【使用OpenCV裁剪图像】

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裁剪是从图像中移除所有不需要的物体或区域。甚至可以突出显示图像的特定特征。

没有使用OpenCV进行裁剪的特定函数，NumPy数组切片是做这项工作的。读取的每个图像都存储在一个2D数组中(对于每个颜色通道)。简单地指定要裁剪区域的高度和宽度(以像素为单位)。

下面的代码片段展示了如何使用Python和c++裁剪图像。在本文中，您将进一步了解这些细节。

裁剪图像

Python

# Import packages
import cv2
import numpy as np

img = cv2.imread('test.jpg')
print(img.shape) # Print image shape
cv2.imshow("original", img)

# Cropping an image
cropped_image = img[80:280, 150:330]

# Display cropped image
cv2.imshow("cropped", cropped_image)

# Save the cropped image
cv2.imwrite("Cropped Image.jpg", cropped_image)

cv2.waitKey(0)
cv2.destroyAllWindows()

C++

// Include Libraries
#include<opencv2/opencv.hpp>
#include<iostream>

// Namespace nullifies the use of cv::function();
using namespace std;
using namespace cv;

int main()
{
    
    
	// Read image
	Mat img = imread("test.jpg");
	cout << "Width : " << img.size().width << endl;
	cout << "Height: " << img.size().height << endl;
	cout<<"Channels: :"<< img.channels() << endl;
	// Crop image
	Mat cropped_image = img(Range(80,280), Range(150,330));

	//display image
	imshow(" Original Image", img);
	imshow("Cropped Image", cropped_image);

	//Save the cropped Image
	imwrite("Cropped Image.jpg", cropped_image);

	// 0 means loop infinitely
	waitKey(0);
	destroyAllWindows();
	return 0;
}

使用裁剪技术将图像

分割网格

OpenCV中裁剪的一个实际应用是将图像分割成小块。使用循环从图像中裁剪出一个片段。

Python

img =  cv2.imread("test_cropped.jpg")
image_copy = img.copy() 
imgheight=img.shape[0]
imgwidth=img.shape[1]

C++

Mat img = imread("test_cropped.jpg");
Mat image_copy = img.clone();
int imgheight = img.rows;
int imgwidth = img.cols;

我们使用的patch的高度和宽度分别为76像素和104像素。内外循环的步幅(我们在图像中移动的像素数)等于我们所考虑的斑块的宽度和高度。

斑块

Python

M = 76
N = 104
x1 = 0
y1 = 0

for y in range(0, imgheight, M):
    for x in range(0, imgwidth, N):
        if (imgheight - y) < M or (imgwidth - x) < N:
            break
            
        y1 = y + M
        x1 = x + N

        # check whether the patch width or height exceeds the image width or height
        if x1 >= imgwidth and y1 >= imgheight:
            x1 = imgwidth - 1
            y1 = imgheight - 1
            #Crop into patches of size MxN
            tiles = image_copy[y:y+M, x:x+N]
            #Save each patch into file directory
            cv2.imwrite('saved_patches/'+'tile'+str(x)+'_'+str(y)+'.jpg', tiles)
            cv2.rectangle(img, (x, y), (x1, y1), (0, 255, 0), 1)
        elif y1 >= imgheight: # when patch height exceeds the image height
            y1 = imgheight - 1
            #Crop into patches of size MxN
            tiles = image_copy[y:y+M, x:x+N]
            #Save each patch into file directory
            cv2.imwrite('saved_patches/'+'tile'+str(x)+'_'+str(y)+'.jpg', tiles)
            cv2.rectangle(img, (x, y), (x1, y1), (0, 255, 0), 1)
        elif x1 >= imgwidth: # when patch width exceeds the image width
            x1 = imgwidth - 1
            #Crop into patches of size MxN
            tiles = image_copy[y:y+M, x:x+N]
            #Save each patch into file directory
            cv2.imwrite('saved_patches/'+'tile'+str(x)+'_'+str(y)+'.jpg', tiles)
            cv2.rectangle(img, (x, y), (x1, y1), (0, 255, 0), 1)
        else:
            #Crop into patches of size MxN
            tiles = image_copy[y:y+M, x:x+N]
            #Save each patch into file directory
            cv2.imwrite('saved_patches/'+'tile'+str(x)+'_'+str(y)+'.jpg', tiles)
            cv2.rectangle(img, (x, y), (x1, y1), (0, 255, 0), 1)

C++

int M = 76;
int N = 104;

int x1 = 0;
int y1 = 0;
for (int y = 0; y<imgheight; y=y+M)
{
    
    
    for (int x = 0; x<imgwidth; x=x+N)
    {
    
    
        if ((imgheight - y) < M || (imgwidth - x) < N)
        {
    
    
            break;
        }
        y1 = y + M;
        x1 = x + N;
        string a = to_string(x);
        string b = to_string(y);

        if (x1 >= imgwidth && y1 >= imgheight)
        {
    
    
            x = imgwidth - 1;
            y = imgheight - 1;
            x1 = imgwidth - 1;
            y1 = imgheight - 1;

            // crop the patches of size MxN
            Mat tiles = image_copy(Range(y, imgheight), Range(x, imgwidth));
            //save each patches into file directory
            imwrite("saved_patches/tile" + a + '_' + b + ".jpg", tiles);  
            rectangle(img, Point(x,y), Point(x1,y1), Scalar(0,255,0), 1);    
        }
        else if (y1 >= imgheight)
        {
    
    
            y = imgheight - 1;
            y1 = imgheight - 1;

            // crop the patches of size MxN
            Mat tiles = image_copy(Range(y, imgheight), Range(x, x+N));
            //save each patches into file directory
            imwrite("saved_patches/tile" + a + '_' + b + ".jpg", tiles);  
            rectangle(img, Point(x,y), Point(x1,y1), Scalar(0,255,0), 1);    
        }
        else if (x1 >= imgwidth)
        {
    
    
            x = imgwidth - 1;   
            x1 = imgwidth - 1;

            // crop the patches of size MxN
            Mat tiles = image_copy(Range(y, y+M), Range(x, imgwidth));
            //save each patches into file directory
            imwrite("saved_patches/tile" + a + '_' + b + ".jpg", tiles);  
            rectangle(img, Point(x,y), Point(x1,y1), Scalar(0,255,0), 1);    
        }
        else
        {
    
    
            // crop the patches of size MxN
            Mat tiles = image_copy(Range(y, y+M), Range(x, x+N));
            //save each patches into file directory
            imwrite("saved_patches/tile" + a + '_' + b + ".jpg", tiles);  
            rectangle(img, Point(x,y), Point(x1,y1), Scalar(0,255,0), 1);    
        }
    }
}

接下来，使用imshow()函数显示图像。使用imwrite()函数将其保存到文件目录中。

显示图像

Python

#Save full image into file directory
cv2.imshow("Patched Image",img)
cv2.imwrite("patched.jpg",img)
 
cv2.waitKey()
cv2.destroyAllWindows()

C++

imshow("Patched Image", img);
imwrite("patched.jpg",img);
waitKey();
destroyAllWindows();

参考
https://learnopencv.com/cropping-an-image-using-opencv/