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[RaiMan <question689217@xxxxxxxxxxxxxxxxxxxxx>]

Question #689217 on Sikuli changed:
https://answers.launchpad.net/sikuli/+question/689217

RaiMan proposed the following answer:
--- it will not easy to detect by capture image, if background changes
therefor it is strongly recommended, to have as little background in the image as possible. The background pixels should not be more than 10 - 20% of the whole image pixels. The more background pixels, the higher the risk for not found or false positives.
This is usually possible with precise capturing. In 2.1.0 there is a feature in the IDE Preview, to rework the image after capture.

 --- whether you can want to import whole world of opencv (running Python)
As mentioned, the whole world of OpenCV is already available at the Java level. The Python project is only a server-based implementation of SikuliX that you can use the SikuliX features in the real Python environment. Of course, a user can feel free in this case to import Python OpenCV, but SikuliX will always use the features on the Java level. 

BTW: A main problem with image compare (matchTemplate) is, when the same
pixel structures differ only in color. The match scores (values between
0 and 1) might then only differ by less than 0.0001. This cannot be
solved with feature point extraction. The most prominent example are
buttons with different states signalled by color.

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