Add files

.gitattributes

@@ -1,3 +1,4 @@
+*.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

@@ -0,0 +1,3 @@
+[submodule "stylegan3"]
+	path = stylegan3
+	url = https://github.com/NVlabs/stylegan3

app.py

@@ -0,0 +1,196 @@
+#!/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/NVlabs/stylegan3'
+TITLE = 'StyleGAN2'
+DESCRIPTION = f'This is a demo for {ORIGINAL_REPO_URL}.'
+SAMPLE_IMAGE_DIR = 'https://huggingface.co/spaces/hysts/StyleGAN2/resolve/main/samples'
+ARTICLE = f'''## Generated images
+- truncation: 0.7
+### CIFAR-10
+- size: 32x32
+- class index: 0-9
+- seed: 0-9
+![CIFAR-10 samples]({SAMPLE_IMAGE_DIR}/cifar10.jpg)
+### AFHQ-Cat
+- size: 512x512
+- seed: 0-99
+![AFHQ-Cat samples]({SAMPLE_IMAGE_DIR}/afhq-cat.jpg)
+### AFHQ-Dog
+- size: 512x512
+- seed: 0-99
+![AFHQ-Dog samples]({SAMPLE_IMAGE_DIR}/afhq-dog.jpg)
+### AFHQ-Wild
+- size: 512x512
+- seed: 0-99
+![AFHQ-Wild samples]({SAMPLE_IMAGE_DIR}/afhq-wild.jpg)
+### AFHQv2
+- size: 512x512
+- seed: 0-99
+![AFHQv2 samples]({SAMPLE_IMAGE_DIR}/afhqv2.jpg)
+### LSUN-Dog
+- size: 256x256
+- seed: 0-99
+![LSUN-Dog samples]({SAMPLE_IMAGE_DIR}/lsun-dog.jpg)
+### BreCaHAD
+- size: 512x512
+- seed: 0-99
+![BreCaHAD samples]({SAMPLE_IMAGE_DIR}/brecahad.jpg)
+### CelebA-HQ
+- size: 256x256
+- seed: 0-99
+![CelebA-HQ samples]({SAMPLE_IMAGE_DIR}/celebahq.jpg)
+### FFHQ
+- size: 1024x1024
+- seed: 0-99
+![FFHQ samples]({SAMPLE_IMAGE_DIR}/ffhq.jpg)
+### FFHQ-U
+- size: 1024x1024
+- seed: 0-99
+![FFHQ-U samples]({SAMPLE_IMAGE_DIR}/ffhq-u.jpg)
+### MetFaces
+- size: 1024x1024
+- seed: 0-99
+![MetFaces samples]({SAMPLE_IMAGE_DIR}/metfaces.jpg)
+### MetFaces-U
+- size: 1024x1024
+- seed: 0-99
+![MetFaces-U samples]({SAMPLE_IMAGE_DIR}/metfaces-u.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, class_index: int, 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)
+    class_index = round(class_index)
+    class_index = min(max(0, class_index), model.c_dim - 1)
+    class_index = torch.tensor(class_index, dtype=torch.long)
+    if class_index >= 0:
+        label[:, class_index] = 1
+
+    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(file_name: str, device: torch.device) -> nn.Module:
+    path = hf_hub_download('hysts/StyleGAN2',
+                           f'models/{file_name}',
+                           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 = {
+        'AFHQ-Cat-512': 'stylegan2-afhqcat-512x512.pkl',
+        'AFHQ-Dog-512': 'stylegan2-afhqdog-512x512.pkl',
+        'AFHQv2-512': 'stylegan2-afhqv2-512x512.pkl',
+        'AFHQ-Wild-512': 'stylegan2-afhqwild-512x512.pkl',
+        'BreCaHAD-512': 'stylegan2-brecahad-512x512.pkl',
+        'CelebA-HQ-256': 'stylegan2-celebahq-256x256.pkl',
+        'CIFAR-10': 'stylegan2-cifar10-32x32.pkl',
+        'FFHQ-256': 'stylegan2-ffhq-256x256.pkl',
+        'FFHQ-512': 'stylegan2-ffhq-512x512.pkl',
+        'FFHQ-1024': 'stylegan2-ffhq-1024x1024.pkl',
+        'FFHQ-U-256': 'stylegan2-ffhqu-256x256.pkl',
+        'FFHQ-U-1024': 'stylegan2-ffhqu-1024x1024.pkl',
+        'LSUN-Dog-256': 'stylegan2-lsundog-256x256.pkl',
+        'MetFaces-1024': 'stylegan2-metfaces-1024x1024.pkl',
+        'MetFaces-U-1024': 'stylegan2-metfacesu-1024x1024.pkl',
+    }
+
+    model_dict = {
+        name: load_model(file_name, device)
+        for name, file_name in model_names.items()
+    }
+
+    func = functools.partial(generate_image,
+                             model_dict=model_dict,
+                             device=device)
+    func = functools.update_wrapper(func, generate_image)
+
+    gr.Interface(
+        func,
+        [
+            gr.inputs.Radio(list(model_names.keys()),
+                            type='value',
+                            default='FFHQ-1024',
+                            label='Model'),
+            gr.inputs.Number(default=0, label='Class index'),
+            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

@@ -0,0 +1,5 @@
+numpy==1.22.3
+Pillow==9.0.1
+scipy==1.8.0
+torch==1.11.0
+torchvision==0.12.0

stylegan3

@@ -0,0 +1 @@
+Subproject commit a5a69f58294509598714d1e88c9646c3d7c6ec94