      2. 根据需要运行合适的推理任务。命令执行成功后,您可以在./results/{task_name}中查看修复后的图像结果。

        单击此处查看运行结果

        2023-09-05 02:36:59,816 - modelscope - INFO - PyTorch version 1.13.1+cu117 Found.
        2023-09-05 02:36:59,818 - modelscope - INFO - Loading ast index from /root/.cache/modelscope/ast_indexer
        2023-09-05 02:36:59,890 - modelscope - INFO - Loading done! Current index file version is 1.8.4, with md5 80fa9349fc3e7b04fcfad511918062b1 and a total number of 902 components indexed
        2023-09-05 02:37:00,925 - modelscope - INFO - initiate model from /mnt/workspace/Colorization/pretrain/cv_ddcolor_image-colorization
        2023-09-05 02:37:00,926 - modelscope - INFO - initiate model from location /mnt/workspace/Colorization/pretrain/cv_ddcolor_image-colorization.
        2023-09-05 02:37:00,926 - modelscope - INFO - initialize model from /mnt/workspace/Colorization/pretrain/cv_ddcolor_image-colorization
        2023-09-05 02:37:05,703 - modelscope - INFO - Loading DDColor model from /mnt/workspace/Colorization/pretrain/cv_ddcolor_image-colorization/pytorch_model.pt, with param key: [params].
        2023-09-05 02:37:05,906 - modelscope - INFO - load model done.
        2023-09-05 02:37:05,927 - modelscope - WARNING - No preprocessor field found in cfg.
        2023-09-05 02:37:05,927 - modelscope - WARNING - No val key and type key found in preprocessor domain of configuration.json file.
        2023-09-05 02:37:05,927 - modelscope - WARNING - Cannot find available config to build preprocessor at mode inference, current config: {'model_dir': '/mnt/workspace/Colorization/pretrain/cv_ddcolor_image-colorization'}. trying to build by task and model information.
        2023-09-05 02:37:05,927 - modelscope - WARNING - No preprocessor key ('ddcolor', 'image-colorization') found in PREPROCESSOR_MAP, skip building preprocessor.
        2023-09-05 02:37:05,948 - modelscope - INFO - load model done
        Total Image:  10
        0/10 saved at results/DDC/64.jpg
        1/10 saved at results/DDC/2.jpg
        2/10 saved at results/DDC/34.jpg
        3/10 saved at results/DDC/54.jpg
        4/10 saved at results/DDC/40.jpg
        5/10 saved at results/DDC/10.jpg
        6/10 saved at results/DDC/70.jpg
        7/10 saved at results/DDC/4.png
        8/10 saved at results/DDC/20.jpg
        9/10 saved at results/DDC/50.jpg
        2023-09-05 02:37:11,906 - modelscope - INFO - PyTorch version 1.13.1+cu117 Found.
        2023-09-05 02:37:11,907 - modelscope - INFO - Loading ast index from /root/.cache/modelscope/ast_indexer
        2023-09-05 02:37:11,979 - modelscope - INFO - Loading done! Current index file version is 1.8.4, with md5 80fa9349fc3e7b04fcfad511918062b1 and a total number of 902 components indexed
        2023-09-05 02:37:13,020 - modelscope - INFO - initiate model from /mnt/workspace/Colorization/pretrain/cv_ddcolor_image-colorization
        2023-09-05 02:37:13,020 - modelscope - INFO - initiate model from location /mnt/workspace/Colorization/pretrain/cv_ddcolor_image-colorization.
        2023-09-05 02:37:13,021 - modelscope - INFO - initialize model from /mnt/workspace/Colorization/pretrain/cv_ddcolor_image-colorization
        2023-09-05 02:37:18,528 - modelscope - INFO - Loading DDColor model from /mnt/workspace/Colorization/pretrain/cv_ddcolor_image-colorization/pytorch_model.pt, with param key: [params].
        2023-09-05 02:37:18,774 - modelscope - INFO - load model done.
        2023-09-05 02:37:18,797 - modelscope - WARNING - No preprocessor field found in cfg.
        2023-09-05 02:37:18,797 - modelscope - WARNING - No val key and type key found in preprocessor domain of configuration.json file.
        2023-09-05 02:37:18,797 - modelscope - WARNING - Cannot find available config to build preprocessor at mode inference, current config: {'model_dir': '/mnt/workspace/Colorization/pretrain/cv_ddcolor_image-colorization'}. trying to build by task and model information.
