Add files

app.py

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+#!/usr/bin/env python
+
+from __future__ import annotations
+
+import functools
+import os
+import pickle
+import sys
+
+sys.path.insert(0, 'stylegan3')
+
+import gradio as gr
+import numpy as np
+import PIL.Image
+import torch
+from huggingface_hub import hf_hub_download
+
+MODEL_REPO = 'hysts/stylegan3-anime-face-exp001-model'
+MODEL_FILE_NAME = '006600.pkl'
+TOKEN = os.environ['TOKEN']
+
+DEFAULT_SEED = 3407851645
+
+TITLE = 'StyleGAN3 Anime Face Generation'
+
+
+def make_transform(translate: tuple[float, float], angle: float) -> np.ndarray:
+    mat = np.eye(3)
+    sin = np.sin(angle / 360 * np.pi * 2)
+    cos = np.cos(angle / 360 * np.pi * 2)
+    mat[0][0] = cos
+    mat[0][1] = sin
+    mat[0][2] = translate[0]
+    mat[1][0] = -sin
+    mat[1][1] = cos
+    mat[1][2] = translate[1]
+    return mat
+
+
+def generate_z(seed, device):
+    return torch.from_numpy(np.random.RandomState(seed).randn(1,
+                                                              512)).to(device)
+
+
+@torch.inference_mode()
+def generate_image(seed, truncation_psi, tx, ty, angle, model, device):
+    seed = int(np.clip(seed, 0, np.iinfo(np.uint32).max))
+    z = generate_z(seed, device)
+    c = torch.zeros(0).to(device)
+
+    mat = make_transform((tx, ty), angle)
+    mat = np.linalg.inv(mat)
+    model.synthesis.input.transform.copy_(torch.from_numpy(mat))
+
+    out = model(z, c, truncation_psi=truncation_psi)
+    out = (out.permute(0, 2, 3, 1) * 127.5 + 128).clamp(0, 255).to(torch.uint8)
+    return PIL.Image.fromarray(out[0].cpu().numpy(), 'RGB')
+
+
+def load_model(device):
+    path = hf_hub_download(MODEL_REPO, MODEL_FILE_NAME, use_auth_token=TOKEN)
+    with open(path, 'rb') as f:
+        model = pickle.load(f)
+    model.eval()
+    model.to(device)
+    with torch.inference_mode():
+        z = torch.zeros((1, 512)).to(device)
+        c = torch.zeros(0).to(device)
+        model(z, c)
+    return model
+
+
+def main():
+    device = torch.device('cpu')
+
+    model = load_model(device)
+    func = functools.partial(generate_image, model=model, device=device)
+    func = functools.update_wrapper(func, generate_image)
+
+    gr.Interface(
+        func,
+        [
+            gr.inputs.Number(default=DEFAULT_SEED, label='Seed'),
+            gr.inputs.Slider(
+                0, 2, step=0.05, default=0.7, label='Truncation psi'),
+            gr.inputs.Slider(-1, 1, step=0.05, default=0, label='Translate X'),
+            gr.inputs.Slider(-1, 1, step=0.05, default=0, label='Translate Y'),
+            gr.inputs.Slider(-180, 180, step=5, default=0, label='Angle'),
+        ],
+        gr.outputs.Image(type='pil', label='Output'),
+        title=TITLE,
+        enable_queue=True,
+        allow_screenshot=False,
+        allow_flagging=False,
+    ).launch()
+
+
+if __name__ == '__main__':
+    main()

requirements.txt

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+numpy>=1.21.4
+Pillow>=8.3.1
+scipy>=1.7.2
+torch>=1.10.0