Python OpenCV | cv2.rectangle()方法
原文:https://www . geesforgeks . org/python-opencv-cv2-rectangle-method/
OpenCV-Python 是一个 Python 绑定库，旨在解决计算机视觉问题。cv2.rectangle()方法用于在任意图像上绘制矩形。
语法: cv2 .矩形(图像、起点、终点、颜色、厚度)
参数: 图像:就是要画矩形的图像。 起点:是矩形的起始坐标。坐标表示为两个值的元组(即 X 坐标值、 Y 坐标值)。 end_point: 是矩形的结束坐标。坐标表示为两个值的元组(即 X 坐标值， Y 坐标值)。 颜色:是待画矩形边框线的颜色。对于 BGR ，我们传递一个元组。例如:(255，0，0)代表蓝色。 厚度:是 px 中矩形边框线的厚度。 -1 px 的厚度会以指定的颜色填充矩形。
返回值:返回图像。
图像用于以下所有示例:
示例#1:
# Python program to explain cv2.rectangle() method
# importing cv2
import cv2
# path
path = r'C:\Users\Rajnish\Desktop\geeksforgeeks\geeks.png'
# Reading an image in default mode
image = cv2.imread(path)
# Window name in which image is displayed
window_name = 'Image'
# Start coordinate, here (5, 5)
# represents the top left corner of rectangle
start_point = (5, 5)
# Ending coordinate, here (220, 220)
# represents the bottom right corner of rectangle
end_point = (220, 220)
# Blue color in BGR
color = (255, 0, 0)
# Line thickness of 2 px
thickness = 2
# Using cv2.rectangle() method
# Draw a rectangle with blue line borders of thickness of 2 px
image = cv2.rectangle(image, start_point, end_point, color, thickness)
# Displaying the image
cv2.imshow(window_name, image)
输出:
例 2:
使用-1 像素的厚度用黑色填充矩形。
# Python program to explain cv2.rectangle() method
# importing cv2
import cv2
# path
path = r'C:\Users\Rajnish\Desktop\geeksforgeeks\geeks.png'
# Reading an image in grayscale mode
image = cv2.imread(path, 0)
# Window name in which image is displayed
window_name = 'Image'
# Start coordinate, here (100, 50)
# represents the top left corner of rectangle
start_point = (100, 50)
# Ending coordinate, here (125, 80)
# represents the bottom right corner of rectangle
end_point = (125, 80)
# Black color in BGR
color = (0, 0, 0)
# Line thickness of -1 px
# Thickness of -1 will fill the entire shape
thickness = -1
# Using cv2.rectangle() method
# Draw a rectangle of black color of thickness -1 px
image = cv2.rectangle(image, start_point, end_point, color, thickness)
# Displaying the image
cv2.imshow(window_name, image)
输出:
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