        2023-09-05 02:37:18,797 - modelscope - WARNING - No preprocessor key ('ddcolor', 'image-colorization') found in PREPROCESSOR_MAP, skip building preprocessor.
        2023-09-05 02:37:18,819 - modelscope - INFO - load model done
        2023-09-05 02:37:18,821 - modelscope - INFO - initiate model from /mnt/workspace/Colorization/pretrain/cv_csrnet_image-color-enhance-models
        2023-09-05 02:37:18,821 - modelscope - INFO - initiate model from location /mnt/workspace/Colorization/pretrain/cv_csrnet_image-color-enhance-models.
        2023-09-05 02:37:18,822 - modelscope - INFO - initialize model from /mnt/workspace/Colorization/pretrain/cv_csrnet_image-color-enhance-models
        2023-09-05 02:37:19,861 - modelscope - INFO - Loading CSRNet model from /mnt/workspace/Colorization/pretrain/cv_csrnet_image-color-enhance-models/pytorch_model.pt, with param key: [params].
        2023-09-05 02:37:19,863 - modelscope - INFO - load model done.
        Total Image:  10
        use_enhance
        0/10 saved at results/DDC/enhance_64.jpg
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        1/10 saved at results/DDC/enhance_2.jpg
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        2/10 saved at results/DDC/enhance_34.jpg
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        3/10 saved at results/DDC/enhance_54.jpg
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        4/10 saved at results/DDC/enhance_40.jpg
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        5/10 saved at results/DDC/enhance_10.jpg
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        6/10 saved at results/DDC/enhance_70.jpg
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        7/10 saved at results/DDC/enhance_4.png
        use_enhance
        8/10 saved at results/DDC/enhance_20.jpg
        use_enhance
        9/10 saved at results/DDC/enhance_50.jpg
        2023-09-05 02:37:25,090 - modelscope - INFO - PyTorch version 1.13.1+cu117 Found.
        2023-09-05 02:37:25,091 - modelscope - INFO - Loading ast index from /root/.cache/modelscope/ast_indexer
        2023-09-05 02:37:25,150 - modelscope - INFO - Loading done! Current index file version is 1.8.4, with md5 80fa9349fc3e7b04fcfad511918062b1 and a total number of 902 components indexed
        2023-09-05 02:37:25,728 - modelscope - INFO - initiate model from /mnt/workspace/Colorization/pretrain/cv_unet_image-colorization
        2023-09-05 02:37:25,728 - modelscope - INFO - initiate model from location /mnt/workspace/Colorization/pretrain/cv_unet_image-colorization.
        2023-09-05 02:37:25,730 - modelscope - WARNING - No preprocessor field found in cfg.
        2023-09-05 02:37:25,730 - modelscope - WARNING - No val key and type key found in preprocessor domain of configuration.json file.
        2023-09-05 02:37:25,730 - modelscope - WARNING - Cannot find available config to build preprocessor at mode inference, current config: {'model_dir': '/mnt/workspace/Colorization/pretrain/cv_unet_image-colorization'}. trying to build by task and model information.
        2023-09-05 02:37:25,730 - modelscope - WARNING - Find task: image-colorization, model type: None. Insufficient information to build preprocessor, skip building preprocessor
        /usr/local/lib/python3.10/dist-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
          warnings.warn(
        /usr/local/lib/python3.10/dist-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=ResNet101_Weights.IMAGENET1K_V1`. You can also use `weights=ResNet101_Weights.DEFAULT` to get the most up-to-date weights.
          warnings.warn(msg)
        Downloading: "https://download.pytorch.org/models/resnet101-63fe2227.pth" to /root/.cache/torch/hub/checkpoints/resnet101-63fe2227.pth
