title: Motion Detection in Python without OpenCV due to Sunlight
body: <p>Okay I know what might come to people's mind is initially that I use OpenCV to solve my problem - except that unfortunately I can't implement it in this case (I'm using a Raspberry PI + the camera module). I have a motion detection script, but the problem is throughout the day shadows are cast or sometimes the camera adjust it's sensitivity - which to the algorithm it detects as a movement. I'm trying to figure out what is a way I can get around this problem. Currently I take an image A and calculate the different between that and image B, and compute the entropy of those images, I do this for ten images average them to create a moving average so that the current image I can compare it to this average entropy if it's outside of 1 standard deviation I take this to be indicative of motion.</p>
  
  <p>I should add since I don't really understand OpenCV - is there potentially a way to have it compare two images and detect motion from that? In which case I'm already generating images as the camera is taking photos I could find a way to feed them to OpenCV using python and maybe get around my sunlight exposure issue?</p>
  
  <p>My current plan of attack is to try and average say the last ten frames into one and then compute the difference, is there a good way to do this in Python? Also say a dog is found in image 10, does that mean that for 10 images following even if it's gone in 11 it will still detect there is motion because the average of those ten frames till it is removed from the queue will have the dog present?</p>