In this article, we will discuss how to remove the black background and make it transparent in Python OpenCV.
cv2.cvtColor method
cv2.cvtColor() method is used to convert an image from one color space to another. There are more than 150 color-space conversion methods available in OpenCV.
Syntax: cv2.cvtColor(src, code[, dst[, dstCn]])
Parameters:
- src: Image
- code: It is the color space conversion code.
- dst: (optional), It is the output image of the same size and depth as src image.
- dstCn: (optional),It is the number of channels in the destination image
Return Value: It returns an image.
Image used for demonstration:
Stepwise Implementation:
Step 1: First of all, import the library OpenCV.
import cv2
Step 2: Now, import the image from your computer.
file_name = "#Image-Location"
Step 3: Then, read the image in OpenCV.
src = cv2.imread(file_name, 1)
Step 4: Then, convert the image background to gray image background.
tmp = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
Step 5: Moreover, apply the thresholding technique.
_,alpha = cv2.threshold(tmp,0,255,cv2.THRESH_BINARY)
Step 6: Further, use cv2.split() to split channels of colored image.
b, g, r = cv2.split(src)
Step 7: Later on, make a list of Red, Green, and Blue Channels and alpha.
rgba = [b,g,r, alpha]
Step 8: Next, use cv2.merge() to merge rgba into a coloured/multi-channeled image.
dst = cv2.merge(rgba,4)
Step 9: Finally, write and save to a new image location.
cv2.imwrite("#New-Image-Location", dst)
Below is the complete implementation:
Python3
# Import the library OpenCVimport cv2 # Import the imagefile_name = "gfg_black.png" # Read the imagesrc = cv2.imread(file_name, 1) # Convert image to image graytmp = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY) # Applying thresholding technique_, alpha = cv2.threshold(tmp, 0, 255, cv2.THRESH_BINARY) # Using cv2.split() to split channels # of coloured imageb, g, r = cv2.split(src) # Making list of Red, Green, Blue# Channels and alphargba = [b, g, r, alpha] # Using cv2.merge() to merge rgba# into a coloured/multi-channeled imagedst = cv2.merge(rgba, 4) # Writing and saving to a new imagecv2.imwrite("gfg_white.png", dst) |
Output:
