Detect open circle with Python / OpenCV

Question

I have a picture with random circles shown of which one circle is always open. The size, position and color of the circles are different each time but the background is always white.

I want to find the coordinates of the circle which is open programmatically. Here is a sample picture:

This picture roughly has coordinates of x:285 y:70. Here is my attempt:

import numpy as np
import argparse
import cv2

ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", required = True, help = "Path to the image")
args = vars(ap.parse_args())

image = cv2.imread(args["image"])
black = cv2.imread('black.png')
output = image.copy()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

ret,thresh = cv2.threshold(gray,127,255,0)
contours, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
cv2.drawContours(black,contours,-1,(250,250,250),2)

newblack = cv2.cvtColor(black, cv2.COLOR_BGR2GRAY)

circles = cv2.HoughCircles(newblack, cv2.cv.CV_HOUGH_GRADIENT, 1, 1,
              param1=42,
              param2=35,
              minRadius=15,
              maxRadius=50)

if circles is not None:
        circles = np.round(circles[0, :]).astype("int")

        for (x, y, r) in circles:
                cv2.circle(output, (x, y), r, (0, 255, 0), 4)
                cv2.rectangle(output, (x - 5, y - 5), (x + 5, y + 5), (0, 128, 255), -1)

        cv2.imshow("output", np.hstack([image, output]))
        print circles
        cv2.waitKey(0)

Almost finished!

The param2 Value determines which circle is found. I tweaked my code so it iterates over param2 values starting with a rather high value of 120.

When it finds a circle it stops.

# import the necessary packages
import numpy as np
import argparse
import cv2
import sys

# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", required = True, help = "Path to the image")
args = vars(ap.parse_args())

# load the image, clone it for output, and then convert it to grayscale
image = cv2.imread(args["image"])
output = image.copy()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

str = 120

def findcircle( str ):
    circles = cv2.HoughCircles(gray, cv2.cv.CV_HOUGH_GRADIENT, 1, 1,
    param1=42,
    param2=str,
    minRadius=10,
    maxRadius=100)

    if circles is not None:
        circles = np.round(circles[0, :]).astype("int")
        print circles
        sys.exit()

    while circles is None:
        str = str-1
        findcircle(str)

findcircle(str)

The success rate is around 80-100%

How do change the output of the variable "circles" to only show one circle incase more then 1 is found and how do I remove unwanted spaces and brackets?

Answer 1

# import the necessary packages
import numpy as np
import argparse
import cv2
import sys

# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", required = True, help = "Path to the image")
args = vars(ap.parse_args())

# load the image, clone it for output, and then convert it to grayscale
image = cv2.imread(args["image"])
output = image.copy()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

str = 120

def findcircle( str ):
    circles = cv2.HoughCircles(gray, cv2.cv.CV_HOUGH_GRADIENT, 1, 1,
    param1=42,
    param2=str,
    minRadius=10,
    maxRadius=100)

    if circles is not None:
        circles = np.round(circles[0, :]).astype("int")
        index = [2]
        new_circles = np.delete(circles[0], index)
        print new_circles
        sys.exit()

    while circles is None:
        str = str-1
        findcircle(str)

findcircle(str)