Update

.pre-commit-config.yaml

@@ -1,36 +1,61 @@
 exclude: ^patch
 repos:
-- repo: https://github.com/pre-commit/pre-commit-hooks
-  rev: v4.2.0
-  hooks:
-  - id: check-executables-have-shebangs
-  - id: check-json
-  - id: check-merge-conflict
-  - id: check-shebang-scripts-are-executable
-  - id: check-toml
-  - id: check-yaml
-  - id: double-quote-string-fixer
-  - id: end-of-file-fixer
-  - id: mixed-line-ending
-    args: ['--fix=lf']
-  - id: requirements-txt-fixer
-  - id: trailing-whitespace
-- repo: https://github.com/myint/docformatter
-  rev: v1.4
-  hooks:
-  - id: docformatter
-    args: ['--in-place']
-- repo: https://github.com/pycqa/isort
-  rev: 5.12.0
-  hooks:
-    - id: isort
-- repo: https://github.com/pre-commit/mirrors-mypy
-  rev: v0.991
-  hooks:
-    - id: mypy
-      args: ['--ignore-missing-imports']
-- repo: https://github.com/google/yapf
-  rev: v0.32.0
-  hooks:
-  - id: yapf
-    args: ['--parallel', '--in-place']
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v4.6.0
+    hooks:
+      - id: check-executables-have-shebangs
+      - id: check-json
+      - id: check-merge-conflict
+      - id: check-shebang-scripts-are-executable
+      - id: check-toml
+      - id: check-yaml
+      - id: end-of-file-fixer
+      - id: mixed-line-ending
+        args: ["--fix=lf"]
+      - id: requirements-txt-fixer
+      - id: trailing-whitespace
+  - repo: https://github.com/myint/docformatter
+    rev: v1.7.5
+    hooks:
+      - id: docformatter
+        args: ["--in-place"]
+  - repo: https://github.com/pycqa/isort
+    rev: 5.13.2
+    hooks:
+      - id: isort
+        args: ["--profile", "black"]
+  - repo: https://github.com/pre-commit/mirrors-mypy
+    rev: v1.10.0
+    hooks:
+      - id: mypy
+        args: ["--ignore-missing-imports"]
+        additional_dependencies:
+          [
+            "types-python-slugify",
+            "types-requests",
+            "types-PyYAML",
+            "types-pytz",
+          ]
+  - repo: https://github.com/psf/black
+    rev: 24.4.2
+    hooks:
+      - id: black
+        language_version: python3.10
+        args: ["--line-length", "119"]
+  - repo: https://github.com/kynan/nbstripout
+    rev: 0.7.1
+    hooks:
+      - id: nbstripout
+        args:
+          [
+            "--extra-keys",
+            "metadata.interpreter metadata.kernelspec cell.metadata.pycharm",
+          ]
+  - repo: https://github.com/nbQA-dev/nbQA
+    rev: 1.8.5
+    hooks:
+      - id: nbqa-black
+      - id: nbqa-pyupgrade
+        args: ["--py37-plus"]
+      - id: nbqa-isort
+        args: ["--float-to-top"]

README.md

@@ -4,7 +4,7 @@ emoji: 📊
 colorFrom: red
 colorTo: yellow
 sdk: gradio
-sdk_version: 3.36.1
+sdk_version: 4.36.1
 app_file: app.py
 pinned: false
 suggested_hardware: t4-small

app.py

@@ -15,29 +15,25 @@ import torch
 import torch.nn as nn
 from huggingface_hub import hf_hub_download
 
-if os.environ.get('SYSTEM') == 'spaces':
-    with open('patch') as f:
-        subprocess.run(shlex.split('patch -p1'),
-                       cwd='stylegan2-pytorch',
-                       stdin=f)
+if os.environ.get("SYSTEM") == "spaces":
+    with open("patch") as f:
+        subprocess.run(shlex.split("patch -p1"), cwd="stylegan2-pytorch", stdin=f)
     if not torch.cuda.is_available():
-        with open('patch-cpu') as f:
-            subprocess.run(shlex.split('patch -p1'),
-                           cwd='stylegan2-pytorch',
-                           stdin=f)
+        with open("patch-cpu") as f:
+            subprocess.run(shlex.split("patch -p1"), cwd="stylegan2-pytorch", stdin=f)
 
-sys.path.insert(0, 'stylegan2-pytorch')
+sys.path.insert(0, "stylegan2-pytorch")
 
 from model import Generator
 
-DESCRIPTION = '''# [TADNE](https://thisanimedoesnotexist.ai/) (This Anime Does Not Exist) interpolation
+DESCRIPTION = """# [TADNE](https://thisanimedoesnotexist.ai/) (This Anime Does Not Exist) interpolation
 
 Related Apps:
 - [TADNE](https://huggingface.co/spaces/hysts/TADNE)
 - [TADNE Image Viewer](https://huggingface.co/spaces/hysts/TADNE-image-viewer)
 - [TADNE Image Selector](https://huggingface.co/spaces/hysts/TADNE-image-selector)
 - [TADNE Image Search with DeepDanbooru](https://huggingface.co/spaces/hysts/TADNE-image-search-with-DeepDanbooru)
-'''
+"""
 
