Comments (11)
@moxiegushi 同问。分割模型师如何训练的?是否采用了faster rcnn?
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客气了,我也是初学者,相互学习
训练过程已经更新了@histronger
没有采用RCNN,只是普通的VGG卷积神经网络@albertyou2
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@moxiegushi
感谢回复
但是我还没有看到您训练的过程,可能我看错地方了。而且有个地方不太明白想请教,
我看您的训网络最后一层是softmax,而且分割器和分类器用的同一个网络,那么如何训练分割器的呢?
我的印象中分割器应该是要输出一个box的~谢谢
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@albertyou2
可以参考一下keras的文档,keras已经把训练过程封装的很好了,不需要人工将图片展成一维再构造batch然后BP什么的,分割器输出的只是box的代号,然后再predict函数中找到对应的box
最后一层的输出是概率,只需选取最大的四个作为成功切割的box即可
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@moxiegushi
请原谅再最后一个问题了,我应该看keras文档的那一部分?是predict_generator这个么。
刚学习keras不久
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请问是否可以公开原始训练数据?有些想法想试验一下。
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@moxiegushi
我大致看懂了您的源码,您是把验证码切分成121个区域,然后依次选出最有可能的4个区域,然后依次分类。
但有一个点我没看懂,def checkAndReplace(index,target,distance):这个方法是做什么的?distance 是什么距离呢?
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训练数据已公开 @lxdestiny
用于排除多张最优解是同一个字母的情况,distance设为小于字符宽度并且大于字符宽度的一半,都可以 @albertyou2
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@moxiegushi SVGG.py
全部代码可以公开不,现在的代码跑不起来啊
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checkAndReplace(index, target, 18)
target.sort()
还是不太清楚,排除多张最优解是同一个字母??抱歉,大神,能再稍微详细解释一下么,谢谢!
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