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Installing bgsegm for python3 My CMAKE includes: -- Python 2: -- Interpreter: /usr/bin/python2.7

Installing bgsegm for python3 My CMAKE includes: -- Python 2: -- Interpreter: /usr/bin/python2.7

Applied erosion and dilation to it and getting really good results!!

I am getting a lot of noise which seems to be just background content for example this is the actual background and this

I am currently running this to acquire images:

 fgbg = cv2.createBackgroundSubtractorMOG2(detectShadows=False)
 for frame in cam.camera.capture_continuous(raw, format="rgb", use_video_port=True):
    img = frame.array
    fgmask = fgbg.apply(img)

How can I go about choosing which images to save in the history. I want to build a function where I can select which images are background. For example initially the first 50 input images will be used as history for the subtractor and after that all masks that have under a certain threshold of difference will be used as history too. I basically do not want the new foreground images to be used as history is that possible?

I have written this code:

fgmask = fgbg.apply(img, bg_learning_rate)

# check if should learn from content
perc_black = np.count_nonzero(fgmask) / len(fgmask)
if perc_black > MOVEMENT_THRESH:
    # something is happening in image
    bg_learning_rate = 0
else:
    bg_learning_rate = -1

but this teaches the system to not use the next image in the model which is not that useful although highly probable that it will still feature a large object.

I am doing this to extract people from a static background.

See my code above!

I can tell you for a fact it won't be.

How to give createBackgroundSubtractorMOG2 selective history images. I am currently running this to acquire images: fg

Can you expand a bit? If I leave it to train on 500 images first of all. After that I set a blackness threshold and if i

How to give createBackgroundSubtractorMOG2 selective history images. I am currently running this to acquire images: fg

Unable to use background subtractor. I have installed opencv 3.3 when running python: import cv2 cv2.__version__ retu

http://vis-www.cs.umass.edu/fddb/ - This data set contains the annotations for 5171 faces in a set of 2845 images taken

How should I measure how well my CascadeClassifier is working? I am currently trying to optimise my CascadeClassifier us