Image overlay | TheAILearner

In the previous blog, we learned how to overlay an image to another image using OpenCV cv2.addWeighted() function. But this approach is limited to rectangular ROI. In this blog, we will learn how to overlay non-rectangular ROI to another image.

Task:

Put the TheAILearner text image(shown in the left) above an image (Right one).

Because the TheAILearner text is non-rectangular, we will be using OpenCV cv2.bitwise_and(img1, img2, mask) where the mask is an 8-bit single channel array, that specifies elements of the output array to be changed.

For Bitwise_and you need to know the following two rules

Black + Any Color = Black
White + Any Color = That Color

Now, let’s see step by step how to do this

First load the two images

img1 = cv2.imread('D:/downloads/pasta_screen.jpg')
img2 = cv2.imread('D:/downloads/logo.jpg')

1 2	img1 = cv2.imread('D:/downloads/pasta_screen.jpg') img2 = cv2.imread('D:/downloads/logo.jpg')

Select the region in the image where you want to put the logo. Here, I am putting this in the top left corner.

rows,cols,channels = img2.shape
roi = img1[0:rows, 0:cols ]

1 2	rows,cols,channels = img2.shape roi = img1[0:rows, 0:cols ]

Now, we will create a mask. You can create a mask by a number of ways but here we will be using thresholding for this as shown in the code below. We will also create an inverse mask. Depending on the image you need to change the thresholding function parameters.

img2gray = cv2.cvtColor(img2,cv2.COLOR_BGR2GRAY)
ret, mask = cv2.threshold(img2gray, 200, 255, cv2.THRESH_BINARY_INV)
mask_inv = cv2.bitwise_not(mask)

img2gray = cv2.cvtColor(img2,cv2.COLOR_BGR2GRAY)

ret, mask = cv2.threshold(img2gray, 200, 255, cv2.THRESH_BINARY_INV)

mask_inv = cv2.bitwise_not(mask)

The mask and mask_inv looks like this

Now black out the area of logo in the roi created above using the bitwise_and as shown in the code below

img1_bg = cv2.bitwise_and(roi,roi,mask = mask_inv)

1	img1_bg = cv2.bitwise_and(roi,roi,mask = mask_inv)

This looks like this

Now, we will extract the logo region (with colors) from the logo image using the following code

img2_fg = cv2.bitwise_and(img2,img2,mask = mask)

1	img2_fg = cv2.bitwise_and(img2,img2,mask = mask)

The output looks like this

Now, we will simply add the above two images because black has intensity 0 so adding this doesn’t change anything and outputs the same color. This is done using the following code

out_img = cv2.add(img1_bg,img2_fg)
img1[0:rows, 0:cols ] = out_img

1 2	out_img = cv2.add(img1_bg,img2_fg) img1[0:rows, 0:cols ] = out_img

The final output looks like this

So, using these simple bitwise operations we can overlay an image to another. Be careful while creating the mask as it entirely depends on the image. According to the image you need to make adjustments to the thresholding function parameters.

Hope you enjoy reading.

If you have any doubt/suggestion please feel free to ask and I will do my best to help or improve myself. Good-bye until next time.

In this blog, we will learn how to add an image to a live camera feed using OpenCV-Python. Also known as Image Blending. In this we take the weighted sum of two images. These weights give a feeling of blending or transparency.

Images are added as per the equation below:

Since an image is a matrix so for the above equation to satisfy, both img1 and img2 must be of equal size.

OpenCV has a built-in function that does the exact same thing as shown below

output = cv2.addWeighted(img1, weight_img1, img2, weight_img2, gamma)
# gamma is the scalar added to each sum

1 2	output = cv2.addWeighted(img1, weight_img1, img2, weight_img2, gamma) # gamma is the scalar added to each sum

The idea is that first, we will select which image we want to overlay (another image will serve as the background). Then we need to select the region in the background image where we want to put the overlay image. Add this selected region with the overlay image using the above equation. At last change the region in the background image with the result obtained in the previous line.

