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使用 opencv (ssim) 进行 Python 质量检查

[英]Python quality inspection with opencv (ssim)

I'm currently an intern at a quality inspector company.我目前在一家质检公司实习。 My job is to write a program that can detect faulty products (for example, missing screw).我的工作是编写一个程序来检测有缺陷的产品(例如,缺少螺丝)。 They take a picture of every single product.他们为每一件产品拍照。 My idea is that I choose an image which could serve as a benchmark and I would compare the other images to that, with the SSIM score, and maybe display the faulty part with a rectangle.我的想法是我选择一个可以作为基准的图像,我会将其他图像与 SSIM 分数进行比较,并可能用矩形显示有缺陷的部分。 Is this a viable idea?这是一个可行的想法吗? (Its a strange internship, because it seems like I'm the only one who can code there...) that's why I'm asking here. (这是一个奇怪的实习,因为似乎我是唯一可以在那里编码的人......)这就是我在这里问的原因。

It sounds good idea if your goal is to classify different objects within images comparing benchmark image.如果您的目标是在比较基准图像的图像中对不同的对象进行分类,这听起来不错。 But in my experience, SSIM score was sensitive to angle, light or environment.但根据我的经验,SSIM 分数对角度、光线或环境很敏感。

So in conclusion, if your goal is to classify different objects in images, your idea would work.所以总而言之,如果您的目标是对图像中的不同对象进行分类,那么您的想法会奏效。 But if your goal is to classify exactly same objects, it might not be able to classify.但是,如果您的目标是对完全相同的对象进行分类,则它可能无法分类。

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