从图像中提取信息
有哪些快速且可靠的方法来提取图像信息？我一直在修改 OpenCV，这似乎是迄今为止最好的路线，而且它还具有 Python 绑定。
因此，更具体地说，我想确定我能了解图像中的内容。例如，haar 面部检测和全身检测分类器就很棒 - 现在我可以判断图像中很可能存在面部和/或人以及大约有多少。
好的 - 还有什么 - 是否有任何建筑物怎么样？如果有的话，它们看起来是什么 - 小屋、办公楼等？是否可见天空、草地、树木等？
根据我所读到的有关训练分类器来检测对象的内容，使用 10,000 个左右的错误图像和 5,000 个左右的正确样本来训练分类器似乎是一个相当费力的过程。
我希望周围已经有一些像样的东西，而不必自己为一堆不同的对象做这一切 - 或者还有其他方法来处理这类事情吗？
What are some fast and somewhat reliable ways to extract information about images? I've been tinkering with OpenCV and this seems so far to be the best route plus it has Python bindings.
So to be more specific I'd like to determine what I can about what's in an image. So for example the haar face detection and full body detection classifiers are great - now I can tell that most likely there are faces and / or people in the image as well as about how many.
okay - what else - how about whether there are any buildings and if so what do they seem to be - huts, office buildings etc? Is there sky visible, grass, trees and so forth.
From what I've read about training classifiers to detect objects, it seems like a rather laborious process 10,000 or so wrong images and 5,000 or so correct samples to train a classifier.
I'm hoping that there are some decent ones around already instead of having to do this all myself for a bunch of different objects - or is there some other way to go about this sort of thing?
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如果不进一步澄清您正在分析的图像类型和目的，您的问题很难回答。
这篇文章的语气似乎是你对修补感兴趣——那很好。如果您想进行修改，一个示例应用程序可能是使用小波分析进行虹膜识别。您还可以尝试运动追踪；我已经使用示例项目在 OpenCV 中做到了这一点，这很有趣。您可以尝试图像分割以进行场景分析；拍摄一张户外照片并根据纹理和/或颜色分割图像。
对于训练集必须有多大，没有硬性数字。它高度依赖于应用程序。几百张图像可能就足够了。
Your question is difficult to answer without more clarification about the types of images you are analyzing and your purpose.
The tone of the post seems that you are interested in tinkering -- that's fine. If you want to tinker, one example application might be iris identification using wavelet analysis. You can also try motion tracking; I've done that in OpenCV using the sample projects, and it is kind of interesting. You can try image segmentation for the purpose of scene analysis; take an outdoor photo and segment the image according to texture and/or color.
There is no hard number for how large your training set must be. It is highly application dependent. A few hundred images may suffice.