如何在 OpenCV(Python)中将灰度图像转换为 RGB?

问题描述

我正在学习使用 OpenCV 进行实时应用程序的图像处理.我对图像进行了一些阈值处理，并希望将轮廓标记为绿色，但它们没有以绿色显示，因为我的图像是黑白的.

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.

在程序的早期，我使用 gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) 将 RGB 转换为灰度，但返回时我很困惑，函数 backtorgb = cv2.cvtColor(gray,cv2.CV_GRAY2RGB) 给:

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' 对象没有属性 'CV_GRAY2RGB'.

下面的代码似乎没有以绿色绘制轮廓.这是因为它是灰度图像吗?如果是这样，我可以将灰度图像转换回 RGB 以显示绿色的轮廓吗?

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()

推荐答案

我将我的评论推广到一个答案:

I am promoting my comment to an answer:

简单的方法是:

您可以在原始框架"本身中绘制，而不是使用灰色图像.

You could draw in the original 'frame' itself instead of using gray image.

艰难的方式(您尝试实施的方法):

The hard way (method you were trying to implement):

backtorgb = cv2.cvtColor(gray,cv2.COLOR_GRAY2RGB) 是正确的语法.

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