        100%|████████████████████████████████████████| 171M/171M [00:08<00:00, 21.7MB/s]
        2023-09-05 02:37:40,123 - modelscope - INFO - load model done
        Total Image:  10
        0/10 saved at results/DeOldify/64.jpg
        1/10 saved at results/DeOldify/2.jpg
        2/10 saved at results/DeOldify/34.jpg
        3/10 saved at results/DeOldify/54.jpg
        4/10 saved at results/DeOldify/40.jpg
        5/10 saved at results/DeOldify/10.jpg
        6/10 saved at results/DeOldify/70.jpg
        7/10 saved at results/DeOldify/4.png
        8/10 saved at results/DeOldify/20.jpg
        9/10 saved at results/DeOldify/50.jpg
        2023-09-05 02:37:44,830 - modelscope - INFO - PyTorch version 1.13.1+cu117 Found.
        2023-09-05 02:37:44,831 - modelscope - INFO - Loading ast index from /root/.cache/modelscope/ast_indexer
        2023-09-05 02:37:44,898 - modelscope - INFO - Loading done! Current index file version is 1.8.4, with md5 80fa9349fc3e7b04fcfad511918062b1 and a total number of 902 components indexed
        2023-09-05 02:37:45,464 - modelscope - INFO - initiate model from /mnt/workspace/Colorization/pretrain/cv_unet_image-colorization
        2023-09-05 02:37:45,464 - modelscope - INFO - initiate model from location /mnt/workspace/Colorization/pretrain/cv_unet_image-colorization.
        2023-09-05 02:37:45,466 - modelscope - WARNING - No preprocessor field found in cfg.
        2023-09-05 02:37:45,466 - modelscope - WARNING - No val key and type key found in preprocessor domain of configuration.json file.
        2023-09-05 02:37:45,466 - modelscope - WARNING - Cannot find available config to build preprocessor at mode inference, current config: {'model_dir': '/mnt/workspace/Colorization/pretrain/cv_unet_image-colorization'}. trying to build by task and model information.
        2023-09-05 02:37:45,466 - modelscope - WARNING - Find task: image-colorization, model type: None. Insufficient information to build preprocessor, skip building preprocessor
        /usr/local/lib/python3.10/dist-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
          warnings.warn(
        /usr/local/lib/python3.10/dist-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=ResNet101_Weights.IMAGENET1K_V1`. You can also use `weights=ResNet101_Weights.DEFAULT` to get the most up-to-date weights.
          warnings.warn(msg)
        2023-09-05 02:37:49,758 - modelscope - INFO - load model done
        2023-09-05 02:37:49,760 - modelscope - INFO - initiate model from /mnt/workspace/Colorization/pretrain/cv_csrnet_image-color-enhance-models
        2023-09-05 02:37:49,760 - modelscope - INFO - initiate model from location /mnt/workspace/Colorization/pretrain/cv_csrnet_image-color-enhance-models.
        2023-09-05 02:37:49,761 - modelscope - INFO - initialize model from /mnt/workspace/Colorization/pretrain/cv_csrnet_image-color-enhance-models
        2023-09-05 02:37:49,766 - modelscope - INFO - Loading CSRNet model from /mnt/workspace/Colorization/pretrain/cv_csrnet_image-color-enhance-models/pytorch_model.pt, with param key: [params].
        2023-09-05 02:37:49,768 - modelscope - INFO - load model done.
        Total Image:  10
        use_enhance
        0/10 saved at results/DeOldify/enhance_64.jpg
        use_enhance
        1/10 saved at results/DeOldify/enhance_2.jpg
        use_enhance
        2/10 saved at results/DeOldify/enhance_34.jpg
        use_enhance
        3/10 saved at results/DeOldify/enhance_54.jpg
        use_enhance
        4/10 saved at results/DeOldify/enhance_40.jpg
        use_enhance
        5/10 saved at results/DeOldify/enhance_10.jpg
        use_enhance
        6/10 saved at results/DeOldify/enhance_70.jpg
        use_enhance
        7/10 saved at results/DeOldify/enhance_4.png
        use_enhance
        8/10 saved at results/DeOldify/enhance_20.jpg
        use_enhance
        9/10 saved at results/DeOldify/enhance_50.jpg

      有条件上色

      1. 下载代码和预训练文件。下载解压完成后,您可以在./sample./unicolor文件夹中查看算法的源代码。

        单击此处查看运行结果

        http://pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com/aigc-data/restoration/repo/sam_unicolor.zip
        cn-hangzhou
        --2023-09-05 02:44:17--  http://pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com/aigc-data/restoration/repo/sam_unicolor.zip
        Resolving pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com (pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com)... 100.118.28.44, 100.118.28.45, 100.118.28.49, ...
        Connecting to pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com (pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com)|100.118.28.44|:80... connected.
        HTTP request sent, awaiting response... 200 OK
        Length: 9102984978 (8.5G) [application/zip]
        Saving to: ‘sam_unicolor.zip’
        
        sam_unicolor.zip    100%[===================>]   8.48G  17.6MB/s    in 8m 33s  
        
        2023-09-05 02:52:51 (16.9 MB/s) - ‘sam_unicolor.zip’ saved [9102984978/9102984978]
        
        Archive:  sam_unicolor.zip
           creating: sample/
          inflating: sample/utils_func.py    
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          inflating: sample/SAM/CONTRIBUTING.md  
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      2. 加载模型文件和待处理的图片。按顺序依次执行单元格命令,获得如下结果。

        单击此处查看运行结果

        image.png594e606afb554ba38ab8bd8bf21822a5.png
      3. 选择需要修改的颜色和点的坐标。

        单击此处查看运行结果

        image.png
      4. 由SAM扩展上色区域。

        单击此处查看运行结果

        image.pngimage.pngimage.png
      5. 对指定区域进行上色。

        单击此处查看运行结果

        image.png
    5. 划痕清理。即检测划痕位置或手动标记划痕位置,进行图像填充。

      1. 下载代码和预训练文件,并安装ModelScope环境。下载解压完成后,您可以在./inpaint文件夹中查看LaMa算法的源代码。

        单击此处查看运行结果

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        WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv
        
        [notice] A new release of pip is available: 23.0.1 -> 23.2.1
        [notice] To update, run: python3 -m pip install --upgrade pip
        http://pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com/aigc-data/restoration/repo/inpaint.zip
        cn-hangzhou
        --2023-09-05 03:10:46--  http://pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com/aigc-data/restoration/repo/inpaint.zip
        Resolving pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com (pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com)... 100.118.28.45, 100.118.28.50, 100.118.28.49, ...
        Connecting to pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com (pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com)|100.118.28.45|:80... connected.
        HTTP request sent, awaiting response... 200 OK
        Length: 603971848 (576M) [application/zip]
        Saving to: ‘inpaint.zip’
        
        inpaint.zip         100%[===================>] 575.99M  10.0MB/s    in 56s     
        
        2023-09-05 03:11:42 (10.3 MB/s) - ‘inpaint.zip’ saved [603971848/603971848]
        
        Archive:  inpaint.zip
           creating: inpaint/
           creating: inpaint/.ipynb_checkpoints/
          inflating: inpaint/.ipynb_checkpoints/demo-checkpoint.py  
          inflating: inpaint/demo.py         
           creating: inpaint/pretrain/
           creating: inpaint/pretrain/cv_fft_inpainting_lama/
          inflating: inpaint/pretrain/cv_fft_inpainting_lama/resnet50-imagenet.pth  
          inflating: inpaint/pretrain/cv_fft_inpainting_lama/.mdl  
          inflating: inpaint/pretrain/cv_fft_inpainting_lama/pytorch_model.pt  
           creating: inpaint/pretrain/cv_fft_inpainting_lama/ade20k/
           creating: inpaint/pretrain/cv_fft_inpainting_lama/ade20k/ade20k-resnet50dilated-ppm_deepsup/
          inflating: inpaint/pretrain/cv_fft_inpainting_lama/ade20k/ade20k-resnet50dilated-ppm_deepsup/encoder_epoch_20.pth  
          inflating: inpaint/pretrain/cv_fft_inpainting_lama/README.md  
          inflating: inpaint/pretrain/cv_fft_inpainting_lama/configuration.json  
           creating: inpaint/pretrain/cv_fft_inpainting_lama/data/
          inflating: inpaint/pretrain/cv_fft_inpainting_lama/data/1.gif  
          inflating: inpaint/pretrain/cv_fft_inpainting_lama/data/2.gif  
          inflating: inpaint/pretrain/cv_fft_inpainting_lama/.msc  
      2. 启动UI界面。

