Drawing a line using centroid point in opencv - python-3.x

Question

How do I pass a line through the center of a contour? I have the center coordinates of my contour.

Answer 1

This is how you solve this question -
Original image -
Result image -
You first need to do basic filtering and find the contour. Then -
1) Find out the area of contour (minAreaRect)
2) Extract points from the contour (BoxPoints)
3) Convert it to a numpy array (np.array)
4) Order the points (perspective.order_points)
5) Take out Top-left, Top-right, Bottom-right and Bottom-left(tl, tr, br, bl) = box (Line 52)
6) Calculate the midpoints ( (point1 + point2) / 2)
7) Draw the lines (line 76)
Here is the code for it
# import the necessary packages
from scipy.spatial import distance as dist
from imutils import perspective
from imutils import contours
import numpy as np
import imutils
import cv2
# Method to find the mid point
def midpoint(ptA, ptB):
return ((ptA[0] + ptB[0]) * 0.5, (ptA[1] + ptB[1]) * 0.5)
# load the image, convert it to grayscale, and blur it slightly
image = cv2.imread("test.png")
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (7, 7), 0)
# perform edge detection, then perform a dilation + erosion to
# close gaps in between object edges
edged = cv2.Canny(gray, 50, 100)
edged = cv2.dilate(edged, None, iterations=1)
edged = cv2.erode(edged, None, iterations=1)
# find contours in the edge map
cnts = cv2.findContours(edged.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if imutils.is_cv2() else cnts[1]
# loop over the contours individually
for c in cnts:
# This is to ignore that small hair countour which is not big enough
if cv2.contourArea(c) < 1000:
continue
# compute the rotated bounding box of the contour
box = cv2.minAreaRect(c)
box = cv2.cv.BoxPoints(box) if imutils.is_cv2() else cv2.boxPoints(box)
box = np.array(box, dtype="int")
# order the points in the contour such that they appear
# in top-left, top-right, bottom-right, and bottom-left
# order, then draw the outline of the rotated bounding
# box
box = perspective.order_points(box)
# draw the contours on the image
orig = image.copy()
cv2.drawContours(orig, [box.astype("int")], -1, (0, 255, 0), 3)
# unpack the ordered bounding box, then compute the midpoint
# between the top-left and top-right coordinates, followed by
# the midpoint between bottom-left and bottom-right coordinates
(tl, tr, br, bl) = box
(tltrX, tltrY) = midpoint(tl, tr)
(blbrX, blbrY) = midpoint(bl, br)
# compute the midpoint between the top-left and top-right points,
# followed by the midpoint between the top-righ and bottom-right
(tlblX, tlblY) = midpoint(tl, bl)
(trbrX, trbrY) = midpoint(tr, br)
# draw and write the midpoints on the image
cv2.circle(orig, (int(tltrX), int(tltrY)), 5, (255, 0, 0), -1)
cv2.putText(orig, "({},{})".format(tltrX, tltrY), (int(tltrX - 50), int(tltrY - 10) - 20),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255,0,0), 2)
cv2.circle(orig, (int(blbrX), int(blbrY)), 5, (255, 0, 0), -1)
cv2.putText(orig, "({},{})".format(blbrX, blbrY), (int(blbrX - 50), int(blbrY - 10) - 20),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255,0,0), 2)
cv2.circle(orig, (int(tlblX), int(tlblY)), 5, (255, 0, 0), -1)
cv2.putText(orig, "({},{})".format(tlblX, tlblY), (int(tlblX - 50), int(tlblY - 10) - 20),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255,0,0), 2)
cv2.circle(orig, (int(trbrX), int(trbrY)), 5, (255, 0, 0), -1)
cv2.putText(orig, "({},{})".format(trbrX, trbrY), (int(trbrX - 50), int(trbrY - 10) - 20),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255,0,0), 2)
# draw lines between the midpoints
cv2.line(orig, (int(tltrX), int(tltrY)), (int(blbrX), int(blbrY)),
(255, 0, 255), 2)
cv2.line(orig, (int(tlblX), int(tlblY)), (int(trbrX), int(trbrY)),
(255, 0, 255), 2)
# compute the Euclidean distance between the midpoints
dA = dist.euclidean((tltrX, tltrY), (blbrX, blbrY))
dB = dist.euclidean((tlblX, tlblY), (trbrX, trbrY))
# loop over the original points
for (xA, yA) in list(box):
# draw circles corresponding to the current points and
cv2.circle(orig, (int(xA), int(yA)), 5, (0,0,255), -1)
cv2.putText(orig, "({},{})".format(xA, yA), (int(xA - 50), int(yA - 10) - 20),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255,0,0), 2)
# show the output image, resize it as per your requirements
cv2.imshow("Image", orig)
cv2.waitKey(0)