Update

.pre-commit-config.yaml

@@ -1,6 +1,6 @@
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.5.0
+    rev: v5.0.0
     hooks:
       - id: check-executables-have-shebangs
       - id: check-json
@@ -13,48 +13,21 @@ repos:
         args: ["--fix=lf"]
       - id: requirements-txt-fixer
       - id: trailing-whitespace
-  - repo: https://github.com/myint/docformatter
-    rev: v1.7.5
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: v0.9.9
     hooks:
-      - id: docformatter
-        args: ["--in-place"]
-  - repo: https://github.com/pycqa/isort
-    rev: 5.13.2
-    hooks:
-      - id: isort
-        args: ["--profile", "black"]
+      - id: ruff
+        args: ["--fix"]
+      - id: ruff-format
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.8.0
+    rev: v1.15.0
     hooks:
       - id: mypy
         args: ["--ignore-missing-imports"]
         additional_dependencies:
           [
             "types-python-slugify",
-            "types-requests",
-            "types-PyYAML",
             "types-pytz",
+            "types-PyYAML",
+            "types-requests",
           ]
-  - repo: https://github.com/psf/black
-    rev: 24.2.0
-    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: 1.7.1
-    hooks:
-      - id: nbqa-black
-      - id: nbqa-pyupgrade
-        args: ["--py37-plus"]
-      - id: nbqa-isort
-        args: ["--float-to-top"]

.python-version

@@ -0,0 +1 @@
+3.10

.vscode/extensions.json

@@ -0,0 +1,8 @@
+{
+    "recommendations": [
+        "ms-python.python",
+        "charliermarsh.ruff",
+        "streetsidesoftware.code-spell-checker",
+        "tamasfe.even-better-toml"
+    ]
+}

.vscode/settings.json

@@ -2,29 +2,16 @@
     "editor.formatOnSave": true,
     "files.insertFinalNewline": false,
     "[python]": {
-        "editor.defaultFormatter": "ms-python.black-formatter",
+        "editor.defaultFormatter": "charliermarsh.ruff",
         "editor.formatOnType": true,
         "editor.codeActionsOnSave": {
+            "source.fixAll.ruff": "explicit",
             "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"
-        }
+    "notebook.formatOnSave.enabled": true
 }

README.md

@@ -4,7 +4,7 @@ emoji: 🏃
 colorFrom: gray
 colorTo: purple
 sdk: gradio
-sdk_version: 4.36.1
+sdk_version: 5.20.0
 app_file: app.py
 pinned: false
 ---

app.py

@@ -1,7 +1,5 @@
 #!/usr/bin/env python
 
-from __future__ import annotations
-
 import os
 import pathlib
 import tarfile
@@ -21,21 +19,19 @@ def load_sample_image_paths() -> list[pathlib.Path]:
     if not image_dir.exists():
         path = huggingface_hub.hf_hub_download("public-data/sample-images-TADNE", "images.tar.gz", repo_type="dataset")
         with tarfile.open(path) as f:
-            f.extractall()
+            f.extractall()  # noqa: S202
     return sorted(image_dir.glob("*"))
 
 
 def load_model() -> tf.keras.Model:
     path = huggingface_hub.hf_hub_download("public-data/DeepDanbooru", "model-resnet_custom_v3.h5")
-    model = tf.keras.models.load_model(path)
-    return model
+    return tf.keras.models.load_model(path)
 
 
 def load_labels() -> list[str]:
     path = huggingface_hub.hf_hub_download("public-data/DeepDanbooru", "tags.txt")
-    with open(path) as f:
-        labels = [line.strip() for line in f.readlines()]
-    return labels
+    with pathlib.Path(path).open() as f:
+        return [line.strip() for line in f]
 
 
 model = load_model()
@@ -53,8 +49,8 @@ def predict(image: PIL.Image.Image, score_threshold: float) -> tuple[dict[str, f
     probs = probs.astype(float)
 
     indices = np.argsort(probs)[::-1]
-    result_all = dict()
-    result_threshold = dict()
+    result_all = {}
+    result_threshold = {}
     for index in indices:
         label = labels[index]
         prob = probs[index]
@@ -67,15 +63,15 @@ def predict(image: PIL.Image.Image, score_threshold: float) -> tuple[dict[str, f
 
 
 image_paths = load_sample_image_paths()
-examples = [[path.as_posix(), 0.5] for path in image_paths]
+examples = [[path, 0.5] for path in image_paths]
 
