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Caltech256图像数据集,256 个对象类别中的30000多张图像

Caltech256图像数据集,256 个对象类别中的30000多张图像

2.12G
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Classification,Image Data,Universities and Colleges Classification

The Caltech 256 is considered an improvement to its predecessor, the Caltech 101 dataset, with new features such as larg......

数据结构 ? 2.12G

    Data Structure ?

    * 以上分析是由系统提取分析形成的结果,具体实际数据为准。

    README.md

    The Caltech 256 is considered an improvement to its predecessor, the Caltech 101 dataset, with new features such as larger category sizes, new and larger clutter categories, and overall increased difficulty. This is a great dataset to train models for visual recognition: How can we recognize frogs, cell phones, sail boats and many other categories in cluttered pictures? How can we learn these categories in the first place? Can we endow machines with the same ability?

    Content

    There are 30,607 images in this dataset spanning 257 object categories. Object categories are extremely diverse, ranging from grasshopper to tuning fork. The distribution of images per category are:

    • Min: 80

    • Med: 100

    • Mean: 119

    • Max: 827

    Acknowledgements

    Original data source and banner image: http://www.vision.caltech.edu/Image_Datasets/Caltech256/

    When using this dataset, please remember to cite:

    Griffin, G. Holub, AD. Perona, P.
    The Caltech 256.
    Caltech Technical Report.


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