findingContours.py

# Getting contours  
im2, contours, hierarchy = cv2.findContours(edges, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

# Finding contour of biggest rectangle
# Otherwise return corners of original image
# Don't forget on our 5px border!
height = edges.shape[0]
width = edges.shape[1]
MAX_COUNTOUR_AREA = (width - 10) * (height - 10)

# Page fill at least half of image, then saving max area found
maxAreaFound = MAX_COUNTOUR_AREA * 0.5

# Saving page contour
pageContour = np.array([[5, 5], [5, height-5], [width-5, heigh-5], [widt-5, 5]])

# Go through all contours
for cnt in contours:
    # Simplify contour
    perimeter = cv2.arcLength(cnt, True)
    approx = cv2.approxPolyDP(cnt, 0.03 * perimeter, True)

    # Page has 4 corners and it is convex
    # Page area must be bigger than maxAreaFound 
    if (len(approx) == 4 and
            cv2.isContourConvex(approx) and
            maxAreaFound < cv2.contourArea(approx) < MAX_COUNTOUR_AREA):

        maxAreaFound = cv2.contourArea(approx)
        pageContour = approx

# Result in pageConoutr (numpy array of 4 points):