3H proficient in opencv (VI) - image stacking

0、 preparation

Right click the new project , choice Python File, Create a new one Python file , Then at the beginning import cv2 Import cv2 library ,import numpy And rename to np.

import cv2import numpy as np

We also need to know where OpenCV in , The direction of the coordinate axis is x Shaft to the right ,y Axis down , The coordinate origin is in the upper left corner , For example, the following one is 640 Pixels , Wide for 480 Pixel image .OK, Let's begin with this section .

1、 Stack horizontally

call np Of hstack() Horizontal stack method , The parameter is the image we want to stack , The number of parameters is the number we want to stack .

img=cv2.imread("Resources/lena.png")imgHor=np.hstack((img,img))cv2.imshow("Horizontal",imgHor)cv2.waitKey(0)

Run to see the effect , Because the parameter we entered is (img,img), So it's the horizontal splicing of two original drawings .

Let's change it to a horizontal three ：imgHor=np.hstack((img,img,img))

2、 Stack vertically

call np Of vstack() Vertical stack method , The parameter is the image we want to stack , The number of parameters is the number we want to stack .

img=cv2.imread("Resources/lena.png")imgVer=np.vstack((img,img))cv2.imshow("Vertical",imgVer)cv2.waitKey(0)

Run to see the effect , Because the parameter we entered is (img,img), So it's vertical splicing of two original drawings .

Empathy , We can change it to three vertical ：imgVer=np.vstack((img,img,img))

3、 Image stack stack

If you just use numpy Stack functions , Images of different sizes and channels cannot be stacked , So we need to implement a stacking method ourselves , Here is the template , It can achieve the effect we want , We don't need to understand this code , Because if you understand it, you can't get any useful information , Just know how to use it .

def stackImages(scale,imgArray):    rows = len(imgArray)    cols = len(imgArray[0])    rowsAvailable = isinstance(imgArray[0], list)    width = imgArray[0][0].shape[1]    height = imgArray[0][0].shape[0]    if rowsAvailable:        for x in range ( 0, rows):            for y in range(0, cols):                if imgArray[x][y].shape[:2] == imgArray[0][0].shape [:2]:                    imgArray[x][y] = cv2.resize(imgArray[x][y], (0, 0), None, scale, scale)                else:                    imgArray[x][y] = cv2.resize(imgArray[x][y], (imgArray[0][0].shape[1], imgArray[0][0].shape[0]), None, scale, scale)                if len(imgArray[x][y].shape) == 2: imgArray[x][y]= cv2.cvtColor( imgArray[x][y], cv2.COLOR_GRAY2BGR)        imageBlank = np.zeros((height, width, 3), np.uint8)        hor = [imageBlank]*rows        hor_con = [imageBlank]*rows        for x in range(0, rows):            hor[x] = np.hstack(imgArray[x])        ver = np.vstack(hor)    else:        for x in range(0, rows):            if imgArray[x].shape[:2] == imgArray[0].shape[:2]:                imgArray[x] = cv2.resize(imgArray[x], (0, 0), None, scale, scale)            else:                imgArray[x] = cv2.resize(imgArray[x], (imgArray[0].shape[1], imgArray[0].shape[0]), None,scale, scale)            if len(imgArray[x].shape) == 2: imgArray[x] = cv2.cvtColor(imgArray[x], cv2.COLOR_GRAY2BGR)        hor= np.hstack(imgArray)        ver = hor    return ver

Horizontal and vertical stack

• This method has two parameters , The first is the scaling of the original image ,0.5 Is to shrink 1 times ,2 Just zoom in 1 times , It's easy to understand ;
• The second parameter is the matrix of the image stack , You can write any row and any column , The number of columns must be the same , Otherwise, it cannot form a matrix .
• In the following code , We just built 2 Row one-dimensional matrix , Each line is three images .

img=cv2.imread("Resources/lena.png")imgStcak=stackImages(0.5,([img,img,img],[img,img,img]))cv2.imshow("ImgStack",imgStcak)cv2.waitKey(0)

Let's run and see the effect ：

Since this method can combine images of different channels , That is, grayscale images and color images can be stacked together . Then let's try ：

img=cv2.imread("Resources/lena.png")imgGray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)imgStcak=stackImages(0.5,([img,imgGray,img],[img,img,img]))cv2.imshow("ImgStack",imgStcak)cv2.waitKey(0)

cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) Is to convert the original color image into gray image , from 3 The channel becomes 1 passageway . Then we replace one of them in the parameter matrix img. Let's run and see the effect ：

The content of section 6 , It's simple and interesting , There are many applications in life . A thousand eyes is better than a thousand hands , Go and knock it again ~