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.
53 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.
1Something 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.
