使用pycharm对图像进行处理提取轮廓，测量尺寸

以下是使用Pycharm对图像进行处理提取轮廓，测量尺寸的步骤：

1. 导入相关的库和模块

import cv2
import numpy as np

2. 加载图像

img = cv2.imread('image.jpg')

3. 灰度化处理

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

4. 滤波处理

blurred = cv2.GaussianBlur(gray, (5, 5), 0)

5. 边缘检测

edged = cv2.Canny(blurred, 30, 150)

6. 轮廓提取

contours, hierarchy = cv2.findContours(edged, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

7. 绘制轮廓

cv2.drawContours(img, contours, -1, (0, 0, 255), 2)

8. 测量尺寸

for c in contours:
    # 计算轮廓周长
    perimeter = cv2.arcLength(c, True)
    # 计算轮廓面积
    area = cv2.contourArea(c)
    # 计算轮廓包围框
    x, y, w, h = cv2.boundingRect(c)
    # 绘制包围框
    cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 2)
    # 显示测量结果
    print("Perimeter: {:.2f}".format(perimeter))
    print("Area: {:.2f}".format(area))

9. 显示处理结果

cv2.imshow("Contours", img)
cv2.waitKey(0)
cv2.destroyAllWindows()

完整代码：

import cv2
import numpy as np

img = cv2.imread('image.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
blurred = cv2.GaussianBlur(gray, (5, 5), 0)
edged = cv2.Canny(blurred, 30, 150)
contours, hierarchy = cv2.findContours(edged, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cv2.drawContours(img, contours, -1, (0, 0, 255), 2)

for c in contours:
    perimeter = cv2.arcLength(c, True)
    area = cv2.contourArea(c)
    x, y, w, h = cv2.boundingRect(c)
    cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 2)
    print("Perimeter: {:.2f}".format(perimeter))
    print("Area: {:.2f}".format(area))

cv2.imshow("Contours", img)
cv2.waitKey(0)
cv2.destroyAllWindows()