OpenCV has AdaBoost algorithm function.
And gpu version also is provided.
For using detection, we prepare the trained xml file.
Although we can train some target using adaboost algorithm in opencv functions, there are several trained xml files in the opencv folder. (mostly in opencv/sources/data/haarcascades )
I will use "haarcascade_frontalface_alt.xml" file for face detection example.
gpu and cpu both versions use xml file.
more detail refer to this source code.
The source code is included 2 version of cpu and gpu.
result is ..
gpu is faster than cpu version (but exactly they may not be same condition..)
blue boxes are result of cpu.
red boxes are results of gpu.
The results are not important because it can be different by parameters values.
cvtColor, CascadeClassifier, CascadeClassifier_GPU, detectMultiScale,
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As you can see in the following video, I created a class that stitching n cameras in real time. https://www.youtube.com/user/feelmare/sear...
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* Introduction - The solution shows panorama image from multi images. The panorama images is processing by real-time stitching algorithm...
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