Add files
Browse files- .gitattributes +1 -0
- .gitmodules +3 -0
- app.py +179 -0
- requirements.txt +5 -0
- samples/afhqv2.jpg +3 -0
- samples/ffhq-u.jpg +3 -0
- samples/ffhq.jpg +3 -0
- samples/metfaces-u.jpg +3 -0
- samples/metfaces.jpg +3 -0
- stylegan3 +1 -0
.gitattributes
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*.7z filter=lfs diff=lfs merge=lfs -text
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*.arrow filter=lfs diff=lfs merge=lfs -text
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*.bin filter=lfs diff=lfs merge=lfs -text
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*.jpg filter=lfs diff=lfs merge=lfs -text
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*.7z filter=lfs diff=lfs merge=lfs -text
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*.arrow filter=lfs diff=lfs merge=lfs -text
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*.bin filter=lfs diff=lfs merge=lfs -text
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.gitmodules
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[submodule "stylegan3"]
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path = stylegan3
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url = https://github.com/NVlabs/stylegan3
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app.py
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#!/usr/bin/env python
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from __future__ import annotations
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import argparse
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import functools
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import os
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import pickle
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import sys
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sys.path.insert(0, 'stylegan3')
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import gradio as gr
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import numpy as np
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import torch
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import torch.nn as nn
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from huggingface_hub import hf_hub_download
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ORIGINAL_REPO_URL = 'https://github.com/NVlabs/stylegan3'
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TITLE = 'NVlabs/stylegan3'
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DESCRIPTION = f'This is a demo for {ORIGINAL_REPO_URL}.'
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SAMPLE_IMAGE_DIR = 'https://huggingface.co/spaces/hysts/StyleGAN3/resolve/main/samples'
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ARTICLE = f'''## Generated images
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- truncation: 0.7
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### AFHQv2
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- size: 512x512
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- seed: 0-99
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![AFHQv2 samples]({SAMPLE_IMAGE_DIR}/afhqv2.jpg)
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### FFHQ
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- size: 1024x1024
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- seed: 0-99
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![FFHQ samples]({SAMPLE_IMAGE_DIR}/ffhq.jpg)
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### FFHQ-U
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- size: 1024x1024
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- seed: 0-99
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![FFHQ-U samples]({SAMPLE_IMAGE_DIR}/ffhq-u.jpg)
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### MetFaces
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- size: 1024x1024
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- seed: 0-99
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![MetFaces samples]({SAMPLE_IMAGE_DIR}/metfaces.jpg)
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### MetFaces-U
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- size: 1024x1024
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- seed: 0-99
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![MetFaces-U samples]({SAMPLE_IMAGE_DIR}/metfaces-u.jpg)
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'''
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TOKEN = os.environ['TOKEN']
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def parse_args() -> argparse.Namespace:
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parser = argparse.ArgumentParser()
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parser.add_argument('--device', type=str, default='cpu')
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parser.add_argument('--theme', type=str)
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parser.add_argument('--live', action='store_true')
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parser.add_argument('--share', action='store_true')
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parser.add_argument('--port', type=int)
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parser.add_argument('--disable-queue',
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dest='enable_queue',
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action='store_false')
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parser.add_argument('--allow-flagging', type=str, default='never')
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parser.add_argument('--allow-screenshot', action='store_true')
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return parser.parse_args()
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def make_transform(translate: tuple[float, float], angle: float) -> np.ndarray:
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mat = np.eye(3)
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sin = np.sin(angle / 360 * np.pi * 2)
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cos = np.cos(angle / 360 * np.pi * 2)
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mat[0][0] = cos
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mat[0][1] = sin
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mat[0][2] = translate[0]
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mat[1][0] = -sin
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mat[1][1] = cos
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mat[1][2] = translate[1]
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return mat
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def generate_z(z_dim: int, seed: int, device: torch.device) -> torch.Tensor:
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return torch.from_numpy(np.random.RandomState(seed).randn(
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1, z_dim)).to(device)
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@torch.inference_mode()
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def generate_image(model_name: str, seed: int, truncation_psi: float,
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tx: float, ty: float, angle: float,
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model_dict: dict[str, nn.Module],
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device: torch.device) -> np.ndarray:
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model = model_dict[model_name]
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seed = int(np.clip(seed, 0, np.iinfo(np.uint32).max))
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z = generate_z(model.z_dim, seed, device)
