["python","image","opencv","image-processing","computer-vision"]
How does one convert a grayscale image to RGB in OpenCV (Python)?

I'm learning image processing using OpenCV for a realtime application. I did some thresholding on an image and want to label the contours in green, but they aren't showing up in green because my image is in black and white. Early in the program I used gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) to convert from RGB to grayscale, but to go back I'm confused, and the function backtorgb = cv2.cvtColor(gray,cv2.CV_GRAY2RGB) is giving: AttributeError: 'module' object has no attribute 'CV_GRAY2RGB'. The code below does not appear to be drawing contours in green. Is this because it's a grayscale image? If so, can I convert the grayscale image back to RGB to visualize the contours in green? import numpy as np import cv2 import time cap = cv2.VideoCapture(0) while(cap.isOpened()): ret, frame = cap.read() gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) ret, gb = cv2.threshold(gray,128,255,cv2.THRESH_BINARY) gb = cv2.bitwise_not(gb) contour,hier = cv2.findContours(gb,cv2.RETR_CCOMP,cv2.CHAIN_APPROX_SIMPLE) for cnt in contour: cv2.drawContours(gb,[cnt],0,255,-1) gray = cv2.bitwise_not(gb) cv2.drawContours(gray,contour,-1,(0,255,0),3) cv2.imshow('test', gray) if cv2.waitKey(1) & 0xFF == ord('q'): break cap.release() cv2.destroyAllWindows()
I am promoting my comment to an answer: The easy way is: You could draw in the original 'frame' itself instead of using gray image. The hard way (method you were trying to implement): backtorgb = cv2.cvtColor(gray,cv2.COLOR_GRAY2RGB) is the correct syntax.