I am interested in the human following using a real robot.
I'd like to use the color of clothes as a key feature to identify the target person in front of the robot to follow him/ her but I am suffering due to it is a weak feature with a very simple illumination changing. So, I need to alter this algorithm to another or update values (RGB) online in real-time but I don't have enough experience with image processing.
this is my full code for color detection:
import cv2
import numpy as np
from imutils.video import FPS
# capturing video through webcam
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
# blue color
blue_lower = np.array([99, 115, 150], np.uint8)
blue_upper = np.array([110, 255, 255], np.uint8)
blue = cv2.inRange(hsv, blue_lower, blue_upper)
kernal = np.ones((5, 5), "uint8")
blue = cv2.dilate(blue, kernal)
res_blue = cv2.bitwise_and(img, img, mask=blue)
# Tracking blue
(_, contours, hierarchy) = cv2.findContours(blue, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
for pic, contour in enumerate(contours):
area = cv2.contourArea(contour)
if (area > 300):
x, y, w, h = cv2.boundingRect(contour)
img = cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
cv2.putText(img, "Blue Colour", (x, y), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 0, 0))
cv2.imshow("Color Tracking", img)
if cv2.waitKey(10) & 0xFF == ord('q'):
cap.release()
cv2.destroyAllWindows()
break
fps.update()
# stop the timer and display FPS information
fps.stop()
# print("[INFO] elapsed time: {:.2f}".format(fps.elapsed()))
# print("[INFO] approx. FPS: {:.2f}".format(fps.fps()))
these are the outputs:
1- recognize a person by his clothes color
2- it is lost, the illumination changing is a very simple not severe
Any ideas or suggestions will be appreciated
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