-with gr.Blocks(css="style.css") as demo:
+with gr.Blocks(css_paths="style.css") as demo:
     gr.Markdown(DESCRIPTION)
     with gr.Row():
         with gr.Column():
             image = gr.Image(label="Input", type="pil")
             score_threshold = gr.Slider(label="Score threshold", minimum=0, maximum=1, step=0.05, value=0.5)
-            run_button = gr.Button("Run")
+            run_button = gr.Button()
         with gr.Column():
             with gr.Tabs():
                 with gr.Tab(label="Output"):

pyproject.toml

@@ -0,0 +1,57 @@
+[project]
+name = "deepdanbooru-app"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = [
+    "deepdanbooru",
+    "gradio>=5.20.0",
+    "hf-transfer>=0.1.9",
+    "tensorflow>=2.18.0",
+]
+
+[tool.uv.sources]
+deepdanbooru = { git = "https://github.com/KichangKim/DeepDanbooru", rev = "v3-20200915-sgd-e30" }
+
+[tool.ruff]
+line-length = 119
+
+[tool.ruff.lint]
+select = ["ALL"]
+ignore = [
+    "COM812", # missing-trailing-comma
+    "D203",   # one-blank-line-before-class
+    "D213",   # multi-line-summary-second-line
+    "E501",   # line-too-long
+    "SIM117", # multiple-with-statements
+]
+extend-ignore = [
+    "D100",    # undocumented-public-module
+    "D101",    # undocumented-public-class
+    "D102",    # undocumented-public-method
+    "D103",    # undocumented-public-function
+    "D104",    # undocumented-public-package
+    "D105",    # undocumented-magic-method
+    "D107",    # undocumented-public-init
+    "EM101",   # raw-string-in-exception
+    "FBT001",  # boolean-type-hint-positional-argument
+    "FBT002",  # boolean-default-value-positional-argument
+    "PD901",   # pandas-df-variable-name
+    "PGH003",  # blanket-type-ignore
+    "PLR0913", # too-many-arguments
+    "PLR0915", # too-many-statements
+    "TRY003",  # raise-vanilla-args
+]
+unfixable = [
+    "F401", # unused-import
+]
+
+[tool.ruff.lint.pydocstyle]
+convention = "google"
+
+[tool.ruff.lint.per-file-ignores]
+"*.ipynb" = ["T201", "T203"]
+
+[tool.ruff.format]
+docstring-code-format = true

