version to 0.0.19 (#41)

* version to 0.0.19

* Updated CI

* Fi in CI

* Mypy fix

* Fix

Author: ternaus

.github/workflows/ci.yml

@@ -4,10 +4,9 @@ on:
     branches:
       - main
     paths-ignore:
-      - 'CONTRIBUTORS.md'
-      - 'README.md'
-      - 'benchmarks/results/**'
-
+      - 'benchmarks/albucore_benchmark/results/**'
+      - '**.md'  # Ignore all markdown files
+      - 'docs/**'  # Ignore documentation changes
 jobs:
   test_and_lint:
     name: Test and lint
@@ -24,13 +23,18 @@ jobs:
           - operating-system: macos-13
             path: ~/Library/Caches/pip
       fail-fast: true
+
     steps:
     - name: Checkout
       uses: actions/checkout@v4
-    - name: Set up Python
+    - name: Set up Python ${{ matrix.python-version }}
       uses: actions/setup-python@v5
       with:
         python-version: ${{ matrix.python-version }}
+        cache: 'pip'
+        cache-dependency-path: |
+          requirements-dev.txt
+          setup.py
 
     - name: Cache Python packages
       uses: actions/cache@v4
@@ -41,29 +45,25 @@ jobs:
           ${{ runner.os }}-pip-${{ matrix.python-version }}-
           ${{ runner.os }}-pip-
 
-    - name: Update pip
-      run: python -m pip install --upgrade pip
-    - name: Install wheel
-      run: python -m pip install --upgrade wheel
-    - name: Install dev requirements
-      run: pip install -r requirements-dev.txt
+    - name: Install uv
+      run: pip install uv
+
     - name: Install dependencies
       run: |
-        python -m ensurepip --upgrade
-        pip install .
-    - name: Cleanup the build directory
-      uses: JesseTG/[email protected]
-      with:
-        path: build
-    - name: Run PyTest
-      run: pytest --cov .
+        uv pip install --system --upgrade pip wheel
+        uv pip install --system -r requirements-dev.txt
+        uv pip install --system .
+
+    - name: Run PyTest with coverage
+      run: pytest --cov . --cov-report=xml
 
     - name: Upload coverage reports to Codecov
-      if: matrix.operating-system == 'ubuntu-latest' && matrix.python-version == '3.8'
+      if: matrix.operating-system == 'ubuntu-latest' && matrix.python-version == '3.12'
       uses: codecov/[email protected]
       with:
         token: ${{ secrets.CODECOV_TOKEN }}
         slug: albumentations-team/albucore
+        files: ./coverage.xml
 
   check_code_formatting_types:
     name: Check code formatting with ruff and mypy
@@ -75,15 +75,23 @@ jobs:
     steps:
     - name: Checkout
       uses: actions/checkout@v4
-    - name: Set up Python
+    - name: Set up Python ${{ matrix.python-version }}
       uses: actions/setup-python@v5
       with:
         python-version: ${{ matrix.python-version }}
+        cache: 'pip'
+        cache-dependency-path: |
+          requirements-dev.txt
+          setup.py
+
+    - name: Install uv
+      run: pip install uv
+
     - name: Install requirements
       run: |
-        python -m pip install --upgrade pip uv
+        uv pip install --system --upgrade pip
+        uv pip install --system -r requirements-dev.txt
         uv pip install --system .
-    - name: Install dev requirements
-      run: uv pip install --system -r requirements-dev.txt
+
     - name: Run checks
-      run: pre-commit run
+      run: pre-commit run --all-files

.pre-commit-config.yaml

@@ -68,7 +68,7 @@ repos:
       # Run the formatter.
       - id: ruff-format
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.12.1
+    rev: v1.13.0
     hooks:
       - id: mypy
         files: ^(albucore|benchmark)/

albucore/__init__.py

@@ -1,4 +1,14 @@
-__version__ = "0.0.18"
+from importlib.metadata import metadata
+
+try:
+    _metadata = metadata("albucore")
+    __version__ = _metadata["Version"]
+    __author__ = _metadata["Author"]
+    __maintainer__ = _metadata["Maintainer"]
+except Exception:  # noqa: BLE001
+    __version__ = "unknown"
+    __author__ = "Vladimir Iglovikov"
+    __maintainer__ = "Vladimir Iglovikov"
 
