OpenCV HOG 描述符上的 SVMLight
我正在尝试使用 SVM Light 来学习 OpenCV2.2 HOG 描述符的分类器。 我从 HOG 描述符获得浮点向量输出。
阅读 SVMLight 文档后，我仍然无法理解输入训练和测试数据的格式是什么。
网站中的 train.dat 中的一行示例：
1 6:0.0176472501759912 15:0.0151152682071138 26:0.0572866228831546 27:0.0128461400334668
Where,
The first char: 1, denote the positive class.
The second and third char 6: <== I don't understand what does this means,
The third variable denote the feature vector.
Will Anybody please help?谢谢！
I am trying to use SVM Light to learn a classifier for the OpenCV2.2 HOG Descriptor.
I get a float vector output from the HOG descriptor.
After reading the SVMLight documentation, i still cannot understand what is the format of the input train and test data.
Example of a line from train.dat from the website:
1 6:0.0176472501759912 15:0.0151152682071138 26:0.0572866228831546 27:0.0128461400334668
Where,
The first char: 1, denote the positive class.
The second and third char 6: <== I don't understand what does this means,
The third variable denote the feature vector.
Would anyone please help? Thanks!
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6:XXXX表示本示例中第 6 个功能的值为XXX在您提供的示例中：
这意味着该示例的类标签为
1。第 6 个特征值是 0.0176472501759912，第 15 个特征值是 0.0151152682071138，等等。将其视为每个示例的特征向量的“稀疏编码”。这隐式意味着对于您提供的示例，功能 1-5、7-14、16-25 的值为 0。
The
6:XXXXmeans that the value of the 6th feature for this example isXXXIn the example you provide:
It means that the example has a class label of
1. The 6th feature value is 0.0176472501759912, the 15th feature value is 0.0151152682071138, etc.Think of it as a "sparse encoding" of the feature vector for each example. Implicitly this means that values for features 1-5, 7-14, 16-25 is 0 for the example that you provided.