requirements.txt

@@ -1,4 +1,261 @@
-git+https://github.com/KichangKim/DeepDanbooru@v3-20200915-sgd-e30#egg=deepdanbooru
-gradio==4.36.1
+# This file was autogenerated by uv via the following command:
+#    uv pip compile pyproject.toml -o requirements.txt
+absl-py==2.1.0
+    # via
+    #   keras
+    #   tensorboard
+    #   tensorflow
+aiofiles==23.2.1
+    # via gradio
+annotated-types==0.7.0
+    # via pydantic
+anyio==4.8.0
+    # via
+    #   gradio
+    #   httpx
+    #   starlette
+astunparse==1.6.3
+    # via tensorflow
+certifi==2025.1.31
+    # via
+    #   httpcore
+    #   httpx
+    #   requests
+charset-normalizer==3.4.1
+    # via requests
+click==8.1.8
+    # via
+    #   deepdanbooru
+    #   typer
+    #   uvicorn
+deepdanbooru @ git+https://github.com/KichangKim/DeepDanbooru@55e8ed7e5e6f24641d9d646a2f34035813b536d4
+    # via deepdanbooru-app (pyproject.toml)
+exceptiongroup==1.2.2
+    # via anyio
+fastapi==0.115.11
+    # via gradio
+ffmpy==0.5.0
+    # via gradio
+filelock==3.17.0
+    # via huggingface-hub
+flatbuffers==25.2.10
+    # via tensorflow
+fsspec==2025.2.0
+    # via
+    #   gradio-client
+    #   huggingface-hub
+gast==0.6.0
+    # via tensorflow
+google-pasta==0.2.0
+    # via tensorflow
+gradio==5.20.0
+    # via deepdanbooru-app (pyproject.toml)
+gradio-client==1.7.2
+    # via gradio
+groovy==0.1.2
+    # via gradio
+grpcio==1.70.0
+    # via
+    #   tensorboard
+    #   tensorflow
+h11==0.14.0
+    # via
+    #   httpcore
+    #   uvicorn
+h5py==3.13.0
+    # via
+    #   keras
+    #   tensorflow
+hf-transfer==0.1.9
+    # via deepdanbooru-app (pyproject.toml)
+httpcore==1.0.7
+    # via httpx
+httpx==0.28.1
+    # via
+    #   gradio
+    #   gradio-client
+    #   safehttpx
+huggingface-hub==0.29.1
+    # via
+    #   gradio
+    #   gradio-client
+idna==3.10
+    # via
+    #   anyio
+    #   httpx
+    #   requests
+imageio==2.37.0
+    # via scikit-image
+jinja2==3.1.5
+    # via gradio
+keras==3.8.0
+    # via tensorflow
+lazy-loader==0.4
+    # via scikit-image
+libclang==18.1.1
+    # via tensorflow
+markdown==3.7
+    # via tensorboard
+markdown-it-py==3.0.0
+    # via rich
+markupsafe==2.1.5
+    # via
+    #   gradio
+    #   jinja2
+    #   werkzeug
+mdurl==0.1.2
+    # via markdown-it-py
+ml-dtypes==0.4.1
+    # via
+    #   keras
+    #   tensorflow
+namex==0.0.8
+    # via keras
+networkx==3.4.2
+    # via scikit-image
+numpy==2.0.2
+    # via
+    #   deepdanbooru
+    #   gradio
+    #   h5py
+    #   imageio
+    #   keras
+    #   ml-dtypes
+    #   pandas
+    #   scikit-image
+    #   scipy
+    #   tensorboard
+    #   tensorflow
+    #   tifffile
+opt-einsum==3.4.0
+    # via tensorflow
+optree==0.14.1
+    # via keras
+orjson==3.10.15
+    # via gradio
+packaging==24.2
+    # via
+    #   gradio
+    #   gradio-client
+    #   huggingface-hub
+    #   keras
+    #   lazy-loader
+    #   scikit-image
+    #   tensorboard
+    #   tensorflow
+pandas==2.2.3
+    # via gradio
 pillow==10.3.0
-tensorflow==2.15.0.post1
+    # via
+    #   gradio
+    #   imageio
+    #   scikit-image
+protobuf==5.29.3
+    # via
+    #   tensorboard
+    #   tensorflow
+pydantic==2.10.6
+    # via
+    #   fastapi
+    #   gradio
+pydantic-core==2.27.2
+    # via pydantic
+pydub==0.25.1
+    # via gradio
+pygments==2.19.1
+    # via rich
+python-dateutil==2.9.0.post0
+    # via pandas
+python-multipart==0.0.20
+    # via gradio
+pytz==2025.1
+    # via pandas
+pyyaml==6.0.2
+    # via
+    #   gradio
+    #   huggingface-hub
+requests==2.32.3
+    # via
+    #   deepdanbooru
+    #   huggingface-hub
+    #   tensorflow
+rich==13.9.4
+    # via
+    #   keras
+    #   typer
+ruff==0.9.9
+    # via gradio
+safehttpx==0.1.6
+    # via gradio
+scikit-image==0.25.2
+    # via deepdanbooru
+scipy==1.15.2
+    # via scikit-image
+semantic-version==2.10.0
+    # via gradio
+setuptools==75.8.2
+    # via
+    #   tensorboard
+    #   tensorflow
+shellingham==1.5.4
+    # via typer
+six==1.17.0
+    # via
+    #   astunparse
+    #   deepdanbooru
+    #   google-pasta
+    #   python-dateutil
+    #   tensorboard
+    #   tensorflow
+sniffio==1.3.1
+    # via anyio
+starlette==0.46.0
+    # via
+    #   fastapi
+    #   gradio
+tensorboard==2.18.0
+    # via tensorflow
+tensorboard-data-server==0.7.2
+    # via tensorboard
+tensorflow==2.18.0
+    # via deepdanbooru-app (pyproject.toml)
+tensorflow-io-gcs-filesystem==0.37.1
+    # via tensorflow
+termcolor==2.5.0
+    # via tensorflow
+tifffile==2025.2.18
+    # via scikit-image
+tomlkit==0.13.2
+    # via gradio
+tqdm==4.67.1
+    # via huggingface-hub
+typer==0.15.2
+    # via gradio
+typing-extensions==4.12.2
+    # via
+    #   anyio
+    #   fastapi
+    #   gradio
+    #   gradio-client
+    #   huggingface-hub
+    #   optree
+    #   pydantic
+    #   pydantic-core
+    #   rich
+    #   tensorflow
+    #   typer
+    #   uvicorn
+tzdata==2025.1
+    # via pandas
+urllib3==2.3.0
+    # via requests
+uvicorn==0.34.0
+    # via gradio
+websockets==15.0
+    # via gradio-client
+werkzeug==3.1.3
+    # via tensorboard
+wheel==0.45.1
+    # via astunparse
+wrapt==1.17.2
+    # via tensorflow