Python Barbershop实现照片换发型功能

目录

• 前言
• 环境部署
• 1、导入environment/environment.yaml环境
• 2、安装pytorch
• 3、依赖库安装
• 4、 cl.exe环境变量配置
• 5、模型下载
• 6、发型数据下载
• 7、代码调整
• 项目验证
• 1、预处理照片
• 2、换发型
• 总结

conda env create -f environment/environment.yaml

python align_face.py

(Barbershop) C:\Users\yi\PycharmProjects\Barbershop>python align_face.py
Downloading Shape Predictor
126.jpg: Number of faces detected: 1

python main.py --im_path1 126.png --im_path2 94.png --im_path3 94.png --sign realistic --smooth 5

(Barbershop) C:\Users\yi\PycharmProjects\Barbershop>python main.py --im_path1 126.png --im_path2 94.png --im_path3 94.png --sign realistic --smooth 5
Loading StyleGAN2 from checkpoint: pretrained_models/ffhq.pt
Setting up Perceptual loss...
Loading model from: C:\Users\yi\PycharmProjects\Barbershop\losses\lpips\weights\v0.1\vgg.pth
...[net-lin [vgg]] initialized
...Done
Number of images: 2
Images: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [10:39<00:00, 319.74s/it]
Number of images: 2
Images: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [02:08<00:00, 64.04s/it]
Loading StyleGAN2 from checkpoint: pretrained_models/ffhq.pt
C:\Users\yi\PycharmProjects\Barbershop\models\Alignment.py:97: UserWarning: where received a uint8 condition tensor. This behavior is deprecated and will be removed in a
 future version of PyTorch. Use a boolean condition instead. (Triggered internally at  ..\aten\src\ATen\native\TensorCompare.cpp:328.)
  new_target_final = torch.where(OB_region, torch.from_numpy(new_target_inpainted), new_target)
Align Step 2:   0%|                                                                                                                             | 0/100 [00:00<?, ?it/s]E
:\ProgramData\Anaconda3\envs\Barbershop\lib\site-packages\torch\nn\functional.py:3680: UserWarning: The default behavior for interpolate/upsample with float scale_factor
 changed in 1.6.0 to align with other frameworks/libraries, and now uses scale_factor directly, instead of relying on the computed output size. If you wish to restore th
e old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details.
  "The default behavior for interpolate/upsample with float scale_factor changed "
E:\ProgramData\Anaconda3\envs\Barbershop\lib\site-packages\torch\nn\functional.py:3635: UserWarning: Default upsampling behavior when mode=bicubic is changed to align_co
rners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
  "See the documentation of nn.Upsample for details.".format(mode)
Loading StyleGAN2 from checkpoint: pretrained_models/ffhq.pt
Setting up Perceptual loss...
Loading model from: C:\Users\yi\PycharmProjects\Barbershop\losses\masked_lpips\weights\v0.1\vgg.pth
...[net-lin [vgg]] initialized
...Done
Setting up Perceptual loss...
Loading model from: C:\Users\yi\PycharmProjects\Barbershop\losses\masked_lpips\weights\v0.1\vgg.pth
...[net-lin [vgg]] initialized
...Done