        单击此处查看运行结果

        2023-09-05 03:12:31,086 - modelscope - INFO - PyTorch version 1.13.1+cu117 Found.
        2023-09-05 03:12:31,087 - modelscope - INFO - Loading ast index from /root/.cache/modelscope/ast_indexer
        2023-09-05 03:12:31,118 - modelscope - INFO - Loading done! Current index file version is 1.8.4, with md5 80fa9349fc3e7b04fcfad511918062b1 and a total number of 902 components indexed
        2023-09-05 03:12:31,921 - modelscope - INFO - initiate model from /mnt/workspace/inpaint/pretrain/cv_fft_inpainting_lama
        2023-09-05 03:12:31,921 - modelscope - INFO - initiate model from location /mnt/workspace/inpaint/pretrain/cv_fft_inpainting_lama.
        2023-09-05 03:12:31,922 - modelscope - INFO - initialize model from /mnt/workspace/inpaint/pretrain/cv_fft_inpainting_lama
        2023-09-05 03:12:32,123 - modelscope - INFO - BaseInpaintingTrainingModule init called, predict_only is False
        Loading weights for net_encoder
        2023-09-05 03:12:33,068 - modelscope - INFO - BaseInpaintingTrainingModule init done
        2023-09-05 03:12:33,068 - modelscope - INFO - loading pretrained model from /mnt/workspace/inpaint/pretrain/cv_fft_inpainting_lama/pytorch_model.pt
        2023-09-05 03:12:33,319 - modelscope - WARNING - No preprocessor field found in cfg.
        2023-09-05 03:12:33,319 - modelscope - WARNING - No val key and type key found in preprocessor domain of configuration.json file.
        2023-09-05 03:12:33,319 - modelscope - WARNING - Cannot find available config to build preprocessor at mode inference, current config: {'model_dir': '/mnt/workspace/inpaint/pretrain/cv_fft_inpainting_lama'}. trying to build by task and model information.
        2023-09-05 03:12:33,319 - modelscope - WARNING - No preprocessor key ('FFTInpainting', 'image-inpainting') found in PREPROCESSOR_MAP, skip building preprocessor.
        2023-09-05 03:12:33,320 - modelscope - INFO - loading model from dir /mnt/workspace/inpaint/pretrain/cv_fft_inpainting_lama
        2023-09-05 03:12:33,320 - modelscope - INFO - BaseInpaintingTrainingModule init called, predict_only is True
        2023-09-05 03:12:33,708 - modelscope - INFO - BaseInpaintingTrainingModule init done
        2023-09-05 03:12:33,709 - modelscope - INFO - loading pretrained model from /mnt/workspace/inpaint/pretrain/cv_fft_inpainting_lama/pytorch_model.pt
        2023-09-05 03:12:34,498 - modelscope - INFO - loading model done, refinement is set to False
        /usr/local/lib/python3.10/dist-packages/gradio/layouts.py:75: UserWarning: mobile_collapse is no longer supported.
          warnings.warn("mobile_collapse is no longer supported.")
        /usr/local/lib/python3.10/dist-packages/gradio/components.py:122: UserWarning: 'rounded' styling is no longer supported. To round adjacent components together, place them in a Column(variant='box').
          warnings.warn(
        /usr/local/lib/python3.10/dist-packages/gradio/components.py:131: UserWarning: 'margin' styling is no longer supported. To place adjacent components together without margin, place them in a Column(variant='box').
          warnings.warn(
        Running on local URL:  http://127.0.0.1:7860
        
