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in AI and Deep Learning by (50.2k points)

I have read a fair amount about Haar training and I'm not clear on how many images one should use for the positive and negative sample sets. I see it recommended to use many images, some people recommend thousands. I'm also unclear about whether the number of positive and negative sample images should be the same?

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by (108k points)

Here is the best tutorial on Haartraining:

It says they used 5000 for positive and 3000 for negative.

This link says 3000 for positive and 5000 for negative. Anyway, a higher number of images improves the accuracy, but it also increases training time.

You can also refer to this for training your own OpenCV haar classifier:

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