Image Processing

#Fixing Perspective #Perspective Transform

def fixPerspective(img, border,ref,ratio=8.5/11.0):
	"""Returns img skewed to the border."""
	out = img.copy()
	#Rotate the array until the reference is first
	while tuple(border[0])!=tuple(ref):
		border = rotateList(border,1)

	#Copied from http://www.pyimagesearch.com/2014/08/25/4-point-opencv-getperspective-transform-example/
	(tl, tr, br, bl) = border
	# compute the width of the new image, which will be the
	# maximum distance between bottom-right and bottom-left
	# x-coordiates or the top-right and top-left x-coordinates
	widthA = np.sqrt(((br[0] - bl[0]) ** 2) + ((br[1] - bl[1]) ** 2))
	widthB = np.sqrt(((tr[0] - tl[0]) ** 2) + ((tr[1] - tl[1]) ** 2))
	maxWidth = max(int(widthA), int(widthB))

	# compute the height of the new image, which will be the
	# maximum distance between the top-right and bottom-right
	# y-coordinates or the top-left and bottom-left y-coordinates
	heightA = np.sqrt(((tr[0] - br[0]) ** 2) + ((tr[1] - br[1]) ** 2))
	heightB = np.sqrt(((tl[0] - bl[0]) ** 2) + ((tl[1] - bl[1]) ** 2))
	maxHeight = max(int(heightA), int(heightB))

	# now that we have the dimensions of the new image, construct
	# the set of destination points to obtain a "birds eye view",
	# (i.e. top-down view) of the image, again specifying points
	# in the top-left, top-right, bottom-right, and bottom-left
	# order
	dst = np.array([
		[0, 0],
		[maxWidth - 1, 0],
		[maxWidth - 1, maxHeight - 1],
		[0, maxHeight - 1]], dtype = "float32")

	#Return Perspective Transform
	M = cv2.getPerspectiveTransform(np.array(border, dtype = "float32"), dst)
	out = cv2.warpPerspective(img.copy(), M, (maxWidth, maxHeight))
	return out

##Cropping

def cropImage(img,r):
	sizeX,sizeY,p = img.shape
	return img[r:sizeX-r,r:sizeY-r]

#Output Filter

def filterOut(img):
	out = cv2.cvtColor(img.copy(),cv2.COLOR_RGB2GRAY)
	out = cv2.adaptiveThreshold(out,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,cv2.THRESH_BINARY,11,2)
	return out