        To create a public link, set `share=True` in `launch()`.
      3. 在返回的运行详情结果中单击URL链接(http://127.0.0.1:7860),进入WebUI页面。在该页面,根据界面提示修复老照片划痕。

      【说明】由于http://127.0.0.1:7860为内网访问地址,仅支持在当前的DSW实例内部通过单击链接来访问WebUI页面,不支持通过外部浏览器直接访问。

      单击此处查看运行结果

      image.png

    基于SD WebUI修复图片

    SD WebUI是目前最受欢迎的AI绘画工具之一,在图像生成任务的基础上,其集成了丰富的超分模型,可用于可视化的图像修复。通过交互式的控制,您可以更加精细化和方便的进行图像修复任务。

    为了解决模型和插件下载困难的问题,PAI在本教程中预置了与图像修复相关的插件和模型,您可以更轻松、便捷地体验SD WebUI的老照片修复功能。

    如果您不需要使用或修改算法的源码,可以直接前往SD WebUI章节,启动SD WebUI页面来修复图片。具体操作步骤如下。

    1. 下载SDWebUI代码和内置的插件。

      单击此处查看运行结果

      http://pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com/aigc-data/restoration/repo/sdwebui.zip
      cn-hangzhou
      --2023-09-05 07:22:40--  http://pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com/aigc-data/restoration/repo/sdwebui.zip
      Resolving pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com (pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com)... 100.118.28.45, 100.118.28.50, 100.118.28.44, ...
      Connecting to pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com (pai-vision-data-hz2.oss-cn-hangzhou-internal.aliyuncs.com)|100.118.28.45|:80... connected.
      HTTP request sent, awaiting response... 200 OK
      Length: 15945784501 (15G) [application/zip]
      Saving to: ‘sdwebui.zip’
      
      sdwebui.zip          99%[==================> ]  14.82G  20.8MB/s    in 12m 22s 
      
      
      Cannot write to ‘sdwebui.zip’ (No space left on device).
      Archive:  sdwebui.zip
        End-of-central-directory signature not found.  Either this file is not
        a zipfile, or it constitutes one disk of a multi-part archive.  In the
        latter case the central directory and zipfile comment will be found on
        the last disk(s) of this archive.
      unzip:  cannot find zipfile directory in one of sdwebui.zip or
              sdwebui.zip.zip, and cannot find sdwebui.zip.ZIP, period.
    2. 下载插件所需的模型文件。

      单击此处查看运行结果

      --2023-09-05 07:35:39--  https://pai-vision-data-sh.oss-cn-shanghai.aliyuncs.com/aigc-data/restoration/models/resnet101-63fe2227.pth
      Resolving pai-vision-data-sh.oss-cn-shanghai.aliyuncs.com (pai-vision-data-sh.oss-cn-shanghai.aliyuncs.com)... 106.14.228.10
      Connecting to pai-vision-data-sh.oss-cn-shanghai.aliyuncs.com (pai-vision-data-sh.oss-cn-shanghai.aliyuncs.com)|106.14.228.10|:443... connected.
      HTTP request sent, awaiting response... 200 OK
      Length: 178793939 (171M) [application/octet-stream]
      Saving to: ‘/root/.cache/torch/hub/checkpoints/resnet101-63fe2227.pth.1’
      
      resnet101-63fe2227. 100%[===================>] 170.51M  14.8MB/s    in 12s     
      
      2023-09-05 07:35:52 (14.0 MB/s) - ‘/root/.cache/torch/hub/checkpoints/resnet101-63fe2227.pth.1’ saved [178793939/178793939]
      
