Showing 3 open source projects for "spatial"

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    TorchIO

    TorchIO

    Medical imaging toolkit for deep learning

    TorchIO is an open-source Python library for efficient loading, preprocessing, augmentation and patch-based sampling of 3D medical images in deep learning, following the design of PyTorch. It includes multiple intensity and spatial transforms for data augmentation and preprocessing. These transforms include typical computer vision operations such as random affine transformations and also domain-specific ones such as simulation of intensity artifacts due to MRI magnetic field inhomogeneity (bias) or k-space motion artifacts. TorchIO is a Python package containing a set of tools to efficiently read, preprocess, sample, augment, and write 3D medical images in deep learning applications written in PyTorch, including intensity and spatial transforms for data augmentation and preprocessing. ...
    Downloads: 1 This Week
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  • 2
    Butteraugli

    Butteraugli

    Estimates the psychovisual difference between two images

    butteraugli is a perceptual similarity metric designed to estimate how noticeable differences between two images will be to the human eye. Instead of simple pixel math, it models aspects of human vision—color sensitivity, spatial masking, and contrast perception—to highlight differences that viewers actually see. The core tool outputs a single “distance” score along with per-pixel or per-region maps that show where artifacts are most objectionable. These maps make it practical to tune compressor settings and confirm whether bitrate reductions are visually acceptable. ...
    Downloads: 0 This Week
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  • 3
    The Video Processing Evaluation Resource: A toolkit for evaluating computer vision algorithms on video, and a corresponding tool for annotating video streams with spatial metadata.
    Downloads: 0 This Week
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