Background removal from webcam OPENCV PYTHON - python-3.x

Question

I'm creating a script that will read the state of a supermarket and tell me if there is products missing.
for example in the image below there is some places where there is products missing. I'm using FAST method to find all the corners in the frame. but sometimes the scripts detects the floor corners. What I want to do is remove the floor from the frame before I find the corners.
import cv2
import numpy as np
image = cv2.imread('gondola_imagem.jpeg')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
fast = cv2.FastFeatureDetector_create()
# Obtain Key points, by default non max suppression is On
# to turn off set fast.setBool('nonmaxSuppression', False)
keypoints = fast.detect(gray, None)
print ("Number of keypoints Detected: ", len(keypoints))
image = cv2.drawKeypoints(image, keypoints, None,
flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
cv2.imshow('Feature Method - FAST', image)
cv2.waitKey()
cv2.destroyAllWindows()

Answer 1

You can use a mask to remove the areas you are not interested. For example with the following image as a mask you can get the bellow results.
Mask
Result
Code is as follow:
import numpy as np
import cv2
image = cv2.imread('test.jpg')
mask = cv2.imread('mask.jpg', 0)
cv2.imshow('Original', image)
cv2.imshow('Mask', mask)
res = cv2.bitwise_and(image,image,mask = mask)
gray = cv2.cvtColor(res, cv2.COLOR_BGR2GRAY)
fast = cv2.FastFeatureDetector_create()
# Obtain Key points, by default non max suppression is On
# to turn off set fast.setBool('nonmaxSuppression', False)
keypoints = fast.detect(gray, None)
print ("Number of keypoints Detected: ", len(keypoints))
image = cv2.drawKeypoints(image, keypoints, None,
flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
cv2.imwrite('result.jpg', image)
cv2.imshow('Feature Method - FAST', image)
cv2.waitKey()
cv2.destroyAllWindows()
Edit:
If you want to do this in realtime (video from webcam) you just need to do it for every frame you get from the video camera. As long as the camera is not moving you should be able to use the same mask for all the frames. You could make the code above a function and then call it with an image as a parameter, as per the following code:
import numpy as np
import cv2
cap = cv2.VideoCapture(0)
while(True):
# Capture frame-by-frame
ret, frame = cap.read()
# Following function will have to be created with the previews code
CallFunctionToPreviewsCode(frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# When everything done, release the capture
cap.release()
cv2.destroyAllWindows()
The code above was taken from OpenCV Python-Tutorials It is a good place for learning OpenCV for Python programming language.