      --2023-09-05 07:35:52--  https://pai-vision-data-sh.oss-cn-shanghai.aliyuncs.com/aigc-data/restoration/models/resnet34-b627a593.pth
      Resolving pai-vision-data-sh.oss-cn-shanghai.aliyuncs.com (pai-vision-data-sh.oss-cn-shanghai.aliyuncs.com)... 106.14.228.10
      Connecting to pai-vision-data-sh.oss-cn-shanghai.aliyuncs.com (pai-vision-data-sh.oss-cn-shanghai.aliyuncs.com)|106.14.228.10|:443... connected.
      HTTP request sent, awaiting response... 200 OK
      Length: 87319819 (83M) [application/octet-stream]
      Saving to: ‘/root/.cache/torch/hub/checkpoints/resnet34-b627a593.pth’
      
      resnet34-b627a593.p 100%[===================>]  83.27M  19.6MB/s    in 4.4s    
      
      2023-09-05 07:35:56 (18.9 MB/s) - ‘/root/.cache/torch/hub/checkpoints/resnet34-b627a593.pth’ saved [87319819/87319819]
      
    3. 启动SD WebUI应用。

      单击此处查看运行结果

      Unable to symlink '/usr/bin/python' to '/mnt/workspace/stable-diffusion-webui/venv/bin/python'
      
      ################################################################
      Install script for stable-diffusion + Web UI
      Tested on Debian 11 (Bullseye)
      ################################################################
      
      ################################################################
      Running on root user
      ################################################################
      
      ################################################################
      Repo already cloned, using it as install directory
      ################################################################
      
      ################################################################
      Create and activate python venv
      ################################################################
      
      ################################################################
      Launching launch.py...
      ################################################################
      Cannot locate TCMalloc (improves CPU memory usage)
      Python 3.10.6 (main, Mar 10 2023, 10:55:28) [GCC 11.3.0]
      Version: v1.5.1
      Commit hash: 68f336bd994bed5442ad95bad6b6ad5564a5409a
      Installing fastai==1.0.60 for DeOldify extension
      Installing ffmpeg-python for DeOldify extension
      Installing yt-dlp for DeOldify extension
      Installing opencv-python for DeOldify extension
      Installing Pillow for DeOldify extension
      
      
      Launching Web UI with arguments: --no-download-sd-model --xformers --gradio-queue --disable-safe-unpickle
      No SDP backend available, likely because you are running in pytorch versions < 2.0. In fact, you are using PyTorch 1.13.1+cu117. You might want to consider upgrading.
      ==============================================================================
      You are running torch 1.13.1+cu117.
      The program is tested to work with torch 2.0.0.
      To reinstall the desired version, run with commandline flag --reinstall-torch.
      Beware that this will cause a lot of large files to be downloaded, as well as
      there are reports of issues with training tab on the latest version.
      
      Use --skip-version-check commandline argument to disable this check.
      ==============================================================================
      =================================================================================
      You are running xformers 0.0.16rc425.
      The program is tested to work with xformers 0.0.20.
      To reinstall the desired version, run with commandline flag --reinstall-xformers.
      
      Use --skip-version-check commandline argument to disable this check.
      =================================================================================
      Tag Autocomplete: Could not locate model-keyword extension, Lora trigger word completion will be limited to those added through the extra networks menu.
      2023-09-05 07:38:10,384 - ControlNet - INFO - ControlNet v1.1.238
      ControlNet preprocessor location: /mnt/workspace/stable-diffusion-webui/extensions/sd-webui-controlnet/annotator/downloads
      2023-09-05 07:38:10,554 - ControlNet - INFO - ControlNet v1.1.238
      Loading weights [e9d3cedc4b] from /mnt/workspace/stable-diffusion-webui/models/Stable-diffusion/realisticVisionV40_v40VAE.safetensors
      Running on local URL:  http://127.0.0.1:7860
      
