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CV,Computer Vision,计算机视觉,是目前人工智能领域非常重要的一个分支,拥有非常多的研究人员和应用,工业化程度也正在飞速提搞。CV主要研究对象为图片和视频,旨在使机器能够复制人类的视觉系统,理解和解释图像/视频中的内容。最新的计算机视觉深度学习模型在面部识别、对象检测和图像分类等现实世界图像识别任务中实现了高于人类水平的准确性和性能,在图片生成/视频生成任务中也有了惊人的进步。并且计算机视觉已被广泛应用于各行业,从安全和医学成像到制造、汽车、农业、建筑、智慧城市、交通等等领域,并随着技术的进步变得更加灵活和可扩展,这也让更多的实际用例成为可能。
旨在学界推广MindSpore CV领域的套件 —— 包括CV基础, 检测套件, OCR套件, 生成式套件等一系列基于 MindSpore 开发的,致力于计算机视觉相关技术研发的开源工具箱。我们提供大量的计算机视觉领域的经典模型和SoTA模型以及它们的预训练权重和训练策略。同时,还提供了自动增强等SoTA算法来提高模型性能。通过解耦的模块设计,我们可以轻松地将MindSpore CV领域套件内的模型权重应用到您自己的CV任务中。
链接:https://github.com/mindspore-lab/
以下人士可以由SIG成员邀请加入。
MindSpore community
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