Showing 4 open source projects for "data processing"

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  • 1

    libsombrero

    Astronomical object/structure detection from 1D and 2D data sets.

    Sombrero is a fast wavelet image processing and object detection C library for astronomical images. Sombrero is named after the "Mexican Hat" shape of the wavelet masks used in image convolution and is released under the GNU LGPL library.
    Downloads: 0 This Week
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  • 2
    Darknet YOLO

    Darknet YOLO

    Real-Time Object Detection for Windows and Linux

    This is YOLO-v3 and v2 for Windows and Linux. YOLO (You only look once) is a state-of-the-art, real-time object detection system of Darknet, an open source neural network framework in C. YOLO is extremely fast and accurate. It uses a single neural network to divide a full image into regions, and then predicts bounding boxes and probabilities for each region. This project is a fork of the original Darknet project.
    Downloads: 43 This Week
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  • 3
    PyTracking

    PyTracking

    Visual tracking library based on PyTorch

    A general python framework for visual object tracking and video object segmentation, based on PyTorch. Official implementation of the RTS (ECCV 2022), ToMP (CVPR 2022), KeepTrack (ICCV 2021), LWL (ECCV 2020), KYS (ECCV 2020), PrDiMP (CVPR 2020), DiMP (ICCV 2019), and ATOM (CVPR 2019) trackers, including complete training code and trained models.
    Downloads: 0 This Week
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  • 4
    MultiPathNet

    MultiPathNet

    A Torch implementation of the object detection network

    MultiPathNet is a Torch-7 implementation of the “A MultiPath Network for Object Detection” paper (BMVC 2016), developed by Facebook AI Research. It extends the Fast R-CNN framework by introducing multiple network “paths” to enhance feature extraction and object recognition robustness. The MultiPath architecture incorporates skip connections and multi-scale processing to capture both fine-grained details and high-level context within a single detection pipeline. This results in improved...
    Downloads: 2 This Week
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