MJRoBot (Marcelo Rovai)
Published © GPL3+

Automatic Vision Object Tracking

A pan/tilt servo device helping a camera to automatically track color objects using vision.

IntermediateFull instructions provided12 hours35,681
Automatic Vision Object Tracking

Things used in this project

Story

Read more

Schematics

Electrical Diagram

Code

Code snippet #7

Plain text
import numpy as np
import cv2

cap = cv2.VideoCapture(0)
 
while(True):
    ret, frame = cap.read()
    frame = cv2.flip(frame, -1) # Flip camera vertically
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    
    cv2.imshow('frame', frame)
    cv2.imshow('gray', gray)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()

Code snippet #9

Plain text
import sys
import numpy as np
import cv2
 
blue = sys.argv[1]
green = sys.argv[2]
red = sys.argv[3]  
 
color = np.uint8([[[blue, green, red]]])
hsv_color = cv2.cvtColor(color, cv2.COLOR_BGR2HSV)
 
hue = hsv_color[0][0][0]
 
print("Lower bound is :"),
print("[" + str(hue-10) + ", 100, 100]\n")
 
print("Upper bound is :"),
print("[" + str(hue + 10) + ", 255, 255]")

Code snippet #13

Plain text
import cv2
import numpy as np

# Read the picure - The 1 means we want the image in BGR
img = cv2.imread('yellow_object.JPG', 1) 

# resize imag to 20% in each axis
img = cv2.resize(img, (0,0), fx=0.2, fy=0.2)
# convert BGR image to a HSV image
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV) 

# NumPy to create arrays to hold lower and upper range 
# The “dtype = np.uint8” means that data type is an 8 bit integer

lower_range = np.array([24, 100, 100], dtype=np.uint8) 
upper_range = np.array([44, 255, 255], dtype=np.uint8)

# create a mask for image
mask = cv2.inRange(hsv, lower_range, upper_range)

# display both the mask and the image side-by-side
cv2.imshow('mask',mask)
cv2.imshow('image', img)

# wait to user to press [ ESC ]
while(1):
  k = cv2.waitKey(0)
  if(k == 27):
    break
 
cv2.destroyAllWindows()

Code snippet #19

Plain text
import sys
import time
import RPi.GPIO as GPIO

# initialize GPIO and variables
redLed = int(sys.argv[1])
freq = int(sys.argv[2])
GPIO.setmode(GPIO.BCM)
GPIO.setup(redLed, GPIO.OUT)
GPIO.setwarnings(False)

print("\n [INFO] Blinking LED (5 times) connected at GPIO {0} at every {1} second(s)".format(redLed, freq))
for i in range(5):
    GPIO.output(redLed, GPIO.LOW)
    time.sleep(freq)
    GPIO.output(redLed, GPIO.HIGH)
    time.sleep(freq)

# do a bit of cleanup
print("\n [INFO] Exiting Program and cleanup stuff \n")
GPIO.cleanup()

Code snippet #21

Plain text
import RPi.GPIO as GPIO
redLed = 21
GPIO.setmode(GPIO.BCM)
GPIO.setwarnings(False)
GPIO.setup(redLed, GPIO.OUT)

Code snippet #25

Plain text
from time import sleep
import RPi.GPIO as GPIO
GPIO.setmode(GPIO.BCM)
GPIO.setwarnings(False)

def setServoAngle(servo, angle):
	pwm = GPIO.PWM(servo, 50)
	pwm.start(8)
	dutyCycle = angle / 18. + 3.
	pwm.ChangeDutyCycle(dutyCycle)
	sleep(0.3)
	pwm.stop()

if __name__ == '__main__':
	import sys
	servo = int(sys.argv[1])
	GPIO.setup(servo, GPIO.OUT)
	setServoAngle(servo, int(sys.argv[2]))
	GPIO.cleanup()

Code snippet #27

Plain text
# only proceed if the radius meets a minimum size
if radius > 10:
	# draw the circle and centroid on the frame,
	# then update the list of tracked points
	cv2.circle(frame, (int(x), int(y)), int(radius),
		(0, 255, 255), 2)
	cv2.circle(frame, center, 5, (0, 0, 255), -1)
			
	# print center of circle coordinates
	mapObjectPosition(int(x), int(y))
			
	# if the led is not already on, turn the LED on
	if not ledOn:
		GPIO.output(redLed, GPIO.HIGH)
		ledOn = True

Code snippet #29

Plain text
# position servos to present object at center of the frame
def mapServoPosition (x, y):
    global panAngle
    global tiltAngle
    if (x < 220):
        panAngle += 10
        if panAngle > 140:
            panAngle = 140
        positionServo (panServo, panAngle)
 
    if (x > 280):
        panAngle -= 10
        if panAngle < 40:
            panAngle = 40
        positionServo (panServo, panAngle)

    if (y < 160):
        tiltAngle += 10
        if tiltAngle > 140:
            tiltAngle = 140
        positionServo (tiltServo, tiltAngle)
 
    if (y > 210):
        tiltAngle -= 10
        if tiltAngle < 40:
            tiltAngle = 40
        positionServo (tiltServo, tiltAngle)

Github file

https://github.com/Mjrovai/OpenCV-Object-Face-Tracking/blob/master/simpleCamTest.py

Credits

MJRoBot (Marcelo Rovai)

MJRoBot (Marcelo Rovai)

67 projects • 958 followers
Professor, Engineer, MBA, Master in Data Science. Writes about Electronics with a focus on Physical Computing, IoT, ML, TinyML and Robotics.

Comments