 MAX_SEED = np.iinfo(np.int32).max
 
@@ -50,13 +46,12 @@ def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
 
 def load_model(device: torch.device) -> nn.Module:
     model = Generator(512, 1024, 4, channel_multiplier=2)
-    path = hf_hub_download('public-data/TADNE',
-                           'models/aydao-anime-danbooru2019s-512-5268480.pt')
+    path = hf_hub_download("public-data/TADNE", "models/aydao-anime-danbooru2019s-512-5268480.pt")
     checkpoint = torch.load(path)
-    model.load_state_dict(checkpoint['g_ema'])
+    model.load_state_dict(checkpoint["g_ema"])
     model.eval()
     model.to(device)
-    model.latent_avg = checkpoint['latent_avg'].to(device)
+    model.latent_avg = checkpoint["latent_avg"].to(device)
     with torch.inference_mode():
         z = torch.zeros((1, model.style_dim)).to(device)
         model([z], truncation=0.7, truncation_latent=model.latent_avg)
@@ -64,26 +59,27 @@ def load_model(device: torch.device) -> nn.Module:
 
 
 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()
+    return torch.from_numpy(np.random.RandomState(seed).randn(1, z_dim)).to(device).float()
 
 
 @torch.inference_mode()
-def generate_image(model: nn.Module, z: torch.Tensor, truncation_psi: float,
-                   randomize_noise: bool) -> np.ndarray:
-    out, _ = model([z],
-                   truncation=truncation_psi,
-                   truncation_latent=model.latent_avg,
-                   randomize_noise=randomize_noise)
+def generate_image(model: nn.Module, z: torch.Tensor, truncation_psi: float, randomize_noise: bool) -> np.ndarray:
+    out, _ = model([z], truncation=truncation_psi, truncation_latent=model.latent_avg, randomize_noise=randomize_noise)
     out = (out.permute(0, 2, 3, 1) * 127.5 + 128).clamp(0, 255).to(torch.uint8)
     return out[0].cpu().numpy()
 
 
 @torch.inference_mode()
-def generate_interpolated_images(seed0: int, seed1: int, num_intermediate: int,
-                                 psi0: float, psi1: float,
-                                 randomize_noise: bool, model: nn.Module,
-                                 device: torch.device) -> list[np.ndarray]:
+def generate_interpolated_images(
+    seed0: int,
+    seed1: int,
+    num_intermediate: int,
+    psi0: float,
+    psi1: float,
+    randomize_noise: bool,
+    model: nn.Module,
+    device: torch.device,
+) -> list[np.ndarray]:
     seed0 = int(np.clip(seed0, 0, MAX_SEED))
     seed1 = int(np.clip(seed1, 0, MAX_SEED))
 
@@ -101,11 +97,9 @@ def generate_interpolated_images(seed0: int, seed1: int, num_intermediate: int,
     return res
 
 
-device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
+device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 model = load_model(device)
-fn = functools.partial(generate_interpolated_images,
-                       model=model,
-                       device=device)
+fn = functools.partial(generate_interpolated_images, model=model, device=device)
 
 examples = [
     [29703, 55376, 3, 0.7, 0.7, False],
@@ -115,41 +109,25 @@ examples = [
     [55376, 55376, 5, 0.3, 1.3, False],
 ]
 
-with gr.Blocks(css='style.css') as demo:
+with gr.Blocks(css="style.css") as demo:
     gr.Markdown(DESCRIPTION)
     with gr.Row():
         with gr.Column():
-            seed_1 = gr.Slider(label='Seed 1',
-                               minimum=0,
-                               maximum=MAX_SEED,
-                               step=1,
-                               value=29703)
-            seed_2 = gr.Slider(label='Seed 2',
-                               minimum=0,
-                               maximum=MAX_SEED,
-                               step=1,
-                               value=55376)
+            seed_1 = gr.Slider(label="Seed 1", minimum=0, maximum=MAX_SEED, step=1, value=29703)
+            seed_2 = gr.Slider(label="Seed 2", minimum=0, maximum=MAX_SEED, step=1, value=55376)
             num_intermediate_frames = gr.Slider(
-                label='Number of Intermediate Frames',
+                label="Number of Intermediate Frames",
                 minimum=1,
                 maximum=21,
                 step=1,
                 value=3,
             )
-            psi_1 = gr.Slider(label='Truncation psi 1',
-                              minimum=0,
-                              maximum=2,
-                              step=0.05,
-                              value=0.7)
-            psi_2 = gr.Slider(label='Truncation psi 2',
-                              minimum=0,
-                              maximum=2,
-                              step=0.05,
-                              value=0.7)
-            randomize_noise = gr.Checkbox(label='Randomize Noise', value=False)
-            run_button = gr.Button('Run')
+            psi_1 = gr.Slider(label="Truncation psi 1", minimum=0, maximum=2, step=0.05, value=0.7)
+            psi_2 = gr.Slider(label="Truncation psi 2", minimum=0, maximum=2, step=0.05, value=0.7)
+            randomize_noise = gr.Checkbox(label="Randomize Noise", value=False)
+            run_button = gr.Button("Run")
         with gr.Column():
-            result = gr.Gallery(label='Output')
+            result = gr.Gallery(label="Output")
 
     inputs = [
         seed_1,
@@ -164,12 +142,12 @@ with gr.Blocks(css='style.css') as demo:
         inputs=inputs,
         outputs=result,
         fn=fn,
-        cache_examples=os.getenv('CACHE_EXAMPLES') == '1',
+        cache_examples=os.getenv("CACHE_EXAMPLES") == "1",
     )
     run_button.click(
         fn=fn,
         inputs=inputs,
         outputs=result,
-        api_name='run',
+        api_name="run",
     )
 demo.queue(max_size=10).launch()

requirements.txt

@@ -1,4 +1,4 @@
-numpy==1.23.5
-Pillow==10.0.0
+numpy==1.26.4
+Pillow==10.3.0
 torch==2.0.1
 torchvision==0.15.2

style.css

@@ -1,7 +1,11 @@
 h1 {
   text-align: center;
+  display: block;
 }
 
 #duplicate-button {
   margin: auto;
+  color: #fff;
+  background: #1565c0;
+  border-radius: 100vh;
 }