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on
Zero
Running
on
Zero
| # https://github.com/eladrich/pixel2style2pixel | |
| import torch | |
| from torch import nn | |
| from ldm.thirdp.psp.model_irse import Backbone | |
| class IDFeatures(nn.Module): | |
| def __init__(self, model_path): | |
| super(IDFeatures, self).__init__() | |
| print('Loading ResNet ArcFace') | |
| self.facenet = Backbone(input_size=112, num_layers=50, drop_ratio=0.6, mode='ir_se') | |
| self.facenet.load_state_dict(torch.load(model_path, map_location="cpu")) | |
| self.face_pool = torch.nn.AdaptiveAvgPool2d((112, 112)) | |
| self.facenet.eval() | |
| def forward(self, x, crop=False): | |
| # Not sure of the image range here | |
| if crop: | |
| x = torch.nn.functional.interpolate(x, (256, 256), mode="area") | |
| x = x[:, :, 35:223, 32:220] | |
| x = self.face_pool(x) | |
| x_feats = self.facenet(x) | |
| return x_feats | |