I'm developing a python script to take isolate the largest and second largest objects that are matched by color in the image. I've managed to get the largest object, draw a contour around it and draw a box. However, I'm stumped to find a solution to find the second largest object. I want the second largest object to be detected separately.
import numpy as np
import cv2
font = cv2.FONT_HERSHEY_SIMPLEX
lineType = cv2.LINE_AA
im = cv2.imread('Photos/test.jpg')
im_ycrcb = cv2.cvtColor(im, cv2.COLOR_BGR2HSV)
ball_ycrcb_mint = np.array([0, 90, 100],np.uint8)
ball_ycrcb_maxt = np.array([25, 255, 255],np.uint8)
ball_ycrcb = cv2.inRange(im_ycrcb, ball_ycrcb_mint, ball_ycrcb_maxt)
#cv2.imwrite('Photos/output2.jpg', ball_ycrcb) # Second image
areaArray = []
count = 1
_, contours, _ = cv2.findContours(ball_ycrcb, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
for i, c in enumerate(contours):
area = cv2.contourArea(c)
areaArray.append(area)
areaLargest = np.argmax(areaArray)
areaLargestMax = max(areaArray)
areaLargestCnt = contours[areaLargest]
x, y, w, h = cv2.boundingRect(areaLargestCnt)
if area == areaLargestMax and area > 10000:
cv2.drawContours(im, contours, i, (255, 0, 0), 2)
cv2.rectangle(im, (x, y), (x+w, y+h), (0,255,0), 2)
cv2.imwrite('Photos/output3.jpg', im)
I'm using the following image for testing purposes: Image of balls
Any help is appreciated!
First of all, it's simpler to first create the array of contours and contour areas, then find the n'th largest contour.
import numpy as np
import cv2
im = cv2.imread('Photos/test.jpg')
im_ycrcb = cv2.cvtColor(im, cv2.COLOR_BGR2HSV)
ball_ycrcb_mint = np.array([0, 90, 100],np.uint8)
ball_ycrcb_maxt = np.array([25, 255, 255],np.uint8)
ball_ycrcb = cv2.inRange(im_ycrcb, ball_ycrcb_mint, ball_ycrcb_maxt)
#cv2.imwrite('Photos/output2.jpg', ball_ycrcb) # Second image
areaArray = []
count = 1
contours, _ = cv2.findContours(ball_ycrcb, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
for i, c in enumerate(contours):
area = cv2.contourArea(c)
areaArray.append(area)
#first sort the array by area
sorteddata = sorted(zip(areaArray, contours), key=lambda x: x[0], reverse=True)
#find the nth largest contour [n-1][1], in this case 2
secondlargestcontour = sorteddata[1][1]
#draw it
x, y, w, h = cv2.boundingRect(secondlargestcontour)
cv2.drawContours(im, secondlargestcontour, -1, (255, 0, 0), 2)
cv2.rectangle(im, (x, y), (x+w, y+h), (0,255,0), 2)
cv2.imwrite('Photos/output3.jpg', im)
This should basically do what you want. I stripped the code of unnecessary stuff that caused crashes on my version of opencv.
You could use sorted(contours, key=cv2.contourArea, reverse=True)
to give you a descending list of contours by area.
image, cnts, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
cnt = sorted(cnts, key=cv2.contourArea)
cnt gives you an ordered list of contours in increasing order w.r.t area.
You can find the area of contour by index:
area = cv2.contourArea(cnt[index])
index can be 1,2,3.....,len(cnts)
For accessing the largest area contour:
cnt[reverse_index]
give reverse_index as -1 which gives u the largest area contour.
For second largest give reverse_index as -2 and so on.