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Version boosted to 1.4.24 (#2219)
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pyproject.toml

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@@ -6,31 +6,73 @@ requires = [ "setuptools>=45", "wheel" ]
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[project]
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name = "albumentations"
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version = "1.4.23"
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version = "1.4.24"
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description = "Fast, flexible, and advanced image augmentation library for deep learning and computer vision. Albumentations offers a wide range of transformations for images, masks, bounding boxes, and keypoints, with optimized performance and seamless integration into ML workflows."
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description = "Fast, flexible, and advanced augmentation library for deep learning, computer vision, and medical imaging. Albumentations offers a wide range of transformations for both 2D (images, masks, bboxes, keypoints) and 3D (volumes, volumetric masks) data, with optimized performance and seamless integration into ML workflows."
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readme = "README.md"
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keywords = [
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"2D augmentation",
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"3D augmentation",
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"aerial photography",
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"anomaly detection",
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"artificial intelligence",
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"bounding box",
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"autonomous driving",
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"bounding boxes",
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# Core Computer Vision Tasks
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"classification",
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# Technical Domains
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"computer vision",
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"computer vision library",
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"data augmentation",
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"data preprocessing",
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"data science",
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"deep learning",
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"deep learning library",
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"depth estimation",
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"face recognition",
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# Performance & Features
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"fast augmentation",
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# Data Types & Processing
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"image augmentation",
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"image classification",
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"image processing",
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"image transformation",
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# Data Structures
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"images",
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"instance segmentation",
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"keras",
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"keypoint detection",
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"keypoints",
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"machine learning",
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"machine learning tools",
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"masks",
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# Application Domains
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"medical imaging",
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"microscopy",
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"object counting",
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"object detection",
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"optimized performance",
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"panoptic segmentation",
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"pose estimation",
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# Development
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"python library",
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# ML Frameworks
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"pytorch",
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"quality inspection",
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"real-time processing",
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"robotics vision",
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"satellite imagery",
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"semantic segmentation",
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"tensorflow",
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"volumes",
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"volumetric data",
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"volumetric masks",
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]
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license = { file = "LICENSE" }
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@@ -40,24 +82,48 @@ authors = [ { name = "Vladimir Iglovikov" } ]
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requires-python = ">=3.9"
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classifiers = [
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# Development Status
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"Development Status :: 5 - Production/Stable",
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# Intended Audience
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"Intended Audience :: Developers",
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"Intended Audience :: Healthcare Industry", # valid for medical applications
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"Intended Audience :: Information Technology",
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"Intended Audience :: Science/Research",
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# License
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"License :: OSI Approved :: MIT License",
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# Operating System
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"Operating System :: OS Independent",
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# Python Versions
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"Programming Language :: Python",
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"Programming Language :: Python :: 3 :: Only",
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"Programming Language :: Python :: 3.9",
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"Programming Language :: Python :: 3.10",
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"Programming Language :: Python :: 3.11",
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"Programming Language :: Python :: 3.12",
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"Programming Language :: Python :: 3.13",
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# Topics - Scientific
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"Topic :: Scientific/Engineering",
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"Topic :: Scientific/Engineering :: Artificial Intelligence",
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"Topic :: Scientific/Engineering :: Astronomy",
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"Topic :: Scientific/Engineering :: Atmospheric Science",
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"Topic :: Scientific/Engineering :: Bio-Informatics",
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"Topic :: Scientific/Engineering :: Image Processing",
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"Topic :: Scientific/Engineering :: Physics",
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"Topic :: Scientific/Engineering :: Visualization",
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# Topics - Software Development
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"Topic :: Software Development :: Libraries",
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"Topic :: Software Development :: Libraries :: Python Modules",
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# Typing
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"Typing :: Typed",
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]
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dynamic = [ "dependencies" ]
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optional-dependencies.hub = [ "huggingface-hub" ]
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optional-dependencies.pytorch = [ "torch" ]

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