 from .decorators import *
 from .functions import *

albucore/functions.py

@@ -72,31 +72,49 @@ def apply_lut(
 
 
 def prepare_value_opencv(
-    img: np.ndarray, value: np.ndarray | float, operation: Literal["add", "multiply"]
+    img: np.ndarray,
+    value: np.ndarray | float,
+    operation: Literal["add", "multiply"],
 ) -> np.ndarray:
-    if isinstance(value, (int, float)):
-        if operation == "add" and img.dtype == np.uint8:
-            value = int(value)
-        num_channels = get_num_channels(img)
-        if num_channels > MAX_OPENCV_WORKING_CHANNELS:
-            if operation == "add":
-                # Cast to float32 if value is negative to handle potential underflow issues
-                cast_type = np.float32 if value < 0 else img.dtype
-                value = np.full(img.shape, value, dtype=cast_type)
-            elif operation == "multiply":
-                value = np.full(img.shape, value, dtype=np.float32)
-    elif isinstance(value, np.ndarray):
-        if value.dtype == np.float64:
-            value = value.astype(np.float32)
-        if value.ndim == 1:
-            value = value.reshape(1, 1, -1)
-        value = np.broadcast_to(value, img.shape)
-        if operation == "add" and img.dtype == np.uint8:
-            if np.all(value >= 0):
-                return clip(value, np.uint8)
-
-            value = np.trunc(value).astype(np.float32)
+    return (
+        _prepare_scalar_value(img, value, operation)
+        if isinstance(value, (int, float))
+        else _prepare_array_value(img, value, operation)
+    )
 
+
+def _prepare_scalar_value(
+    img: np.ndarray,
+    value: float,
+    operation: Literal["add", "multiply"],
+) -> np.ndarray | float:
+    if operation == "add" and img.dtype == np.uint8:
+        value = int(value)
+    num_channels = get_num_channels(img)
+    if num_channels > MAX_OPENCV_WORKING_CHANNELS:
+        if operation == "add":
+            # Cast to float32 if value is negative to handle potential underflow issues
+            cast_type = np.float32 if value < 0 else img.dtype
+            return np.full(img.shape, value, dtype=cast_type)
+        if operation == "multiply":
+            return np.full(img.shape, value, dtype=np.float32)
+    return value
+
+
+def _prepare_array_value(
+    img: np.ndarray,
+    value: np.ndarray,
+    operation: Literal["add", "multiply"],
+) -> np.ndarray:
+    if value.dtype == np.float64:
+        value = value.astype(np.float32)
+    if value.ndim == 1:
+        value = value.reshape(1, 1, -1)
+    value = np.broadcast_to(value, img.shape)
+    if operation == "add" and img.dtype == np.uint8:
+        if np.all(value >= 0):
+            return clip(value, np.uint8)
+        return np.trunc(value).astype(np.float32)
     return value
 
 

albucore/utils.py

@@ -55,7 +55,9 @@
 
 
 def maybe_process_in_chunks(
-    process_fn: Callable[Concatenate[np.ndarray, P], np.ndarray], **kwargs: Any
+    process_fn: Callable[Concatenate[np.ndarray, P], np.ndarray],
+    *args: P.args,
+    **kwargs: P.kwargs,
 ) -> Callable[[np.ndarray], np.ndarray]:
     """Wrap OpenCV function to enable processing images with more than 4 channels.
 
@@ -64,15 +66,19 @@ def maybe_process_in_chunks(
 
     Args:
         process_fn: Transform function (e.g cv2.resize).
-        kwargs: Additional parameters.
+        args: Additional positional arguments.
+        kwargs: Additional keyword arguments.
 
     Returns:
         np.ndarray: Transformed image.
-
     """
 
     @wraps(process_fn)
-    def __process_fn(img: np.ndarray) -> np.ndarray:
+    def __process_fn(img: np.ndarray, *process_args: P.args, **process_kwargs: P.kwargs) -> np.ndarray:
+        # Merge args and kwargs
+        all_args = (*args, *process_args)
+        all_kwargs: P.kwargs = {**kwargs, **process_kwargs}
+
         num_channels = get_num_channels(img)
         if num_channels > MAX_OPENCV_WORKING_CHANNELS:
             chunks = []
@@ -81,16 +87,16 @@ def __process_fn(img: np.ndarray) -> np.ndarray:
                     # Many OpenCV functions cannot work with 2-channel images
                     for i in range(2):
                         chunk = img[:, :, index + i : index + i + 1]
-                        chunk = process_fn(chunk, **kwargs)
+                        chunk = process_fn(chunk, *all_args, **all_kwargs)
                         chunk = np.expand_dims(chunk, -1)
                         chunks.append(chunk)
                 else:
                     chunk = img[:, :, index : index + 4]
-                    chunk = process_fn(chunk, **kwargs)
+                    chunk = process_fn(chunk, *all_args, **all_kwargs)
                     chunks.append(chunk)
             return np.dstack(chunks)
 