I hope you understand the idea. Now, let’s get started

Task:

Overlay a white square image on the live webcam feed according to different weights. Instead of manually giving weights, set two keys which on pressing increase or decrease the weights.

Steps:

Take an image which you want to overlay. Here, I have used a small white square created using numpy. You can use any.
Open the camera using cv2.VideoCapture()
Initialize the weights (alpha).
Until the camera is opened
- Read the frame using cap.read()
- Select the region in the frame where we want to add the image and add the images using cv2.addWeighted()
- Change the region in the frame with the result obtained
- Display the current value of weights using cv2.putText()
- Display the image using cv2.imshow()
- On pressing ‘a’ increase the value of alpha by 0.1 and decrease by the same amount on pressing ‘d’
- Press ‘q’ to break

Code:

import cv2
import numpy as np
 
# create an overlay image. You can use any image
foreground = np.ones((100,100,3),dtype='uint8')*255
# Open the camera
cap = cv2.VideoCapture(0)
# Set initial value of weights
alpha = 0.4
while True:
    # read the background
    ret, background = cap.read()
    background = cv2.flip(background,1)
    # Select the region in the background where we want to add the image and add the images using cv2.addWeighted()
    added_image = cv2.addWeighted(background[150:250,150:250,:],alpha,foreground[0:100,0:100,:],1-alpha,0)
    # Change the region with the result
    background[150:250,150:250] = added_image
    # For displaying current value of alpha(weights)
    font = cv2.FONT_HERSHEY_SIMPLEX
    cv2.putText(background,'alpha:{}'.format(alpha),(10,30), font, 1,(255,255,255),2,cv2.LINE_AA)
    cv2.imshow('a',background)
    k = cv2.waitKey(10)
    # Press q to break
    if k == ord('q'):
        break
    # press a to increase alpha by 0.1
    if k == ord('a'):
        alpha +=0.1
        if alpha >=1.0:
            alpha = 1.0
    # press d to decrease alpha by 0.1
    elif k== ord('d'):
        alpha -= 0.1
        if alpha <=0.0:
            alpha = 0.0
# Release the camera and destroy all windows         
cap.release()
cv2.destroyAllWindows()

import cv2

import numpy as np

# create an overlay image. You can use any image

foreground = np.ones((100,100,3),dtype='uint8')*255

# Open the camera

cap = cv2.VideoCapture(0)

# Set initial value of weights

alpha = 0.4

while True:

# read the background

ret, background = cap.read()

background = cv2.flip(background,1)

# Select the region in the background where we want to add the image and add the images using cv2.addWeighted()

added_image = cv2.addWeighted(background[150:250,150:250,:],alpha,foreground[0:100,0:100,:],1-alpha,0)

# Change the region with the result

background[150:250,150:250] = added_image

# For displaying current value of alpha(weights)

font = cv2.FONT_HERSHEY_SIMPLEX

cv2.putText(background,'alpha:{}'.format(alpha),(10,30), font, 1,(255,255,255),2,cv2.LINE_AA)

cv2.imshow('a',background)

k = cv2.waitKey(10)

# Press q to break

if k == ord('q'):

break

# press a to increase alpha by 0.1

if k == ord('a'):

alpha +=0.1

if alpha >=1.0:

alpha = 1.0

# press d to decrease alpha by 0.1

elif k== ord('d'):

alpha -= 0.1

if alpha <=0.0:

alpha = 0.0

# Release the camera and destroy all windows

cap.release()

cv2.destroyAllWindows()

See the change in transparency by pressing keys ‘a’ and ‘d’. The output looks like this

You might encounter wrong values of alpha being displayed. This is because of Python’s floating point limitations.

Hope you enjoy reading. In the next blog, we will learn how to do the same for the non-rectangular region of interest.

If you have any doubt/suggestion please feel free to ask and I will do my best to help or improve myself. Good-bye until next time.

TheAILearner

Mastering Artificial Intelligence

Tag Archives: Image overlay

Image Overlays using Bitwise Operations OpenCV-Python

Task:

Add image to a live camera feed using OpenCV-Python

Task:

Steps:

Code: