Kornia is a powerful Python library designed to bring computer vision capabilities into PyTorch in a differentiable and efficient way. It allows developers and researchers to perform image processing, geometric transformations, filtering, feature detection, and data augmentation directly within deep learning pipelines, enabling seamless integration with neural networks and GPU acceleration.

Features of Kornia:

• Kornia provides differentiable image operations such as color conversion, blurring, edge detection, and geometric transformations, allowing gradients to flow through vision tasks in neural networks.
• Kornia supports image augmentation for training deep learning models, including random crops, rotations, flips, color jittering, and more.
• Kornia includes feature detection and matching modules for keypoints, descriptors, and image alignment, useful for tasks like SLAM, 3D reconstruction, and image stitching.
• Kornia offers loss functions specifically designed for computer vision tasks, including photometric loss, SSIM, and perceptual losses, simplifying model training and evaluation.
• Kornia integrates seamlessly with PyTorch, enabling GPU acceleration and easy combination with neural networks, making it ideal for research and production pipelines.

Check Kornia version: python -c "import kornia; print(kornia.__version__)"

Disclaimer: Kornia is an open-source software distributed under the Apache 2.0 License. It is not affiliated with, endorsed by, or sponsored by any company. Kornia is provided "as is," without any warranty, express or implied. Users utilize this software at their own risk. The developers and contributors to Kornia hold no responsibility for any damages, losses, or consequences resulting from the use of this software. Users are advised to carefully review and comply with licensing terms and any applicable regulations while using Kornia.