How to sum areas of contours after sorted them? - python-2.7

Question

I'd like to sum areas of the largest five contours after sorted or all of them if less than five.
The robot follows the people's base on the color but sometimes people have the same color and I'd like to choose one from them using the area. I used this line for two contours but this method is not good area1 = cv2.contourArea(cnts[0]) + cv2.contourArea(cnts[1])
Full code:
import cv2
import numpy as np
from imutils.video import FPS
import time
cap = cv2.VideoCapture(0)
width = cap.get(3) # float
height = cap.get(4) # float
print width, height
time.sleep(2.0)
fps = FPS().start()
while (1):
_, img = cap.read()
if _ is True:
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
else:
continue
black_lower = np.array([0,0,0], np.uint8)
black_upper = np.array([180,255,30], np.uint8)
black = cv2.inRange(hsv, black_lower, black_upper)
kernal = np.ones((5, 5), "uint8")
black = cv2.dilate(black, kernal)
res_black = cv2.bitwise_and(img, img, mask=black)
# Tracking black
(_, contours, hierarchy) = cv2.findContours(black, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
cnts = sorted(contours, key=cv2.contourArea, reverse=True)[:2000] # get largest 2000 contour area
area1 = cv2.contourArea(cnts[0]) + cv2.contourArea(cnts[1])
# area2 = cv2.contourArea(cnts[0])
# total = area1 +area2
print 'area', area1, type(cnts)
rects = []
print len(cnts) , type(cnts[1])
for c in cnts:
peri = cv2.arcLength(c, True)
approx = cv2.approxPolyDP(c, 0.02 * peri, True)
x, y, w, h = cv2.boundingRect(approx)
if h >= 15:
rect = (x, y, w, h)
rects.append(rect)
img = cv2.rectangle(img, (x, y), (x + w, y + h), (0, 0, 0), 2)
cv2.putText(img, "Black Colour", (x, y), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 0))
cv2.imshow("Color Tracking", img)
if cv2.waitKey(10) & 0xFF == ord('q'):
cap.release()
cv2.destroyAllWindows()
break
Any help or suggestions would be appreciated.

Answer 1

You can sum them using list = [], but maybe you face another issue, sum of areas for all people.
import cv2
import numpy as np
from imutils.video import FPS
import time
cap = cv2.VideoCapture(0)
width = cap.get(3) # float
height = cap.get(4) # float
print width, height
time.sleep(2.0)
fps = FPS().start()
while (1):
_, img = cap.read()
if _ is True:
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
else:
continue
black_lower = np.array([0,0,0], np.uint8)
black_upper = np.array([180,255,30], np.uint8)
black = cv2.inRange(hsv, black_lower, black_upper)
kernal = np.ones((5, 5), "uint8")
black = cv2.dilate(black, kernal)
res_black = cv2.bitwise_and(img, img, mask=black)
# Tracking black
(_, contours, hierarchy) = cv2.findContours(black, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
cnts = sorted(contours, key=cv2.contourArea, reverse=True)[:5] # get largest five contour area
areas = []
for contour in cnts:
area = cv2.contourArea(contour)
if area > 300:
areas.append(area)
x, y, w, h = cv2.boundingRect(contour)
img = cv2.rectangle(img, (x, y), (x + w, y + h), (0, 0, 0), 2)
cv2.putText(img, "Black Colour", (x, y), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 0))
a = sum(areas)
print areas
print a
cv2.imshow("Color Tracking", img)
if cv2.waitKey(10) & 0xFF == ord('q'):
cap.release()
cv2.destroyAllWindows()
break

Answer 2

you can use just this line:
area = sum([cv2.contourArea(cnt) for cnt in sorted(cnts, key=cv2.contourArea, reverse=True)[:5]])
I will add the full code to compare between them.
import cv2
import numpy as np
from imutils.video import FPS
import time
cap = cv2.VideoCapture(0)
width = cap.get(3) # float
height = cap.get(4) # float
print width, height
time.sleep(2.0)
fps = FPS().start()
while (1):
_, img = cap.read()
if _ is True:
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
else:
continue
black_lower = np.array([0,0,0], np.uint8)
black_upper = np.array([180,255,30], np.uint8)
black = cv2.inRange(hsv, black_lower, black_upper)
kernal = np.ones((5, 5), "uint8")
black = cv2.dilate(black, kernal)
res_black = cv2.bitwise_and(img, img, mask=black)
# Tracking black
(_, contours, hierarchy) = cv2.findContours(black, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
cnts = sorted(contours, key=cv2.contourArea, reverse=True)[:5] # get largest five contour area
area = sum([cv2.contourArea(cnt) for cnt in sorted(cnts, key=cv2.contourArea, reverse=True)[:5]])
print 'area_method1', area
areas = []
for contour in cnts:
area = cv2.contourArea(contour)
if area > 300:
areas.append(area)
x, y, w, h = cv2.boundingRect(contour)
img = cv2.rectangle(img, (x, y), (x + w, y + h), (0, 0, 0), 2)
cv2.putText(img, "Black Colour", (x, y), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 0))
a = sum(areas)
# print areas
print 'area_method2', a
cv2.imshow("Color Tracking", img)
if cv2.waitKey(10) & 0xFF == ord('q'):
cap.release()
cv2.destroyAllWindows()
break