Python OpenCV | cv2.ellipse()方法

原文:https://www . geesforgeks . org/python-opencv-cv2-ellipse-method/

OpenCV-Python 是一个 Python 绑定库,旨在解决计算机视觉问题。cv2.ellipse()方法用于在任意图像上绘制椭圆。

语法: cv2 .椭圆(图像、中心坐标、轴长度、角度、起始角度、角度、颜色[、厚度[、线型[、偏移]])

参数: 图像:就是要画椭圆的图像。 中心坐标:是椭圆的中心坐标。坐标表示为两个值的元组(即 X 坐标值、 Y 坐标值)。 axesLength: 它包含包含椭圆长轴和短轴(长轴长度、短轴长度)的两个变量的元组。 角度:椭圆旋转角度,单位为度。 起始角度:椭圆弧的起始角度,单位为度。 endAngle: 椭圆弧的终止角,单位为度。 颜色:是要绘制的形状的边框线的颜色。对于 BGR ,我们传递一个元组。例如:(255,0,0)代表蓝色。 厚度:px 中形状边框线的厚度。 -1 px 的厚度会以指定的颜色填充形状。 线型:这是可选参数。它给出了椭圆边界的类型。 换挡:这是可选参数。它表示中心坐标中的小数位数和轴的值。

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.ellipse() 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'

center_coordinates = (120, 100)

axesLength = (100, 50)

angle = 0

startAngle = 0

endAngle = 360

# Red color in BGR
color = (0, 0, 255)

# Line thickness of 5 px
thickness = 5

# Using cv2.ellipse() method
# Draw a ellipse with red line borders of thickness of 5 px
image = cv2.ellipse(image, center_coordinates, axesLength,
           angle, startAngle, endAngle, color, thickness)

# Displaying the image 
cv2.imshow(window_name, image) 

输出:

示例#2: 使用-1 px 的厚度和 30 度的旋转。

# Python program to explain cv2.ellipse() 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'

center_coordinates = (120, 100)

axesLength = (100, 50)

angle = 30

startAngle = 0

endAngle = 360

# Blue color in BGR
color = (255, 0, 0)

# Line thickness of -1 px
thickness = -1

# Using cv2.ellipse() method
# Draw a ellipse with blue line borders of thickness of -1 px
image = cv2.ellipse(image, center_coordinates, axesLength, angle,
                          startAngle, endAngle, color, thickness)

# Displaying the image
cv2.imshow(window_name, image) 

输出: