Python OpenCV drawKeypoints()用法及代码示例

在本文中，我们讨论 OpenCV 的 drawKeypoints() 函数。使图像脱颖而出的独特品质被称为图像中的关键点。特定图像的关键点让我们能够识别物体并比较图像。可以使用多种技术和算法来检测图片中的关键点。我们利用OpenCV中的drawKeypoints()方法能够在给定图片上绘制识别出的关键点。输入图片、关键点、颜色和标志被发送到drawKeypoints()方法。关键点是检测中最重要的方面。即使图像被修改后，关键点仍然保持不变。目前，我们只能使用SIRF_create()函数，因为surf函数已获得专利。

Syntax of drawKeypoints() function:

drawKeypoints(input_image, key_points, output_image, colour, flag)

parameters:

input_image : The image which is turned into grayscale and then the key points are extracted using the SURF or SIFT algorithms is called input image.

key_points : The key points obtained from the input picture after using the algorithms are referred to as keypoints.

output_image : image on which the keypoints are drawn.

colour : the colour of the keypoints.

flag : drawing features are represented by the flag.

示例 1：

此示例首先导入 OpenCV 和 matplotlib 包。我们读取图像，将其转换为灰度，然后应用SIRF_create()算法来帮助我们检测图像中的关键点。 drawKeypoints()函数接收多个参数并在图像上绘制关键点。标志可以改变。在下面的示例中，我们使用 cv2.DRAW_MATCHES_FLAGS_NOT_DRAW_SINGLE_POINTS 作为标志。绘制输出图像。除了使用 cv2.SIRF_create() 之外，还可以使用 cv2.xfeatures2d.SIFT_create() ，在 OpenCV 的几个版本中它可能不起作用。 cv2.xfeatures2d.SURF_create() 算法也是如此。

注意：红色为 (255,0,0)，蓝色为 (0,0,255)，绿色为 (0,255,0)。

使用的图像：

Python3


# importing packages 
import cv2 
import matplotlib.pyplot as plt 
  
# reading image using the imread() function 
imageread = cv2.imread('img1.jpeg') 
  
# input image is converted to gray scale image 
imagegray = cv2.cvtColor(imageread, cv2.COLOR_BGR2GRAY) 
  
# using the SIRF algorithm to detect key 
# points in the image 
features = cv2.SIFT_create() 
  
keypoints = features.detect(imagegray, None) 
  
# drawKeypoints function is used to draw keypoints 
output_image = cv2.drawKeypoints(imagegray, keypoints, 0, (0, 0, 255), 
                                 flags=cv2.DRAW_MATCHES_FLAGS_NOT_DRAW_SINGLE_POINTS) 
  
# displaying the image with keypoints as the 
# output on the screen 
  
plt.imshow(output_image) 
  
# plotting image 
plt.show()

输出：

示例 2：

此示例与上一个示例类似，只是我们将颜色更改为红色 (255,0,0)，并将标志更改为 cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS。

Python3


# importing packages 
import cv2 
import matplotlib.pyplot as plt 
  
# reading image using the imread() function 
imageread = cv2.imread('img1.jpeg') 
  
# input image is converted to gray scale image 
imagegray = cv2.cvtColor(imageread, cv2.COLOR_BGR2GRAY) 
  
# using the SIRF algorithm to detect key  
# points in the image 
features = cv2.SIFT_create() 
  
keypoints = features.detect(imagegray, None) 
  
# drawKeypoints function is used to draw keypoints 
output_image = cv2.drawKeypoints(imagegray, keypoints, 0, (255, 0, 0), 
                                 flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS) 
  
# displaying the image with keypoints as the 
# output on the screen 
plt.imshow(output_image) 
  
# plotting image 
plt.show()

输出：

示例3：

此示例与上一个示例类似，只是我们将颜色更改为绿色 (0,255,0)，并将标志更改为 cv2.DRAW_MATCHES_FLAGS_DEFAULT。

Python3


import cv2 
import matplotlib.pyplot as plt 
  
# reading image using the imread() function 
imageread = cv2.imread('img1.jpeg') 
  
# input image is converted to gray scale image 
imagegray = cv2.cvtColor(imageread, cv2.COLOR_BGR2GRAY) 
  
# using the SIRF algorithm to detect key 
# points in the image 
features = cv2.SIFT_create() 
  
keypoints = features.detect(imagegray, None) 
  
# drawKeypoints function is used to draw keypoints 
output_image = cv2.drawKeypoints(imagegray, keypoints, 0, (0, 255, 0), 
                                 flags=cv2.DRAW_MATCHES_FLAGS_DEFAULT) 
  
# displaying the image with keypoints as 
# the output on the screen 
plt.imshow(output_image) 
  
# plotting image 
plt.show()

输出：

相关用法

注：本文由纯净天空筛选整理自isitapol2002大神的英文原创作品 Python OpenCV – drawKeypoints() Function。非经特殊声明，原始代码版权归原作者所有，本译文未经允许或授权，请勿转载或复制。