使用Python的OpenCV绘制矩形并提取对象 _Python图像处理

OpenCV的是一个开放源代码的计算机视觉和机器学习软件库。借助它可以完成各种图像处理操作, 例如处理图像和应用大量滤镜。它广泛用于对象检测, 面部检测和其他图像处理任务。
让我们看看如何在图像上绘制矩形并使用OpenCV提取对象。

# Python program to extract rectangular # Shape using OpenCV in Python3 import cv2 import numpy as npdrawing = False# true if mouse is pressed mode = True# if True, draw rectangle. ix, iy = - 1 , - 1# mouse callback function def draw_circle(event, x, y, flags, param): global ix, iy, drawing, modeif event = = cv2.EVENT_LBUTTONDOWN: drawing = True ix, iy = x, yelif event = = cv2.EVENT_MOUSEMOVE: if drawing = = True : if mode = = True : cv2.rectangle(img, (ix, iy), (x, y), ( 0 , 255 , 0 ), 3 ) a = x b = y if a ! = x | b ! = y: cv2.rectangle(img, (ix, iy), (x, y), ( 0 , 0 , 0 ), - 1 ) else : cv2.circle(img, (x, y), 5 , ( 0 , 0 , 255 ), - 1 )elif event = = cv2.EVENT_LBUTTONUP: drawing = False if mode = = True : cv2.rectangle(img, (ix, iy), (x, y), ( 0 , 255 , 0 ), 2 )else : cv2.circle(img, (x, y), 5 , ( 0 , 0 , 255 ), - 1 )img = np.zeros(( 512 , 512 , 3 ), np.uint8) cv2.namedWindow( 'image' ) cv2.setMouseCallback( 'image' , draw_circle)while ( 1 ): cv2.imshow( 'image' , img) k = cv2.waitKey( 1 ) & 0xFF if k = = ord ( 'm' ): mode = not mode elif k = = 27 : breakcv2.destroyAllWindows()

【使用Python的OpenCV绘制矩形并提取对象】输出如下：

文章图片
上面的代码仅适用于黑色背景图像。但是可以在任何图像上绘制矩形。我们可以编写一个程序, 使我们能够选择图像中的所需部分并提取所选部分。任务包括以下内容–

在任何图像上绘制形状
重新选择提取部分, 以防选择错误
从图像中提取特定对象

# Write Python code here # import the necessary packages import cv2 import argparse# now let's initialize the list of reference point ref_point = [] crop = Falsedef shape_selection(event, x, y, flags, param): # grab references to the global variables global ref_point, crop# if the left mouse button was clicked, record the starting # (x, y) coordinates and indicate that cropping is being performed if event = = cv2.EVENT_LBUTTONDOWN: ref_point = [(x, y)]# check to see if the left mouse button was released elif event = = cv2.EVENT_LBUTTONUP: # record the ending (x, y) coordinates and indicate that # the cropping operation is finished ref_point.append((x, y))# draw a rectangle around the region of interest cv2.rectangle(image, ref_point[ 0 ], ref_point[ 1 ], ( 0 , 255 , 0 ), 2 ) cv2.imshow( "image" , image)# construct the argument parser and parse the arguments ap = argparse.ArgumentParser() ap.add_argument( "-i" , "--image" , required = True , help = "Path to the image" ) args = vars (ap.parse_args())# load the image, clone it, and setup the mouse callback function image = cv2.imread(args[ "image" ]) clone = image.copy() cv2.namedWindow( "image" ) cv2.setMouseCallback( "image" , shape_selection)# keep looping until the 'q' key is pressed while True : # display the image and wait for a keypress cv2.imshow( "image" , image) key = cv2.waitKey( 1 ) & 0xFF# press 'r' to reset the window if key = = ord ( "r" ): image = clone.copy()# if the 'c' key is pressed, break from the loop elif key = = ord ( "c" ): breakif len (ref_point) = = 2 : crop_img = clone[ref_point[ 0 ][ 1 ]:ref_point[ 1 ][ 1 ], ref_point[ 0 ][ 0 ]: ref_point[ 1 ][ 0 ]] cv2.imshow( "crop_img" , crop_img) cv2.waitKey( 0 )# close all open windows cv2.destroyAllWindows()

运行：将文件另存为capture_events.py为了进行测试, 请选择位于同一目录中的演示图片。现在, 执行以下命令–