-        return process_fn(img, **kwargs)
+        return process_fn(img, *all_args, **all_kwargs)
 
     return __process_fn
 

benchmark/albucore_benchmark/benchmark.py

@@ -173,7 +173,7 @@ def opencv_transform(self, img: np.ndarray) -> np.ndarray | None:
         return albucore.multiply_opencv(img, self.multiplier)
 
     def lut_transform(self, img: np.ndarray) -> np.ndarray:
-        return albucore.multiply_lut(img, self.multiplier)
+        return albucore.multiply_lut(img, self.multiplier, inplace=False)
 
     def torchvision_transform(self, img: torch.Tensor) -> torch.Tensor:
         return torch.mul(img, self.multiplier)
@@ -195,7 +195,7 @@ def opencv_transform(self, img: np.ndarray) -> np.ndarray:
         return albucore.multiply_opencv(img, self.multiplier)
 
     def lut_transform(self, img: np.ndarray) -> np.ndarray:
-        return albucore.multiply_lut(img, self.multiplier)
+        return albucore.multiply_lut(img, self.multiplier, inplace=False)
 
     def torchvision_transform(self, img: torch.Tensor) -> torch.Tensor:
         return torch.mul(img, self.torch_multiplier)
@@ -239,7 +239,7 @@ def opencv_transform(self, img: np.ndarray) -> np.ndarray | None:
         return albucore.add_opencv(img, self.value)
 
     def lut_transform(self, img: np.ndarray) -> np.ndarray:
-        return albucore.add_lut(img, self.value)
+        return albucore.add_lut(img, self.value, inplace=False)
 
     def torchvision_transform(self, img: torch.Tensor) -> torch.Tensor:
         return torch.add(img, self.value)
@@ -261,7 +261,7 @@ def opencv_transform(self, img: np.ndarray) -> np.ndarray:
         return albucore.add_opencv(img, self.value)
 
     def lut_transform(self, img: np.ndarray) -> np.ndarray:
-        return albucore.add_lut(img, self.value)
+        return albucore.add_lut(img, self.value, inplace=False)
 
     def torchvision_transform(self, img: torch.Tensor) -> torch.Tensor:
         return torch.add(img, self.torch_value)
@@ -472,7 +472,7 @@ def opencv_transform(self, img: np.ndarray) -> np.ndarray:
 
     def lut_transform(self, img: np.ndarray) -> np.ndarray:
         value = MAX_VALUES_BY_DTYPE[img.dtype] / 10.0
-        return albucore.multiply_add_lut(img, self.factor, value)
+        return albucore.multiply_add_lut(img, self.factor, value, inplace=False)
 
     def torchvision_transform(self, img: torch.Tensor) -> torch.Tensor:
         return img * self.factor + 13

pyproject.toml

@@ -5,11 +5,15 @@ requires = [ "setuptools>=45", "wheel" ]
 
 [project]
 name = "albucore"
+version = "0.0.19"
+
 description = "High-performance image processing functions for deep learning and computer vision."
 readme = "README.md"
 keywords = [ "deep learning", "image processing" ]
 license = { file = "LICENSE" }
-authors = [ { name = "Vladimir I. Iglovikov" } ]
+maintainers = [ { name = "Vladimir Iglovikov" } ]
+
+authors = [ { name = "Vladimir Iglovikov" } ]
 requires-python = ">=3.9"
 
 classifiers = [
@@ -31,7 +35,7 @@ classifiers = [
   "Topic :: Software Development :: Libraries :: Python Modules",
   "Typing :: Typed",
 ]
-dynamic = [ "dependencies", "version" ]
+dynamic = [ "dependencies" ]
 
 [tool.setuptools]
 packages = { find = { include = [

setup.py

@@ -1,6 +1,4 @@
 import re
-from typing import List, Tuple
-import os
 
 from pkg_resources import DistributionNotFound, get_distribution
 from setuptools import setup, find_packages
@@ -21,17 +19,7 @@
     ),
 ]
 
-def get_version():
-    version_file = os.path.join(os.path.dirname(__file__), 'albucore', '__init__.py')
-    with open(version_file, 'r') as f:
-        version_line = f.read().strip()
-    version_regex = r"^__version__ = ['\"]([^'\"]*)['\"]"
-    match = re.match(version_regex, version_line, re.M)
-    if match:
-        return match.group(1)
-    raise RuntimeError("Unable to find version string.")
-
-def choose_requirement(mains: Tuple[str, ...], secondary: str) -> str:
+def choose_requirement(mains: tuple[str, ...], secondary: str) -> str:
     chosen = secondary
     for main in mains:
         try:
@@ -43,13 +31,12 @@ def choose_requirement(mains: Tuple[str, ...], secondary: str) -> str:
             pass
     return chosen
 
-def get_install_requirements(install_requires: List[str], choose_install_requires: List[Tuple[Tuple[str, ...], str]]) -> List[str]:
+def get_install_requirements(install_requires: list[str], choose_install_requires: list[tuple[tuple[str, ...], str]]) -> list[str]:
     for mains, secondary in choose_install_requires:
         install_requires.append(choose_requirement(mains, secondary))
     return install_requires
 
 setup(
-    version=get_version(),
     packages=find_packages(exclude=["tests", "benchmark"], include=['albucore*']),
     install_requires=get_install_requirements(INSTALL_REQUIRES, CHOOSE_INSTALL_REQUIRES),
 )