circle-finder.py
# The MIT License (MIT) | |
# | |
# Copyright (c) 2015 Michael Bates | |
# | |
# Permission is hereby granted, free of charge, to any person obtaining a copy | |
# of this software and associated documentation files (the "Software"), to deal | |
# in the Software without restriction, including without limitation the rights | |
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | |
# copies of the Software, and to permit persons to whom the Software is | |
# furnished to do so, subject to the following conditions: | |
# | |
# The above copyright notice and this permission notice shall be included in | |
# all copies or substantial portions of the Software. | |
# | |
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR | |
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, | |
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE | |
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER | |
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, | |
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN | |
# THE SOFTWARE. | |
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") | |
ap.add_argument("-d", "--distance", required = False, help = "Minimum distance between circles") | |
args = vars(ap.parse_args()) | |
# open the image, convert it to grayscale and apply a slight gaussian blur. | |
# these changes help reduce noise, making the algorithm more accurate. | |
image = cv2.imread(args["image"]) | |
output = image.copy() | |
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) | |
gray = cv2.GaussianBlur(gray, (9,9), 2, 2) | |
# detect circles in the image | |
distance = int(args["distance"]) or 100 | |
print "Finding circles at least %(distance)i pixels apart" % {"distance": distance} | |
circles = cv2.HoughCircles(gray, cv2.cv.CV_HOUGH_GRADIENT, 1.3, distance) | |
if circles is None: | |
print "No circles found :(" | |
sys.exit() | |
# convert the (x, y) coordinates and radius of the circles to integers | |
circles = np.round(circles[0, :]).astype("int") | |
# loop over the (x, y) coordinates and radius of the circles | |
for (x, y, r) in circles: | |
# draw the circle in the output image, then draw a rectangle | |
# corresponding to the center of the circle | |
print "r:%(r)s (%(x)s, %(y)s)" % locals() | |
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) | |
# show the output image | |
cv2.imshow("output", np.hstack([output])) | |
cv2.waitKey(0) |
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