Dusk 0.90

Dusk is an open-source Python library for loading and preprocessing volumetric data to be used with deep learning workflows.

Dusk can load a variety of volumetric data formats, including medical imaging data such as CT and MRI scans, as well as scientific imaging and simulation data.

Dusk is designed to work with popular deep learning frameworks such as TensorFlow, PyTorch, and Keras, making it easy to incorporate volumetric data into your machine learning workflows.

Dusk offers a range of preprocessing tools, such as intensity normalization, resizing, cropping, and data augmentation. These can be easily applied to the loaded volumetric data to prepare it for training deep learning models.

Yes, Dusk is designed with scalability in mind and can handle large datasets efficiently using streaming and caching techniques.

Yes, Dusk integrates seamlessly with NVIDIA GPU-accelerated frameworks for deep learning, such as TensorFlow and PyTorch. This allows for fast processing of volumetric data on GPUs.

Yes, Dusk is released under the Apache 2.0 license, which allows for commercial use.

You can get started with Dusk by installing it using pip and following the documentation and tutorials available on the Dusk website.

Yes, Dusk has an active community of developers and users who provide support and contribute to the development of the library.

Yes, contributions to Dusk are welcome and can be made through the GitHub repository. Please review the contribution guidelines on the Dusk website for more information.