Python+OpenCV图像处理之对象测量

OpenCV中经常会测量对象的面积，周长，质心，边界框等

求图形几何矩中心并求最小外接矩形python实现

import cv2
import numpy as np


__author__ = "boboa"


def measure_demo(image):
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    ret, thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)
    print("threshold value", ret)
    cv2.imshow("binary", thresh)
    outImage,contours, hierarchy = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    for i, contour in enumerate(contours):  # 遍历全部轮廓
        area = cv2.contourArea(contour)
        # cv2.boundingRect返回四个参数（x，y）为矩形左上角的坐标，（w，h）是矩形的宽和高
        x, y, w, h = cv2.boundingRect(contour)  # 外接矩形大小
        rate = min(w, h) / max(w, h)            # 宽高比
        # 计算图像中的中心矩
        mm = cv2.moments(contour)
        cx = mm["m10"]/mm["m00"]
        cy = mm["m01"]/mm["m00"]  # 几何图形的中心位置 , mm是字典类型
        cv2.circle(image, (np.int(cx), np.int(cy)), 2, (0, 255, 255), -1)
        cv2.rectangle(image, (x, y), (x+w, y+h), (0, 0, 255), 2)  # 外接矩形
        print("contour area ", area)
    cv2.imshow("measure contours", image)


if __name__ == "__main__":
    img = cv2.imread("image/123.jpg")
    cv2.namedWindow("input image", cv2.WINDOW_AUTOSIZE)
    cv2.imshow("input image", img)
    measure_demo(img)
    cv2.waitKey(0)
    cv2.destroyAllWindows()

运行结果

多边形拟合（应用：选择图片中几何体形状）python实现

"""
     approxPolyDP(curve, epsilon, closed[, approxCurve]) -> approxCurve
     curve-拟合曲线
     epsilon-拟合曲线条数（int）
     closed-拟合曲线是否闭合（True or False）
     多边形拟合
 """
    approxCurve = cv2.approxPolyDP(contour,10,True)
    print(approxCurve.shape)
    #画轮廓多边形拟合数目>6的图形轮廓为红
    if approxCurve.shape[0] > 6:
        cv2.drawContours(dst,contours,i,(0,0,255),2)
 # 画轮廓多边形拟合数目=3的图形轮廓为蓝
    elif approxCurve.shape[0] == 3:
        cv2.drawContours(dst,contours,i,(255,0,0),2)
    # 画其余数目的轮廓多边形拟合的图形轮廓为黄
    else:
        cv2.drawContours(dst,contours,i,(0,255,255),2)

Python+OpenCV图像处理之对象测量

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