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Reputation: 139

Color tracking by OpenCV and Python error with findContours Function

I want to track 3 colors, but I have a problem with this statement:

(ti,contours,hierarchy)=cv2.findContours(red,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)

ValueError: need more than 2 values to unpack

When I try: (contours,hierarchy)=cv2.findContours(red,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)

There is no error but the variables contours and hierarchy are empty and I get the following error for cv2.imshow("Color Tracking",img):

"error in size img"

I used Python 2.7 and OpenCV 2.4.

My code is :

#importing modules

import cv2   
import numpy as np

#capturing video through webcam
webcam = cv2.VideoCapture(0)

while(webcam.isOpened()):

    ret, img = webcam.read()
    if ret:
        hsv=cv2.cvtColor(img,cv2.COLOR_BGR2HSV)

    #definig the range of red color
        red_lower=np.array([136,87,111],np.uint8)
        red_upper=np.array([180,255,255],np.uint8)

    #defining the Range of Blue color
        blue_lower=np.array([99,115,150],np.uint8)
        blue_upper=np.array([110,255,255],np.uint8)

    #defining the Range of yellow color
        yellow_lower=np.array([22,60,200],np.uint8)
        yellow_upper=np.array([60,255,255],np.uint8)

    #finding the range  of red,blue and yellow color in the image
        red=cv2.inRange(hsv, red_lower, red_upper)
        blue=cv2.inRange(hsv,blue_lower,blue_upper)
        yellow=cv2.inRange(hsv,yellow_lower,yellow_upper)

    #Morphological transformation, Dilation     
        kernal = np.ones((5 ,5), "uint8")

        red=cv2.dilate(red, kernal)
        res=cv2.bitwise_and(img, img, mask = red)

        blue=cv2.dilate(blue,kernal)
        res1=cv2.bitwise_and(img, img, mask = blue)

        yellow=cv2.dilate(yellow,kernal)
        res2=cv2.bitwise_and(img, img, mask = yellow)    


       #Tracking the Red Color
        (ti,contours,hierarchy)=cv2.findContours(red,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
        #cv2.findContours(red, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE[, contours[, hierarchy[, offset]]])
        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),(0,0,255),2)
                cv2.putText(img,"RED color",(x,y),cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0,0,255))

    #Tracking the Blue Color
        (ti,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 color",(x,y),cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255,0,0))

    #Tracking the yellow Color
        (ti,contours,hierarchy)=cv2.findContours(yellow,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),(0,255,0),2)
                cv2.putText(img,"yellow  color",(x,y),cv2.FONT_HERSHEY_SIMPLEX, 1.0, (0,255,0))  
        #cv2.imshow("Redcolour",red)
        cv2.imshow("Color Tracking",img)
        #cv2.imshow("red",res)  
        if cv2.waitKey(10) & 0xFF == ord('q'):
                cap.release()
                cv2.destroyAllWindows()
                break

Upvotes: 3

Views: 896

Answers (1)

charlie maere
charlie maere

Reputation: 21

Hi i tried to replicate your error what i have noted is that there is no control in your code that checks if those colors you have set are available or not in a frame. this is the reason why you get error in img size as it did not find any matching color and it has masked an empty array. my advice is try the code with a single frame and single color like this:

import cv2   
import numpy as np
img = cv2.imread('frame1.jpg')
#Convert BGR to HSV
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
kernal = np.ones((5 ,5), "uint8")
# define range of blue color in HSV
yellow_lower=np.array([22,60,200],np.uint8)
yellow_upper=np.array([60,255,255],np.uint8)
# Threshold the HSV image to get only blue colors
yellow=cv2.inRange(hsv,yellow_lower,yellow_upper)
yellow=cv2.dilate(yellow,kernal)
res2=cv2.bitwise_and(img, img, mask = yellow) 
(ti,contours,hierarchy)=cv2.findContours(yellow,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),(0,255,0),2)
        cv2.putText(img,"yellow  color",(x,y),cv2.FONT_HERSHEY_SIMPLEX, 1.0, (0,255,0))  

cv2.imshow("Color Tracking",img)
cv2.waitKey(0)

Upvotes: 1

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