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label = torch.zeros([1, model.c_dim], device=device)
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mat = make_transform((tx, ty), angle)
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mat = np.linalg.inv(mat)
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model.synthesis.input.transform.copy_(torch.from_numpy(mat))
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out = model(z, label, truncation_psi=truncation_psi)
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out = (out.permute(0, 2, 3, 1) * 127.5 + 128).clamp(0, 255).to(torch.uint8)
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return out[0].cpu().numpy()
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def load_model(file_name: str, device: torch.device) -> nn.Module:
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path = hf_hub_download('hysts/StyleGAN3',
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f'models/{file_name}',
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use_auth_token=TOKEN)
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with open(path, 'rb') as f:
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model = pickle.load(f)['G_ema']
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model.eval()
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model.to(device)
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with torch.inference_mode():
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z = torch.zeros((1, model.z_dim)).to(device)
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label = torch.zeros([1, model.c_dim], device=device)
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model(z, label)
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return model
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def main():
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gr.close_all()
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args = parse_args()
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device = torch.device(args.device)
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model_names = {
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'AFHQv2-512-R': 'stylegan3-r-afhqv2-512x512.pkl',
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'FFHQ-1024-R': 'stylegan3-r-ffhq-1024x1024.pkl',
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'FFHQ-U-256-R': 'stylegan3-r-ffhqu-256x256.pkl',
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'FFHQ-U-1024-R': 'stylegan3-r-ffhqu-1024x1024.pkl',
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'MetFaces-1024-R': 'stylegan3-r-metfaces-1024x1024.pkl',
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'MetFaces-U-1024-R': 'stylegan3-r-metfacesu-1024x1024.pkl',
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'AFHQv2-512-T': 'stylegan3-t-afhqv2-512x512.pkl',
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'FFHQ-1024-T': 'stylegan3-t-ffhq-1024x1024.pkl',
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'FFHQ-U-256-T': 'stylegan3-t-ffhqu-256x256.pkl',
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'FFHQ-U-1024-T': 'stylegan3-t-ffhqu-1024x1024.pkl',
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'MetFaces-1024-T': 'stylegan3-t-metfaces-1024x1024.pkl',
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'MetFaces-U-1024-T': 'stylegan3-t-metfacesu-1024x1024.pkl',
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}
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model_dict = {
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name: load_model(file_name, device)
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for name, file_name in model_names.items()
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}
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func = functools.partial(generate_image,
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model_dict=model_dict,
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device=device)
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func = functools.update_wrapper(func, generate_image)
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gr.Interface(
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func,
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[
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gr.inputs.Radio(list(model_names.keys()),
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type='value',
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default='FFHQ-1024-R',
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label='Model'),
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gr.inputs.Number(default=0, label='Seed'),
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gr.inputs.Slider(
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0, 2, step=0.05, default=0.7, label='Truncation psi'),
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gr.inputs.Slider(-1, 1, step=0.05, default=0, label='Translate X'),
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gr.inputs.Slider(-1, 1, step=0.05, default=0, label='Translate Y'),
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gr.inputs.Slider(-180, 180, step=5, default=0, label='Angle'),
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],
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gr.outputs.Image(type='numpy', label='Output'),
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theme=args.theme,
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title=TITLE,
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description=DESCRIPTION,
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article=ARTICLE,
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allow_screenshot=args.allow_screenshot,
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allow_flagging=args.allow_flagging,
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live=args.live,
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).launch(
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enable_queue=args.enable_queue,
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server_port=args.port,
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share=args.share,
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)
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if __name__ == '__main__':
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main()
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requirements.txt
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numpy==1.22.3
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Pillow==9.0.1
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scipy==1.8.0
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torch==1.11.0
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torchvision==0.12.0
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samples/afhqv2.jpg
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Git LFS Details
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samples/ffhq-u.jpg
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Git LFS Details
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samples/ffhq.jpg
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Git LFS Details
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samples/metfaces-u.jpg
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Git LFS Details
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samples/metfaces.jpg
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Git LFS Details
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stylegan3
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Subproject commit a5a69f58294509598714d1e88c9646c3d7c6ec94
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