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Is Haar cascade classifier suitable for bottle label detection?

Can OpenCV's Haar feature-based cascade classifiers be trained to detect labels in the bottle's body?

I've been struggling to create my own detector heuristically by using edge detectors such as Canny, Sobel, Laplacian and HED.

But I've found that a bottle's labels isn't so trivial to describe by its edges as I have imagined, neither I can trust edge detectors since most of them is dependent upon hysteresis thresholding values.

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So I was wondering whether I should try another approach using Haar cascade.

I have never trained a Haar classifier by myself. I've been told that it might work well for blocky objects.

How many positives and negatives samples do I need?