imgaug (fork with fix for NumPy 2.0+)

🛠️ This fork of imgaug includes a compatibility fix for NumPy 2.0+, which removed the np.sctypes attribute.
Based on a solution proposed by @qja1998 in an issue on the original repository.

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🔧 What's Changed?

In imgaug/parameters.py, this code:

NP_FLOAT_TYPES = set(np.sctypes["float"])
NP_INT_TYPES = set(np.sctypes["int"])
NP_UINT_TYPES = set(np.sctypes["uint"])

Has been replaced with:

NP_FLOAT_TYPES = {np.float16, np.float32, np.float64}
NP_INT_TYPES = {np.int8, np.int16, np.int32, np.int64}
NP_UINT_TYPES = {np.uint8, np.uint16, np.uint32, np.uint64}

This resolves an AttributeError when using imgaug with NumPy 2.0 or later.

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📦 Installation

Install this patched version directly using pip:

pip install git+https://github.com/pbarbadol/imgaug.git@v0.4.1-fixnp

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📌 Requirements

• Python ≥ 3.7
• NumPy ≥ 2.0.0
• Based on imgaug v0.4.0

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🙌 Credits

• Original library: aleju/imgaug
• Fix proposed by @qja1998
• Fork maintained by @pbarbadol

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📜 License

This fork follows the MIT License of the original project.

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imgaug

This Python library helps you with augmenting images for your machine learning projects.
It converts a set of input images into a new, much larger set of slightly altered images.