Update

.pre-commit-config.yaml

@@ -1,35 +1,60 @@
 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"]

.style.yapf

@@ -1,5 +0,0 @@
-[style]
-based_on_style = pep8
-blank_line_before_nested_class_or_def = false
-spaces_before_comment = 2
-split_before_logical_operator = true

.vscode/settings.json

@@ -0,0 +1,30 @@
+{
+    "editor.formatOnSave": true,
+    "files.insertFinalNewline": false,
+    "[python]": {
+        "editor.defaultFormatter": "ms-python.black-formatter",
+        "editor.formatOnType": true,
+        "editor.codeActionsOnSave": {
+            "source.organizeImports": "explicit"
+        }
+    },
+    "[jupyter]": {
+        "files.insertFinalNewline": false
+    },
+    "black-formatter.args": [
+        "--line-length=119"
+    ],
+    "isort.args": ["--profile", "black"],
+    "flake8.args": [
+        "--max-line-length=119"
+    ],
+    "ruff.lint.args": [
+        "--line-length=119"
+    ],
+    "notebook.output.scrolling": true,
+    "notebook.formatOnCellExecution": true,
+    "notebook.formatOnSave.enabled": true,
+        "notebook.codeActionsOnSave": {
+            "source.organizeImports": "explicit"
+        }
+}

app.py

@@ -12,16 +12,16 @@ import torch
 import torch.nn as nn
 from huggingface_hub import hf_hub_download
 
-sys.path.insert(0, 'StyleGAN-Human')
+sys.path.insert(0, "StyleGAN-Human")
 
-TITLE = 'StyleGAN-Human (Interpolation)'
-DESCRIPTION = 'https://github.com/stylegan-human/StyleGAN-Human'
+TITLE = "StyleGAN-Human (Interpolation)"
+DESCRIPTION = "https://github.com/stylegan-human/StyleGAN-Human"
 
 
 def load_model(file_name: str, device: torch.device) -> nn.Module:
-    path = hf_hub_download('public-data/StyleGAN-Human', f'models/{file_name}')
-    with open(path, 'rb') as f:
-        model = pickle.load(f)['G_ema']
+    path = hf_hub_download("public-data/StyleGAN-Human", f"models/{file_name}")
+    with open(path, "rb") as f:
+        model = pickle.load(f)["G_ema"]
     model.eval()
     model.to(device)
     with torch.inference_mode():
@@ -32,15 +32,13 @@ def load_model(file_name: str, 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_interpolated_images(seed0: int, psi0: float, seed1: int,
-                                 psi1: float, num_intermediate: int,
-                                 model: nn.Module,
-                                 device: torch.device) -> list[np.ndarray]:
+def generate_interpolated_images(
+    seed0: int, psi0: float, seed1: int, psi1: float, num_intermediate: int, model: nn.Module, device: torch.device
+) -> list[np.ndarray]:
     seed0 = int(np.clip(seed0, 0, np.iinfo(np.uint32).max))
     seed1 = int(np.clip(seed1, 0, np.iinfo(np.uint32).max))
 
@@ -57,51 +55,26 @@ def generate_interpolated_images(seed0: int, psi0: float, seed1: int,
     res = []
     for z, psi in zip(zs, psis):
         out = model(z, label, truncation_psi=psi, force_fp32=True)
-        out = (out.permute(0, 2, 3, 1) * 127.5 + 128).clamp(0, 255).to(
-            torch.uint8)
+        out = (out.permute(0, 2, 3, 1) * 127.5 + 128).clamp(0, 255).to(torch.uint8)
         out = out[0].cpu().numpy()
         res.append(out)
     return res
 
 
-device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
-model = load_model('stylegan_human_v2_1024.pkl', device)
-fn = functools.partial(generate_interpolated_images,
-                       model=model,
-                       device=device)
+device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
+model = load_model("stylegan_human_v2_1024.pkl", device)
+fn = functools.partial(generate_interpolated_images, model=model, device=device)
 
 gr.Interface(
     fn=fn,
     inputs=[
-        gr.Slider(label='Seed 1',
-                  minimum=0,
-                  maximum=100000,
-                  step=1,
-                  value=0,
-                  randomize=True),
-        gr.Slider(label='Truncation psi 1',
-                  minimum=0,
-                  maximum=2,
-                  step=0.05,
-                  value=0.7),
-        gr.Slider(label='Seed 2',
-                  minimum=0,
-                  maximum=100000,
-                  step=1,
-                  value=1,
-                  randomize=True),
-        gr.Slider(label='Truncation psi 2',
-                  minimum=0,
-                  maximum=2,
-                  step=0.05,
-                  value=0.7),
-        gr.Slider(label='Number of Intermediate Frames',
-                  minimum=0,
-                  maximum=21,
-                  step=1,
-                  value=7),
+        gr.Slider(label="Seed 1", minimum=0, maximum=100000, step=1, value=0, randomize=True),
+        gr.Slider(label="Truncation psi 1", minimum=0, maximum=2, step=0.05, value=0.7),
+        gr.Slider(label="Seed 2", minimum=0, maximum=100000, step=1, value=1, randomize=True),
+        gr.Slider(label="Truncation psi 2", minimum=0, maximum=2, step=0.05, value=0.7),
+        gr.Slider(label="Number of Intermediate Frames", minimum=0, maximum=21, step=1, value=7),
     ],
-    outputs=gr.Gallery(label='Output Images', type='numpy'),
+    outputs=gr.Gallery(label="Output Images", type="numpy"),
     title=TITLE,
     description=DESCRIPTION,
 ).queue(max_size=10).launch()