利用神经网络（考虑模型、数据集的大小以及模型的感受野）在数据集上进行训练，直接预测需要滑动的距离。由于百度安全验证的角度并不是整数变化的，滑动距离与角度的变化也不是一一对应的，因此相对于预测角度而言，直接预测滑动距离更加准确、便捷。且滑动距离的类别相比较于而言要少，从而使得模型的参数也更少。此外，因为模型的目的是能足够准确地预测滑动距离，从而使得自动化程序模拟验证，因此，应该使得模型尽可能多地在现有数据集上学习。综上，考虑到真实场景的验证图片与获得的图片存在一定的差异（即使是相同的图片，也会受到不同程度的噪声干扰，如水印等），不再对数据集进行训练集与测试集的划分。
☆34Aug 15, 2022Updated 4 years ago
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