Add files

.gitattributes

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+*.jpg filter=lfs diff=lfs merge=lfs -text
 *.7z filter=lfs diff=lfs merge=lfs -text
 *.arrow filter=lfs diff=lfs merge=lfs -text
 *.bin filter=lfs diff=lfs merge=lfs -text

.gitmodules

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+[submodule "stylegan3"]
+	path = stylegan3
+	url = https://github.com/NVlabs/stylegan3

app.py

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+#!/usr/bin/env python
+
+from __future__ import annotations
+
+import argparse
+import functools
+import os
+import pickle
+import sys
+
+sys.path.insert(0, 'stylegan3')
+
+import gradio as gr
+import numpy as np
+import torch
+import torch.nn as nn
+from huggingface_hub import hf_hub_download
+
+ORIGINAL_REPO_URL = 'https://github.com/self-distilled-stylegan/self-distilled-internet-photos'
+TITLE = 'Self-Distilled StyleGAN'
+DESCRIPTION = f'This is a demo for models provided in {ORIGINAL_REPO_URL}.'
+SAMPLE_IMAGE_DIR = 'https://huggingface.co/spaces/hysts/Self-Distilled-StyleGAN/resolve/main/samples'
+ARTICLE = f'''## Generated images
+- truncation: 0.7
+### Dogs
+- size: 1024x1024
+- seed: 0-99
+![Dogs]({SAMPLE_IMAGE_DIR}/dogs.jpg)
+### Elephants
+- size: 512x512
+- seed: 0-99
+![Elephants]({SAMPLE_IMAGE_DIR}/elephants.jpg)
+### Horses
+- size: 256x256
+- seed: 0-99
+![Horses]({SAMPLE_IMAGE_DIR}/horses.jpg)
+### Bicycles
+- size: 256x256
+- seed: 0-99
+![Bicycles]({SAMPLE_IMAGE_DIR}/bicycles.jpg)
+### Lions
+- size: 512x512
+- seed: 0-99
+![Lions]({SAMPLE_IMAGE_DIR}/lions.jpg)
+### Giraffes
+- size: 512x512
+- seed: 0-99
+![Giraffes]({SAMPLE_IMAGE_DIR}/giraffes.jpg)
+### Parrots
+- size: 512x512
+- seed: 0-99
+![Parrots]({SAMPLE_IMAGE_DIR}/parrots.jpg)
+'''
+
+TOKEN = os.environ['TOKEN']
+
+
+def parse_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--device', type=str, default='cpu')
+    parser.add_argument('--theme', type=str)
+    parser.add_argument('--live', action='store_true')
+    parser.add_argument('--share', action='store_true')
+    parser.add_argument('--port', type=int)
+    parser.add_argument('--disable-queue',
+                        dest='enable_queue',
+                        action='store_false')
+    parser.add_argument('--allow-flagging', type=str, default='never')
+    parser.add_argument('--allow-screenshot', action='store_true')
+    return parser.parse_args()
+
+
+def generate_z(z_dim: int, seed: int, device: torch.device) -> torch.Tensor:
+    return torch.from_numpy(np.random.RandomState(seed).randn(
+        1, z_dim)).to(device).float()
+
+
+@torch.inference_mode()
+def generate_image(model_name: str, seed: int, truncation_psi: float,
+                   model_dict: dict[str, nn.Module],
+                   device: torch.device) -> np.ndarray:
+    model = model_dict[model_name]
+    seed = int(np.clip(seed, 0, np.iinfo(np.uint32).max))
+
+    z = generate_z(model.z_dim, seed, device)
+    label = torch.zeros([1, model.c_dim], device=device)
+
+    out = model(z, label, truncation_psi=truncation_psi)
+    out = (out.permute(0, 2, 3, 1) * 127.5 + 128).clamp(0, 255).to(torch.uint8)
+    return out[0].cpu().numpy()
+
+
+def load_model(model_name: str, device: torch.device) -> nn.Module:
+    path = hf_hub_download('hysts/Self-Distilled-StyleGAN',
+                           f'models/{model_name}_pytorch.pkl',
+                           use_auth_token=TOKEN)
+    with open(path, 'rb') as f:
+        model = pickle.load(f)['G_ema']
+    model.eval()
+    model.to(device)
+    with torch.inference_mode():
+        z = torch.zeros((1, model.z_dim)).to(device)
+        label = torch.zeros([1, model.c_dim], device=device)
+        model(z, label)
+    return model
+
+
+def main():
+    gr.close_all()
+
+    args = parse_args()
+    device = torch.device(args.device)
+
+    model_names = [
+        'dogs_1024',
+        'elephants_512',
+        'horses_256',
+        'bicycles_256',
+        'lions_512',
+        'giraffes_512',
+        'parrots_512',
+    ]
+
+    model_dict = {name: load_model(name, device) for name in model_names}
+
+    func = functools.partial(generate_image,
+                             model_dict=model_dict,
+                             device=device)
+    func = functools.update_wrapper(func, generate_image)
+
+    gr.Interface(
+        func,
+        [
+            gr.inputs.Radio(
+                model_names, type='value', default='dogs_1024', label='Model'),
+            gr.inputs.Number(default=0, label='Seed'),
+            gr.inputs.Slider(
+                0, 2, step=0.05, default=0.7, label='Truncation psi'),
+        ],
+        gr.outputs.Image(type='numpy', label='Output'),
+        title=TITLE,
+        description=DESCRIPTION,
+        article=ARTICLE,
+        theme=args.theme,
+        allow_screenshot=args.allow_screenshot,
+        allow_flagging=args.allow_flagging,
+        live=args.live,
+    ).launch(
+        enable_queue=args.enable_queue,
+        server_port=args.port,
+        share=args.share,
+    )
+
+
+if __name__ == '__main__':
+    main()

requirements.txt

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+numpy==1.22.3
+Pillow==9.0.1
+scipy==1.8.0
+torch==1.11.0
+torchvision==0.12.0

stylegan3

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+Subproject commit a5a69f58294509598714d1e88c9646c3d7c6ec94