WIP

.github/workflows/python.yml

@@ -17,10 +17,11 @@ jobs:
       uses: actions/setup-python@v5
       with:
         python-version: ${{ matrix.python-version }}
+    - name: Install Poetry
+      uses: snok/install-poetry@v1
     - name: Install dependencies
       run: |
-        python -m pip install --upgrade pip
-        pip install -r tests/actions_requirements.txt
+        poetry install --with dev
     - name: Test with pytest
       run: |
         python --version

.pre-commit-config.yaml

@@ -0,0 +1,82 @@
+# can be used to exclude certain regex patterns or paths
+exclude: '^$'
+# if set to true, fails on first failure
+fail_fast: false
+repos:
+  # The following pre-commit hooks could be very useful.
+  # They are not part of CI/CD, so use or remove them as you please
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v4.6.0
+    hooks:
+    - id: trailing-whitespace
+    - id: end-of-file-fixer
+    - id: debug-statements
+    - id: name-tests-test
+      args: [
+        "--pytest-test-first" # test_.*\.py
+        #"--pytest" # .*_test\.py
+        #"--unittest" # test.*\.py
+      ]
+    - id: check-added-large-files
+    - id: check-docstring-first
+    - id: check-executables-have-shebangs
+    - id: check-shebang-scripts-are-executable
+    - id: check-merge-conflict
+    - id: check-yaml
+      args: ['--unsafe']
+    - id: check-toml
+    - id: check-xml
+    - id: detect-private-key
+
+  - repo: https://gitlab.com/bmares/check-json5
+    rev: v1.0.0
+    hooks:
+    - id: check-json5
+
+  - repo: https://github.com/DavidAnson/markdownlint-cli2
+    rev: v0.13.0
+    hooks:
+      - id: markdownlint-cli2
+        args: [ "--fix", "--config", ".markdownlint.yaml" ]
+
+  # part of CI/CD
+  - repo: local
+    hooks:
+      - id: poetry-check
+        name: poetry-check --lock
+        description: run poetry check to validate config
+        entry: poetry check --lock
+        language: python
+        pass_filenames: false
+        files: ^(.*/)?pyproject\.toml$
+#      - id: poetry-export
+#        name: poetry-export
+#        description: run poetry export to sync lock file with requirements.txt
+#        entry: poetry export
+#        language: python
+#        pass_filenames: false
+#        files: ^(.*/)?poetry\.lock$
+#        args: ["-f", "requirements.txt", "-o", "requirements.txt"]
+#      - id: poetry-export-dev
+#        name: poetry-export --with-dev
+#        description: run poetry export to sync lock file with requirements.txt
+#        entry: poetry export
+#        language: python
+#        pass_filenames: false
+#        files: ^(.*/)?poetry\.lock$
+#        args: ["--with", "dev", "-f", "requirements.txt", "-o", "requirements-dev.txt"]
+
+      - id: ruff-format
+        name: ruff-format
+        description: "Run 'ruff format' for extremely fast Python formatting"
+        entry: ruff format --force-exclude
+        language: python
+        types_or: [python, pyi]
+        args: []
+      - id: ruff
+        name: ruff
+        description: Run 'ruff' for extremely fast Python linting
+        entry: ruff check --force-exclude
+        language: python
+        types_or: [python, pyi]
+        args: [--fix]

README.md

@@ -38,10 +38,10 @@ Also included in this repo is an efficient pytorch implementation of MTCNN for f
     ```bash
     # With pip:
     pip install facenet-pytorch
-    
+
     # or clone this repo, removing the '-' to allow python imports:
     git clone https://github.com/timesler/facenet-pytorch.git facenet_pytorch
-    
+
     # or use a docker container (see https://github.com/timesler/docker-jupyter-dl-gpu):
     docker run -it --rm timesler/jupyter-dl-gpu pip install facenet-pytorch && ipython
     ```
@@ -50,10 +50,10 @@ Also included in this repo is an efficient pytorch implementation of MTCNN for f
 
     ```py
     from facenet_pytorch import MTCNN, InceptionResnetV1
-    
+
     # If required, create a face detection pipeline using MTCNN:
     mtcnn = MTCNN(image_size=<image_size>, margin=<margin>)
-    
+
     # Create an inception resnet (in eval mode):
     resnet = InceptionResnetV1(pretrained='vggface2').eval()
     ```
@@ -62,7 +62,7 @@ Also included in this repo is an efficient pytorch implementation of MTCNN for f
 
     ```py
     from PIL import Image
-    
+
     img = Image.open(<image path>)
 
     # Get cropped and prewhitened image tensor
@@ -176,7 +176,7 @@ The package and any of the example notebooks can be run with docker (or nvidia-d
 docker run --rm -p 8888:8888
     -v ./facenet-pytorch:/home/jovyan timesler/jupyter-dl-gpu \
     -v <path to data>:/home/jovyan/data
-    pip install facenet-pytorch && jupyter lab 
+    pip install facenet-pytorch && jupyter lab
 ```
 
 Navigate to the examples/ directory and run any of the ipython notebooks.

README_cn.md

@@ -72,7 +72,7 @@ Pytorch 模型权重使用从 David Sandberg 的 [tensorflow Facenet repo](https
 ## 快速启动
 
 1. 安装：
-   
+
 ````bash
 # 使用pip安装：
 pip install facenet-pytorch
@@ -85,7 +85,7 @@ docker run -it --rm timesler/jupyter-dl-gpu pip install facenet-pytorch && ipyth
 ````
 
 2. 在python中，导入 facenet-pytorch 并实例化模型：
-   
+
 ````python
 from facenet_pytorch import MTCNN, InceptionResnetV1
 
@@ -97,7 +97,7 @@ resnet = InceptionResnetV1(pretrained='vggface2').eval()
 ````
 
 3. 处理图像：
-   
+
 ````python
 from PIL import Image
 
@@ -214,7 +214,7 @@ MTCNN 可用于构建人脸跟踪系统（使用 `MTCNN.detect()` 方法）。
 docker run --rm -p 8888:8888
     -v ./facenet-pytorch:/home/jovyan timesler/jupyter-dl-gpu \
     -v <path to data>:/home/jovyan/data
-    pip install facenet-pytorch && jupyter lab 
+    pip install facenet-pytorch && jupyter lab
 ````
 
 导航到 example/ 目录并运行任何 ipython 笔记本。

codecov.yml

@@ -2,5 +2,5 @@ coverage:
   status:
     project: off
     patch: off
-codecov: 
+codecov:
   token: 1e4f3aaa-9c74-4888-9408-71cc7fcfb64c