CODEWITHSUNDEEP
c++arraysimageopencvimage-processing
deptrai
deptrai

Reputation: 147

Blur content from a rectangle with Opencv

in the following rectangle function, rectangles are drawn.

// Draw the predicted bounding box
void drawPred(int classId, float conf, int left, int top, int right, int bottom, Mat& frame)
{
    //Draw a rectangle displaying the bounding box
    rectangle(frame, Point(left, top), Point(right, bottom), Scalar(255, 178, 50),LINE_4);

    //bluring region
    cout << frame; 

    //Get the label for the class name and its confidence
    string label = format("%.2f", conf);
    if (!classes.empty())
    {
        CV_Assert(classId < (int)classes.size());
        label = classes[classId] + ":" + label;
    }

    //Display the label at the top of the bounding box
    int baseLine;
    Size labelSize = getTextSize(label, FONT_ITALIC, 0.5, 1, &baseLine);
    top = max(top, labelSize.height);
    putText(frame, label, Point(left, top), FONT_ITALIC, 0.5, Scalar(255, 255, 255), 1);
}

frame here is a multi-array of the image. Point(left, top) is the top-left point of the rectangle.
I would like to censor everything in this rectangle in the form of a blur. Since I come from Python programming, it is a bit difficult to define the array of these rectangles. It would be very nice if you could help me. Thank you very much and best regards.

Upvotes: 7

Views: 5381

Answers (2)

nathancy
nathancy

Reputation: 46600

Here is the Python equivalent to @HansHirse's answer. The idea is the same except we use Numpy slicing to obtain the ROI

import cv2

# Read in image
image = cv2.imread('1.png')

# Create ROI coordinates
topLeft = (60, 40)
bottomRight = (340, 120)
x, y = topLeft[0], topLeft[1]
w, h = bottomRight[0] - topLeft[0], bottomRight[1] - topLeft[1]

# Grab ROI with Numpy slicing and blur
ROI = image[y:y+h, x:x+w]
blur = cv2.GaussianBlur(ROI, (51,51), 0) 

# Insert ROI back into image
image[y:y+h, x:x+w] = blur

cv2.imshow('blur', blur)
cv2.imshow('image', image)
cv2.waitKey()

Upvotes: 10

HansHirse
HansHirse

Reputation: 18895

The way to go is setting up a corresponding region of interest (ROI) by using cv::Rect. Since you already have your top left and bottom right locations as cv::Points, you get this more or less for free. Afterwards, just use - for example - cv::GaussianBlur only on that ROI. Using the C++ API, this approach works for a lot of OpenCV methods.

The code is quite simple, see the following snippet:

// (Just use your frame instead.)
cv::Mat image = cv::imread("path/to/your/image.png");

// Top left and bottom right cv::Points are already defined.
cv::Point topLeft = cv::Point(60, 40);
cv::Point bottomRight = cv::Point(340, 120);

// Set up proper region of interest (ROI) using a cv::Rect from the two cv::Points.
cv::Rect roi = cv::Rect(topLeft, bottomRight);

// Only blur image within ROI.
cv::GaussianBlur(image(roi), image(roi), cv::Size(51, 51), 0);

For some exemplary input like this

Input

the above code generates the following output:

Output

Hope that helps!

Upvotes: 8

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