Python + OpenCV image processing of the measurement target

OpenCV will often measured object area, perimeter, centroid, bounding box, etc.

Seeking graphic geometric moments, and determining the center of the minimum enclosing rectangle python achieved

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 inthe enumerate (Contours):   # traversing the entire contour 
        Area = cv2.contourArea (Contour)
         # cv2.boundingRect returns four parameters (x, Y) coordinates of the upper left corner of the rectangle, (w, h) is the width and height of a rectangular 
        x, Y, W, H = cv2.boundingRect (Contour)   # circumscribed rectangle size 
        Rate = min (W, H) / max (W, H)             # aspect ratio 
        # image is calculated in the central moments 
        mm = cv2.moments (Contour) 
        CX = mm [ " MlO " ] / mm [ " M00 " ] 
        CY = mm [ " M01 " ] / mm [ " M00 " ]   #The geometry of the center position, mm is the dictionary type 
        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)   # circumscribed rectangle 
        Print ( " Contour Area " , Area) 
    cv2.imshow ( " its measure Contours " , Image) 


IF  the __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()

operation result

 Fitting polygon (application: the geometry is selected in the picture) Python implemented

"" " 
     ApproxPolyDP (Curve, Epsilon, Closed [, approxCurve]) -> approxCurve 
     curve- fitting curve 
     epsilon- curve fitting article number (int) 
     closed- fit curve is closed (True or False) 
     polygonal fitting 
 " " " 
    approxCurve = cv2.approxPolyDP (contour, 10 , True)
     Print (approxCurve.shape)
     # contoured to fit the number of polygons> into red pattern profile 6 
    IF approxCurve.shape [0]> 6 : 
        cv2.drawContours (DST, contours , I, (0,0, 255), 2 )
  # contouring fit polygonal contour pattern number = 3 for blue 
    elif approxCurve.shape [0] == 3 : 
        cv2.drawContours (DST, contours, I, ( 255 , 0, 0), 2 )
     #Remaining number of polygon contouring fit figure outline yellow 
    the else : 
        cv2.drawContours (DST, Contours, I, (0, 255,255), 2)