Rotate image by 90, 180 or 270 degrees

问题:

I need to rotate an image by either 90, 180 or 270 degrees. In OpenCV4Android I can use:

Imgproc.getRotationMatrix2D(new Point(center, center), degrees, 1);
Imgproc.warpAffine(src, dst, rotationMatrix, dst.size());

However, this is a huge bottleneck in my image processing algorithm. Of course, a simple rotation by a multiple of 90 degrees is much simpler than the most general case of warpAffine, and can be done much more efficiently. For 180 degrees, for instance, I could use:

Core.flip(src, dst, -1);

where -1 means to flip about both horizontal and vertical axes. Is there a similar optimization I could use for 90 or 270 degree rotations?

回答1:

This is the first result when you Google it and none of these solutions really answer the question or is correct or succinct.

Core.rotate(Mat src, Mat dst, Core.ROTATE_90_CLOCKWISE); //ROTATE_180 or ROTATE_90_COUNTERCLOCKWISE

回答2:

I don't know the java api very well, this codes are developed by c++. The logics should be the same, use transpose + flip to rotate the image with 90n(n belongs to N = -minimum value of int, ....., -3, -2, -1, 0, 1, 2, 3, ..., max value of int)

/*
 *@brief rotate image by multiple of 90 degrees
 *
 *@param source : input image
 *@param dst : output image
 *@param angle : factor of 90, even it is not factor of 90, the angle
 * will be mapped to the range of [-360, 360].
 * {angle = 90n; n = {-4, -3, -2, -1, 0, 1, 2, 3, 4} }
 * if angle bigger than 360 or smaller than -360, the angle will
 * be map to -360 ~ 360.
 * mapping rule is : angle = ((angle / 90) % 4) * 90;
 *
 * ex : 89 will map to 0, 98 to 90, 179 to 90, 270 to 3, 360 to 0.
 *
 */
void rotate_image_90n(cv::Mat &src, cv::Mat &dst, int angle)
{   
   if(src.data != dst.data){
       src.copyTo(dst);
   }

   angle = ((angle / 90) % 4) * 90;

   //0 : flip vertical; 1 flip horizontal
   bool const flip_horizontal_or_vertical = angle > 0 ? 1 : 0;
   int const number = std::abs(angle / 90);          

   for(int i = 0; i != number; ++i){
       cv::transpose(dst, dst);
       cv::flip(dst, dst, flip_horizontal_or_vertical);
   }
}

Edit : Improve performance, thanks for the comments of TimZaman and the implementation of 1''

void rotate_90n(cv::Mat const &src, cv::Mat &dst, int angle)
{        
     CV_Assert(angle % 90 == 0 && angle <= 360 && angle >= -360);
     if(angle == 270 || angle == -90){
        // Rotate clockwise 270 degrees
        cv::transpose(src, dst);
        cv::flip(dst, dst, 0);
    }else if(angle == 180 || angle == -180){
        // Rotate clockwise 180 degrees
        cv::flip(src, dst, -1);
    }else if(angle == 90 || angle == -270){
        // Rotate clockwise 90 degrees
        cv::transpose(src, dst);
        cv::flip(dst, dst, 1);
    }else if(angle == 360 || angle == 0 || angle == -360){
        if(src.data != dst.data){
            src.copyTo(dst);
        }
    }
}

回答3:

This will rotate an image any number of degrees, using the most efficient means for multiples of 90.

    void
    rotate_cw(const cv::Mat& image, cv::Mat& dest, int degrees)
    {
        switch (degrees % 360) {
            case 0:
                dest = image.clone();
                break;
            case 90:
                cv::flip(image.t(), dest, 1);
                break;
            case 180:
                cv::flip(image, dest, -1);
                break;
            case 270:
                cv::flip(image.t(), dest, 0);
                break;
            default:
                cv::Mat r = cv::getRotationMatrix2D({image.cols/2.0F, image.rows/2.0F}, degrees, 1.0);
                int len = std::max(image.cols, image.rows);
                cv::warpAffine(image, dest, r, cv::Size(len, len));
                break; //image size will change
        }
    }

But with opencv 3.0, this is done by just via the cv::rotate command:

cv::rotate(image, dest, e.g. cv::ROTATE_90_COUNTERCLOCKWISE);

回答4:

Here is a solution using the Android API. Here, I am using it to rotate images from a camera which could be mounted in various orientations.

if (mCameraOrientation == 270) {
    // Rotate clockwise 270 degrees
    Core.flip(src.t(), dst, 0);
} else if (mCameraOrientation == 180) {
    // Rotate clockwise 180 degrees
    Core.flip(src, dst, -1);
} else if (mCameraOrientation == 90) {
    // Rotate clockwise 90 degrees
    Core.flip(src.t(), dst, 1);
} else if (mCameraOrientation == 0) {
    // No rotation
    dst = src;
}

回答5:

Here is my Python translation (and thanks to all the posters):

import cv2
def rot90(img, rotflag):
    """ rotFlag 1=CW, 2=CCW, 3=180"""
    if rotflag == 1:
        img = cv2.transpose(img)  
        img = cv2.flip(img, 1)  # transpose+flip(1)=CW
    elif rotflag == 2:
        img = cv2.transpose(img)  
        img = cv2.flip(img, 0)  # transpose+flip(0)=CCW
    elif rotflag ==3:
        img = cv2.flip(img, -1)  # transpose+flip(-1)=180
    elif rotflag != 0:  # if not 0,1,2,3
        raise Exception("Unknown rotation flag({})".format(rotflag))
    return img

回答6:

I wrote this Python version using Numpy only, which are much faster than using cv2.transpose() and cv2.flip().

def rotate_image_90(im, angle):
    if angle % 90 == 0:
        angle = angle % 360
        if angle == 0:
            return im
        elif angle == 90:
            return im.transpose((1,0, 2))[:,::-1,:]
        elif angle == 180:
            return im[::-1,::-1,:]
        elif angle == 270:
            return im.transpose((1,0, 2))[::-1,:,:]

    else:
        raise Exception('Error')

回答7:

You can rotate image using numpy rot90 function

like

def rotate_image(image,deg):
    if deg ==90:
        return np.rot90(image)
    if deg ==180:
        return np.rot90(image,2)
    if deg == 270:
        return np.rot90(image,-1) #Reverse 90 deg rotation

Hope this help ..

回答8:

Use the numpy.rot90,if you want 180 degrees,just do it twice.

import numpy as np
import cv2

img = cv2.imread('img.png',1)
cv2.imshow('',img)
cv2.waitKey(0)

img90 = np.rot90(img)
cv2.imshow('',img90)
cv2.waitKey(0)

回答9:

In python:

# import the necessary packages
import numpy as np
import cv2

# initialize the camera and grab a reference to the raw camera capture
vs = cv2.VideoCapture(0)
(ret, image_original) = vs.read()
image_rotated_90 = np.rot90(image_original)
image_rotated_180 = np.rot90(image_rotated_90)

# show the frame and press any key to quit the image frame
cv2.imshow("Frame", image_rotated_180)
cv2.waitKey(0)