      To create a public link, set `share=True` in `launch()`.
      Startup time: 28.1s (launcher: 17.7s, import torch: 3.3s, import gradio: 1.6s, setup paths: 1.7s, other imports: 0.9s, setup codeformer: 0.1s, load scripts: 1.9s, create ui: 0.6s, gradio launch: 0.3s).
      Creating model from config: /mnt/workspace/stable-diffusion-webui/configs/v1-inference.yaml
      LatentDiffusion: Running in eps-prediction mode
      DiffusionWrapper has 859.52 M params.
      Applying attention optimization: xformers... done.
      Model loaded in 13.3s (load weights from disk: 1.2s, create model: 0.7s, apply weights to model: 10.6s, apply half(): 0.3s, move model to device: 0.4s).
    4. 当上个步骤启动WebUI运行完成后,在返回的运行详情结果中单击URL链接(http://127.0.0.1:7860),进入WebUI页面。后续您可以在该页面进行模型推理。

步骤三:修复图片

完成基于源码的图片修复操作步骤后,您已经成功完成了图片的修复,您可以前往指定的目录查看修复后的图片结果。

完成基于SDWebUI的图片修复操作步骤后,您需要在SDWebUI页面上进行进一步的操作,以实现老照片的修复。PAI提供了最常见的三种操作方式供您选择:

方式一:附加功能

您可以在附加功能选项卡中对图像进行适当的超分、面部增强、图像上色任务。以下参数配置仅为示例说明,您可以根据实际场景来调整参数值。image.png

  1. 单击附加功能,切换至附加功能选项卡。

  2. 根据界面提示,将待修复的图片上传到单张图像选项卡中。

  3. 选择缩放比例并设置放大器。

    • 缩放比例:配置为4。

    • Upscaler 1:选择除LDSR外的其他选项。

    • Upscaler2(可选配置)。

  4. (可选)设置面部增强算法及其权重。

    • GFPGAN可见度:配置为1。

    • CodeFormer可见度:配置为0.665。

    • CodeFormer权重:配置为0.507。

  5. (可选)选中Deoldify进行图片上色,选中Artistic切换上色模型,并调节权重。

  6. 单击生成,即可在右侧区域生成修复后的图片。生成的图片保存到了DSW实例./stable-diffusion-webui/outputs/extras-images文件夹中。您可以在DSW的Notebook选项卡中,右键单击图片文件并单击Download,即可将图片下载到本地。

方式二:StableSR插件

以下参数配置仅为示例说明,您可以根据实际场景调整参数值。

  1. 切换模型为SD2.1,并切换至图生图选项卡。image.png

  2. 根据界面提示,将待修复的图片上传到图生图选项卡中。image.png

  3. 请参考以下内容来设置相关参数。image.png

    • 如果提示显存不够,可以展开分块VAE,选中Enable Tiled VAE,并将下方的编码器图块尺寸解码器土块尺寸数值调小。

    • 脚本选择StableSR

    • SR Model选择webui_768v_139.ckpt

    • 缩放系数配置为2。

  4. 单击生成,即可在右侧区域生成修复后的图片。image.png

  5. 生成的图片保存到了DSW实例的./stable-diffusion-webui/outputs/img2img-images/date文件夹中。您可以在DSW的Notebook选项卡中,右键单击图片文件并单击Download,即可将图片下载到本地。

方式三:局部重绘

以下参数配置仅为示例说明,您可以根据实际场景调整参数值。

  1. 选择基模型,并在图生图选项卡中输入提示词(Prompt),例如:raw photo,a chinese woman,happy,high quality,high detailimage.png

  2. 局部重绘选项卡中,根据界面提示上传待修复的图片,并绘制掩码。image.png

  3. 请参考以下内容来设置相关参数。image.png

    • 选中面部修复进行人脸重绘。

    • Resize by页签,通过配置Scale来调整图片缩放比例。

    • 降低重绘幅度,取值范围为0.01~0.1。

  4. (可选)设置ControlNet进行局部可控的重绘。image.png

    • 可选多个ControlNet进行设置。

    • 选中启用后,当前单元生效。

  5. 单击生成,即可在右侧区域生成修复后的图片。image.png

  6. 生成的图片保存到了DSW实例的./stable-diffusion-webui/outputs/img2img-images/date文件夹中。您可以在DSW的Notebook选项卡中,右键单击图片文件并单击Download,即可将图片下载到本地。