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How to calculate the distance between the objects in the image with Python

Today I want to show you how to calculate the distance between the objects in the image. We will write an awesome algorithm that you can modify and extend to your needs. This is our test image: Let’s jump to the code! First, we need to import the necessary packages:

from scipy.spatial import distance as dist from imutils import perspective from imutils import contours import numpy as np import argparse import imutils import cv2

def midpoint(ptA, ptB): return ((ptA[0] + ptB[0]) * 0.5, (ptA[1] + ptB[1]) * 0.5)

image = cv2.imread('images/test.jpg') gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) gray = cv2.GaussianBlur(gray, (7, 7), 0)

edged = cv2.Canny(gray, 50, 100) edged = cv2.dilate(edged, None, iterations=1) edged = cv2.erode(edged, None, iterations=1)

cnts = cv2.findContours(edged.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) cnts = imutils.grab_contours(cnts)

(cnts, _) = contours.sort_contours(cnts) colors = ((0, 0, 255), (240, 0, 159), (0, 165, 255), (255, 255, 0), (255, 0, 255)) refObj = None

for c in cnts: if cv2.contourArea(c)  100: continue box = cv2.minAreaRect(c) box = cv2.cv.BoxPoints(box) if imutils.is_cv2() else cv2.boxPoints(box) box = np.array(box, dtype="int") box = perspective.order_points(box) cX = np.average(box[:, 0]) cY = np.average(box[:, 1]) if refObj is None: (tl, tr, br, bl) = box (tlblX, tlblY) = midpoint(tl, bl) (trbrX, trbrY) = midpoint(tr, br) D = dist.euclidean((tlblX, tlblY), (trbrX, trbrY)) refObj = (box, (cX, cY), D / 70) continue orig = image.copy() cv2.drawContours(orig, [box.astype("int")], -1, (0, 255, 0), 2) cv2.drawContours(orig, [refObj[0].astype("int")], -1, (0, 255, 0), 2) refCoords = np.vstack([refObj[0], refObj[1]]) objCoords = np.vstack([box, (cX, cY)])

for ((xA, yA), (xB, yB), color) in zip(refCoords, objCoords, colors): cv2.circle(orig, (int(xA), int(yA)), 5, color, -1) cv2.circle(orig, (int(xB), int(yB)), 5, color, -1) cv2.line(orig, (int(xA), int(yA)), (int(xB), int(yB)), color, 2) D = dist.euclidean((xA, yA), (xB, yB)) / refObj[2] (mX, mY) = midpoint((xA, yA), (xB, yB)) cv2.putText(orig, "in".format(D), (int(mX), int(mY - 10)), cv2.FONT_HERSHEY_SIMPLEX, 0.55, color, 2) cv2.imshow("Image", orig) cv2.waitKey(0) cv2.destroyAllWindows()

This is our final result: Thank you all.

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