python语言实现的基于opencv的表针识别代码

import cv2
import numpy as np
import time
import NUMBER
import screenshot


def dist_2_pts（x1 y1 x2 y2）:
    return np.sqrt（（x2 - x1）**2 + （y2 - y1）**2）

def avg_circles（circles b）:
    avg_x=0
    avg_y=0
    avg_r=0
    for i in range（b）:

        avg_x = avg_x + circles[0][i][0]
        avg_y = avg_y + circles[0][i][1]
        avg_r = avg_r + circles[0][i][2]
    avg_x = int（avg_x/ （b））
    avg_y = int（avg_y/（b））
    avg_r = int（avg_r/（b））
    return avg_x avg_y avg_r

def avg_circles_three（circles b）:
    number=[1]
    avg_x = [000]
    avg_y = [000]
    avg_r = [000]
    initial=[000]
    for i in range（b）:
        if （initial[0] == 1 ）:
            if（dist_2_pts（avg_x[0]avg_y[0]circles[0][i][0]circles[0][i][1]） >= （avg_r[0]+circles[0][i][2]））:
                if（initial[1] == 1）:
                    if （dist_2_pts（avg_x[1] avg_y[1] circles[0][i][0] circles[0][i][1]） >= （avg_r[1] + circles[0][i][2]））:
                        if （initial[2] == 1）:
                            avg_x[2] = （avg_x[2] + circles[0][i][0]）/2
                            avg_y[2] = （avg_y[2] + circles[0][i][1]）/2
                            avg_r[2] = （avg_r[2] + circles[0][i][2]）/2
                        else:
                            initial[2] = 1
                            number[0]=number[0]+1
                            avg_x[2] =  circles[0][i][0]
                            avg_y[2] =  circles[0][i][1]
                            avg_r[2] =  circles[0][i][2]
                    else:
                        avg_x[1] = （avg_x[1] + circles[0][i][0]）/2
                        avg_y[1] = （avg_y[1] + circles[0][i][1]）/2
                        avg_r[1] = （avg_r[1] + circles[0][i][2]）/2
                else:
                    initial[1] = 1
                    avg_x[1] = circles[0][i][0]
                    avg_y[1] = circles[0][i][1]
                    avg_r[1] = circles[0][i][2]
                    number[0] = number[0] + 1

            else:
                avg_x[0] = （avg_x[0] + circles[0][i][0]）/2
                avg_y[0] = （avg_y[0] + circles[0][i][1]）/2
                avg_r[0] = （avg_r[0] + circles[0][i][2]）/2
        else:
            avg_x[0] = circles[0][i][0]
            avg_y[0] = circles[0][i][1]
            avg_r[0] = circles[0][i][2]
            initial[0]=1
    for i in range（3）:
        avg_x[i] = int（avg_x[i]）
        avg_y[i] = int（avg_y[i]）
        avg_r[i] = int（avg_r[i]）
    return avg_x avg_y avg_r number

def calibrate_gauge（gauge_number file_type）:
    img = cv2.imread（‘gauge-%s.%s‘ %（gauge_number file_type））
    height width = img.shape[:2]
    gray = cv2.cvtColor（img cv2.COLOR_BGR2GRAY）  #convert to gray


    #detect circles
    circles = cv2.HoughCircles（gray cv2.HOUGH_GRADIENT 1 20 np.array（[]） 100 80 int（height*0.1） int（height*0.48））
    a b c = circles.shape
    xyr = avg_circles（circles b）

    ‘‘‘
    Circles=avg_circles_three（circlesb）
    x=Circles[0][0]
    y=Circles[1][0]
    r=