How to convert a Binary Image to Grayscale and RGB using python?

I am working on hair removal from skin lesion images. Is there any way to convert binary back to rgb?

Original Image:

Mask Image:

I just want to restore the black area with the original image.

3 Answers

As I know binary images are stored in grayscale in opencv values 1-->255.

To create „dummy“ RGB images you can do: rgb_img = cv2.cvtColor(binary_img, cv.CV_GRAY2RGB)

I call them „dummy“ since in these images the red, green and blue values are just the same.

Something like this, but your mask is the wrong size (200x200 px) so it doesn't match your image (600x450 px):

#!/usr/local/bin/python3 from PIL import Image import numpy as np # Open the input image as numpy array npImage=np.array(Image.open("image.jpg")) # Open the mask image as numpy array npMask=np.array(Image.open("mask2.jpg").convert("RGB")) # Make a binary array identifying where the mask is black cond = npMask<128 # Select image or mask according to condition array pixels=np.where(cond, npImage, npMask) # Save resulting image result=Image.fromarray(pixels) result.save('result.png') 

I updated the Daniel Tremer's answer:

import cv2 opencv_rgb_img = cv2.cvtColor(opencv_image, cv2.COLOR_GRAY2RGB) 

opencv_image would be two dimension matrix like [width, height] because of binary.
opencv_rgb_img would be three dimension matrix like [width, height, color channel] because of RGB.