text stringlengths 1 93.6k |
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See the License for the specific language governing permissions and
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limitations under the License.
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"""
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import os
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import sys
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from argparse import ArgumentParser
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from pathlib import Path
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sys.path.append('third_party/stylegan2_ada_pytorch')
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from reconstruct.alpha_projector import AlphaProjector
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from utils import io_utils, image_ops
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from utils.data_utils import PersonalizedDataset
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from utils.io_utils import load_latents
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from utils.image_ops import Degradation
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import torch
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import numpy as np
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torch.manual_seed(2)
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np.random.seed(2)
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def project(args):
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dataset = PersonalizedDataset(args.images_dir,
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mask_dir=args.mask_dir)
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anchors = load_latents(args.anchor_dir, to_w=True)
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generator = io_utils.load_net(args.generator_path)
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if args.mask_dir is not None:
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deg_func = Degradation.hole
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elif args.sr_factor is not None:
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deg_func = lambda x, **kwargs: Degradation.downsample(x, args.sr_factor)
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else:
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deg_func = lambda x, **kwargs: x
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alpha_projector = AlphaProjector(args.device, generator,
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args.debug_output_dir, args.is_wplus,
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anchors, deg_func,
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beta=args.beta)
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for sample in dataset:
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sample.img = deg_func(sample.img, mask=sample.mask)
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sample.save_input(args.output_dir)
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sample = alpha_projector.reconstruct(sample)
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if sample.mask is not None:
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blended_recon = image_ops.blend(sample.img, sample.recon_img, sample.mask)
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sample.set(recon_img=blended_recon)
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sample.save_latent(args.output_dir)
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sample.save_recon(args.output_dir)
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# TODO(3): SR blending, face segmenetation model?
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def parse_args(raw_args=None):
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parser = ArgumentParser('Projection arguments')
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parser.add_argument('--device', type=str, default="0")
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parser.add_argument('--verbose', type=io_utils.str2bool, default="True")
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parser.add_argument('--images_dir', type=io_utils.existing_path, required=True)
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parser.add_argument('--output_dir', type=Path, required=True)
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parser.add_argument('--generator_path', type=io_utils.existing_path, required=True)
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parser.add_argument('--anchor_dir', type=io_utils.existing_path, required=True)
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parser.add_argument('--beta', type=io_utils.float_or_none, default=0.03,
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help='Controls the maximal allowed dilation of the personalized space.'
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'Pass None to not restrict dilation.')
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parser.add_argument('--is_wplus', type=io_utils.str2bool, default="True")
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parser.add_argument('--mask_dir', type=io_utils.existing_path)
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parser.add_argument('--sr_factor', type=float)
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# TODO(2): support W/W+ projection
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args = parser.parse_args(raw_args)
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return args
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def process_args(args):
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os.environ['CUDA_VISIBLE_DEVICES'] = str(args.device)
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args.device = torch.device(f'cuda')
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args.output_dir.mkdir(exist_ok=True, parents=True)
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args.debug_output_dir = None
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if args.verbose:
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args.debug_output_dir = args.output_dir.joinpath('debug')
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args.debug_output_dir.mkdir(exist_ok=True, parents=True)
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if args.sr_factor is not None and args.sr_factor > 1:
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args.sr_factor = 1 / args.sr_factor
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return args
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