I draw some rectangles in OpenCV and put text in them. My general approach looks like this:
# Draw rectangle p1(x,y) p2(x,y) Student name box
cv2.rectangle(frame, (500, 650), (800, 700), (42, 219, 151), cv2.FILLED )
font = cv2.FONT_HERSHEY_DUPLEX
cv2.putText(frame, name, (510, 685), font, 1.0, (255, 255, 255), 1
Everything works so far. The only thing is, that the opacity in all boxes is at 100 %. My question is: How can I change the opacity?
The final result should look like this:
I would like to add a small optimization to the @HansHirse answer, Instead of creating the canvas for whole image, we can crop the rectangle first from the src image and then later swap it with the cv2.addWeighted result as:
import cv2
import numpy as np
img = cv2.imread("lena.png")
# First we crop the sub-rect from the image
x, y, w, h = 100, 100, 200, 100
sub_img = img[y:y+h, x:x+w]
white_rect = np.ones(sub_img.shape, dtype=np.uint8) * 255
res = cv2.addWeighted(sub_img, 0.5, white_rect, 0.5, 1.0)
# Putting the image back to its position
img[y:y+h, x:x+w] = res
EDIT: Since this answer seems to have some importance, I decided to edit it again, incorporating the proper blending from ZdaR's answer, which initially was an improvement to my original answer (check the timeline if interested). Also, I incorporated Jon's comments to include an example of a non-rectangular shape.
At least from my point of view, built-in functions like cv2.rectangle don't support opacity, even on BGRA images, see here. So, as I described in the linked answer, the only possibility to achieve, what you want, is to use the cv2.addWeighted function. You can simply set up a blank mask image, and draw all possible shapes on that. Doing so, you can also use that as an actual mask to limit the blending to that part only.
An example could be:
import cv2
import numpy as np
# Load image
img = cv2.imread('images/paddington.png')
# Initialize blank mask image of same dimensions for drawing the shapes
shapes = np.zeros_like(img, np.uint8)
# Draw shapes
cv2.rectangle(shapes, (5, 5), (100, 75), (255, 255, 255), cv2.FILLED)
cv2.circle(shapes, (300, 300), 75, (255, 255, 255), cv2.FILLED)
# Generate output by blending image with shapes image, using the shapes
# images also as mask to limit the blending to those parts
out = img.copy()
alpha = 0.5
mask = shapes.astype(bool)
out[mask] = cv2.addWeighted(img, alpha, shapes, 1 - alpha, 0)[mask]
# Visualization
cv2.imshow('Image', img)
cv2.imshow('Shapes', shapes)
cv2.imshow('Output', out)
cv2.waitKey(0)
cv2.destroyAllWindows()
The original Paddington img:
The intermediate image to draw the shapes on shapes:
And, the final result out:
After drawing the shapes and blending the images, you can add your texts as before.
Hope that helps!
Simply install pyshine and use putBText, it has following inputs and output.
pip install pyshine
"""
Inputs:
img: cv2 image img
text_offset_x, text_offset_x: X,Y location of text start
vspace, hspace: Vertical and Horizontal space between text and box boundaries
font_scale: Font size
background_RGB: Background R,G,B color
text_RGB: Text R,G,B color
font: Font Style e.g. cv2.FONT_HERSHEY_DUPLEX,cv2.FONT_HERSHEY_SIMPLEX,cv2.FONT_HERSHEY_PLAIN,cv2.FONT_HERSHEY_COMPLEX
cv2.FONT_HERSHEY_TRIPLEX, etc
thickness: Thickness of the text font
alpha: Opacity 0~1 of the box around text
gamma: 0 by default
Output:
img: CV2 image with text and background
"""
Example tested on Python3 and complete demonstration is here:
import pyshine as ps
import cv2
image = cv2.imread('lena.jpg')
text = 'HELLO WORLD!'
image = ps.putBText(image,text,text_offset_x=20,text_offset_y=20,vspace=10,hspace=10, font_scale=2.0,background_RGB=(0,250,250),text_RGB=(255,250,250))
cv2.imshow('Output', image)
cv2.imwrite('out.jpg',image)
cv2.waitKey(0)
import pyshine as ps
import cv2
import time
image = cv2.imread('lena.jpg')
text = 'ID: '+str(123)
image = ps.putBText(image,text,text_offset_x=20,text_offset_y=20,vspace=10,hspace=10, font_scale=1.0,background_RGB=(228,225,222),text_RGB=(1,1,1))
text = str(time.strftime("%H:%M %p"))
image = ps.putBText(image,text,text_offset_x=image.shape[1]-170,text_offset_y=20,vspace=10,hspace=10, font_scale=1.0,background_RGB=(228,225,222),text_RGB=(1,1,1))
text = '6842'
image = ps.putBText(image,text,text_offset_x=80,text_offset_y=372,vspace=10,hspace=10, font_scale=1.0,background_RGB=(228,225,222),text_RGB=(255,255,255))
text = "Lena Fors'en"
image = ps.putBText(image,text,text_offset_x=80,text_offset_y=425,vspace=20,hspace=10, font_scale=1.0,background_RGB=(20,210,4),text_RGB=(255,255,255))
text = 'Status: '
image = ps.putBText(image,text,text_offset_x=image.shape[1]-130,text_offset_y=200,vspace=10,hspace=10, font_scale=1.0,background_RGB=(228,225,222),text_RGB=(255,255,255))
text = 'On time'
image = ps.putBText(image,text,text_offset_x=image.shape[1]-130,text_offset_y=242,vspace=10,hspace=10, font_scale=1.0,background_RGB=(228,225,222),text_RGB=(255,255,255))
text = 'Attendence: '
image = ps.putBText(image,text,text_offset_x=image.shape[1]-200,text_offset_y=394,vspace=10,hspace=10, font_scale=1.0,background_RGB=(228,225,222),text_RGB=(255,255,255))
text = '96.2% '
image = ps.putBText(image,text,text_offset_x=image.shape[1]-200,text_offset_y=436,vspace=10,hspace=10, font_scale=1.0,background_RGB=(228,225,222),text_RGB=(255,255,255))
cv2.imshow('Output', image)
cv2.imwrite('out.jpg',image)
cv2.waitKey(0)
A simpler solution (although a bit less efficient in terms of memory) is:
alpha*img + (1-alpha)*img_cpy In this way each original pixel will not change it's value (since alpha*px + (1-alpha)px = px), whereas pixels which were drawn on will be affected by the overlay.
This eliminates the need to perform crops and pesky calculations seen in the other answers.
...and applying to to the OP's code:
frame_cpy = frame.copy()
cv2.rectangle(frame, (500, 650), (800, 700), (42, 219, 151), cv2.FILLED)
font = cv2.FONT_HERSHEY_DUPLEX
cv2.putText(frame, name, (510, 685), font, 1.0, (255, 255, 255), 1)
alpha = 0.4
frame_overlay=cv2.addWeighted(frame, alpha, frame_cpy,1-alpha, gamma=0)
cv2.imshow("overlay result",frame_overlay)
cv2.waitKey(0)
Disclaimer: this answer was inspired by a post on www.pyimagesearch.com
