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Configuration error
Download models/FeatureStyleEncoder/FSencoder.py from miguelmuzo/HairSwapModel: direct link, hf CLI and curl.
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- Download file 1.6 kB
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https://huggingface.co/spaces/miguelmuzo/HairSwapModel/resolve/main/models/FeatureStyleEncoder/FSencoder.py
- Command line
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hf download hf://spaces/miguelmuzo/HairSwapModel/models/FeatureStyleEncoder/FSencoder.py
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curl -L -o FSencoder.py https://huggingface.co/spaces/miguelmuzo/HairSwapModel/resolve/main/models/FeatureStyleEncoder/FSencoder.py
1.6 kB
| from argparse import Namespace | |
| import glob | |
| import os | |
| import numpy as np | |
| import torch | |
| import torch.nn as nn | |
| import torch.nn.functional as F | |
| import torch.utils.data as data | |
| import yaml | |
| import sys | |
| current_dir = os.path.abspath(os.path.dirname(__file__)) | |
| sys.path.insert(0, current_dir) | |
| from PIL import Image | |
| from tqdm import tqdm | |
| from torchvision import transforms, utils | |
| from trainer import * | |
| torch.backends.cudnn.enabled = True | |
| torch.backends.cudnn.deterministic = True | |
| torch.backends.cudnn.benchmark = True | |
| # torch.autograd.set_detect_anomaly(True) | |
| Image.MAX_IMAGE_PIXELS = None | |
| opts = Namespace(config='001', pretrained_model_path='pretrained_models/FeatureStyleEncoder/143_enc.pth', stylegan_model_path=f'pretrained_models/FeatureStyleEncoder/psp_ffhq_encode.pt', arcface_model_path=f'pretrained_models/FeatureStyleEncoder/backbone.pth', parsing_model_path=f'pretrained_models/FeatureStyleEncoder/79999_iter.pth', log_path='./logs/', resume=False, checkpoint='', checkpoint_noiser='', multigpu=False, input_path='./test/', save_path='./') | |
| config = yaml.load(open(f'{current_dir}/configs/' + opts.config + '.yaml', 'r'), Loader=yaml.FullLoader) | |
| def get_trainer(device): | |
| # Initialize trainer | |
| trainer = Trainer(config, opts) | |
| trainer.initialize(opts.stylegan_model_path, opts.arcface_model_path, opts.parsing_model_path) | |
| trainer.to(device) | |
| # state_dict = torch.load(opts.pretrained_model_path)#os.path.join(opts.log_path, opts.config + '/checkpoint.pth')) | |
| trainer.enc.load_state_dict(torch.load(opts.pretrained_model_path)) | |
| trainer.enc.eval() | |
| return trainer |