Showing 3 open source projects for "fast performance"

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    Paessler: Easy to Use With Enterprise Power. Free Trial

    A low-code dashboard makes monitoring intuitive for any admin, while scripting and custom sensors give experts full control.

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    Albumentations

    Albumentations

    Fast image augmentation library and an easy-to-use wrapper

    Albumentations is a computer vision tool that boosts the performance of deep convolutional neural networks. Albumentations is a Python library for fast and flexible image augmentations. Albumentations efficiently implements a rich variety of image transform operations that are optimized for performance, and does so while providing a concise, yet powerful image augmentation interface for different computer vision tasks, including object classification, segmentation, and detection. ...
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  • 2
    fastai

    fastai

    Deep learning library

    fastai is a deep learning library which provides practitioners with high-level components that can quickly and easily provide state-of-the-art results in standard deep learning domains, and provides researchers with low-level components that can be mixed and matched to build new approaches. It aims to do both things without substantial compromises in ease of use, flexibility, or performance. This is possible thanks to a carefully layered architecture, which expresses common underlying...
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  • 3
    maskrcnn-benchmark

    maskrcnn-benchmark

    Fast, modular reference implementation of Instance Segmentation

    Mask R-CNN Benchmark is a PyTorch-based framework that provides high-performance implementations of object detection, instance segmentation, and keypoint detection models. Originally built to benchmark Mask R-CNN and related models, it offers a clean, modular design to train and evaluate detection systems efficiently on standard datasets like COCO. The framework integrates critical components—region proposal networks (RPNs), RoIAlign layers, mask heads, and backbone architectures such as...
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