单个图像可以成为多个类别的正面示例吗? [英] Can a single image be a positive example for multiple classes?

问题描述

花束是我们问题领域的一个非常准确的类比，并且我们有另一个所以问题，询问采用其他方法解决我们的问题/目标的可行性.

Bouquets of flowers are a fairly accurate analogy for our problem domain, and we have another S.O. question out there asking about the feasibility of a different approach to our problem/goal.

如果不是根据花的类型来分类，而是根据花束的内容和复杂的组合根据需要采取的动作来进行分类，该怎么办?

What if, rather than making classes by flower types, we made our classes according to the actions we need to take depending on the contents and complex combinations of the bouquet?

假设，如果在我们测试图像的花束中有:
>9 roses, >14 pansies, <1 marigold, any qty of other flowers
那么我们需要同时采取 action-a & action-d .

Let's say that, if in the bouquet in our test image, there are:
>9 roses, >14 pansies, <1 marigold, any qty of other flowers
then we need to take, both, action-a & action-d.

因此，相同的图像将同时用作类action-a和类action-d的正面示例.
相反，绝对有action-d个正例，而有一个action-a个负例，反之亦然.

So, then, the same image would be used as a positive example for both class action-a and class action-d.
Inversely, there would absolutely be positive action-d examples which would be negative action-a examples, and vice versa.

当然，即使进行了这种简化，它仍然变得相当复杂.
我想这种方法将需要 巨大 数量的训练图像.
即使如此，我还是希望它能起作用.

Of course, even with this simplification it still gets quite complex.
I imagine this approach would need a huge number of training images.
Even still, I'm hopeful that it might work.

有想法吗?

推荐答案

是的，您可以在1个分类器中的> 1个类中拥有相同的图像，只要每个类具有> = 10个唯一图像且总计> = 20总共包含分类器中的唯一图像，包括所有negative_examples.

Yes, you can have the same image in >1 classes inside 1 classifier, as long as you have >=10 unique images per class AND >=20 total unique images in the classifier in total, including any negative_examples.

但是，您应该谨慎执行此操作，以教"系统.

However, you should be careful about what you are "teaching" the system by doing this.

分类器中的类是互斥的.在系统内部，系统正在尝试找出使分类器的训练数据中的一个类的正面示例与所有其他示例不同的原因.

Classes within a classifier are meant to be mutually exclusive. Internally the system is trying to figure out what makes the positive examples of one class different from all the other examples in a classifier's training data.

如果系统在单个分类器的多个类别中发现图像文件的精确重复，它将用作两个类别的肯定示例.确切的重复项由图像文件的校验和确定.

If the system discovers an exact duplicate of an image file in more than one class of a single classifier , it will use it as a positive example of both classes. Exact duplicates are determined by the check sum of the image file.

这篇关于单个图像可以成为多个类别的正面示例吗?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！