color detection using opencv python

Question

I am trying to run a script written using opencv in python which uses webcam to track colored objects (here the object is blue colored), which is also mentioned in opencv's documentation here

import cv2
import numpy as np

cap = cv2.VideoCapture(0)

while(1):

    # Take each frame
    _, frame = cap.read()

    # Convert BGR to HSV
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)

    # define range of blue color in HSV
    lower_blue = np.array([110,50,50])
    upper_blue = np.array([130,255,255])

    # Threshold the HSV image to get only blue colors
    mask = cv2.inRange(hsv, lower_blue, upper_blue)

    # Bitwise-AND mask and original image
    res = cv2.bitwise_and(frame,frame, mask= mask)

    cv2.imshow('frame',frame)
    cv2.imshow('mask',mask)
    cv2.imshow('res',res)
    k = cv2.waitKey(5) & 0xFF
    if k == 27:
        break

cv2.destroyAllWindows()

But this code produces error :

OpenCV Error: Sizes of input arguments do not match (The lower bounary is neither an      array of the same size and same type as src, nor a scalar) in inRange, file     /build/buildd/opencv-2.4.2+dfsg/modules/core/src/arithm.cpp, line 2527
Traceback (most recent call last):
File "blue.py", line 19, in <module>
mask = cv2.inRange(hsv, lower_blue, upper_blue)
cv2.error: /build/buildd/opencv-2.4.2+dfsg/modules/core/src/arithm.cpp:2527: error: (     (-209) The lower bounary is neither an array of the same size and same type as src, nor a scalar in function inRange

I've tried solutions provided in related stackoverflow questions, but none of them helped. What is the problem with the code ? why this error arises ?

I'm using opencv 2.4.2 & python 2.7 on ubuntu

i have a little python background but seems like you have a data type problem. np.array([110, 50, 50], np.uint8) please try this.. — baci
– baci, Commented Jan 3, 2014 at 22:02
:D that worked ! .. I wrote np.array([110, 50, 50], dtype=np.uint8)...and now it works fine ! ty — Vipul
– Vipul, Commented Jan 4, 2014 at 4:54

Vipul · Accepted Answer · 2014-01-12 10:22:23Z

17

The range of blue color in HSV should be given as :

lower_blue = np.array([110, 50, 50], dtype=np.uint8)
upper_blue = np.array([130,255,255], dtype=np.uint8)

answered Jan 12, 2014 at 10:22

Vipul

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Comments

nathancy · Accepted Answer · 2019-10-03 20:34:49Z

Here's a HSV color threshold script to determine the lower and upper ranges instead of guess-and-checking

import cv2
import sys
import numpy as np

def nothing(x):
    pass

# Load in image
image = cv2.imread('1.png')

# Create a window
cv2.namedWindow('image')

# create trackbars for color change
cv2.createTrackbar('HMin','image',0,179,nothing) # Hue is from 0-179 for Opencv
cv2.createTrackbar('SMin','image',0,255,nothing)
cv2.createTrackbar('VMin','image',0,255,nothing)
cv2.createTrackbar('HMax','image',0,179,nothing)
cv2.createTrackbar('SMax','image',0,255,nothing)
cv2.createTrackbar('VMax','image',0,255,nothing)

# Set default value for MAX HSV trackbars.
cv2.setTrackbarPos('HMax', 'image', 179)
cv2.setTrackbarPos('SMax', 'image', 255)
cv2.setTrackbarPos('VMax', 'image', 255)

# Initialize to check if HSV min/max value changes
hMin = sMin = vMin = hMax = sMax = vMax = 0
phMin = psMin = pvMin = phMax = psMax = pvMax = 0

output = image
wait_time = 33

while(1):

    # get current positions of all trackbars
    hMin = cv2.getTrackbarPos('HMin','image')
    sMin = cv2.getTrackbarPos('SMin','image')
    vMin = cv2.getTrackbarPos('VMin','image')

    hMax = cv2.getTrackbarPos('HMax','image')
    sMax = cv2.getTrackbarPos('SMax','image')
    vMax = cv2.getTrackbarPos('VMax','image')

    # Set minimum and max HSV values to display
    lower = np.array([hMin, sMin, vMin])
    upper = np.array([hMax, sMax, vMax])

    # Create HSV Image and threshold into a range.
    hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
    mask = cv2.inRange(hsv, lower, upper)
    output = cv2.bitwise_and(image,image, mask= mask)

    # Print if there is a change in HSV value
    if( (phMin != hMin) | (psMin != sMin) | (pvMin != vMin) | (phMax != hMax) | (psMax != sMax) | (pvMax != vMax) ):
        print("(hMin = %d , sMin = %d, vMin = %d), (hMax = %d , sMax = %d, vMax = %d)" % (hMin , sMin , vMin, hMax, sMax , vMax))
        phMin = hMin
        psMin = sMin
        pvMin = vMin
        phMax = hMax
        psMax = sMax
        pvMax = vMax

    # Display output image
    cv2.imshow('image',output)

    # Wait longer to prevent freeze for videos.
    if cv2.waitKey(wait_time) & 0xFF == ord('q'):
        break

cv2.destroyAllWindows()

Shashiben · Accepted Answer · 2020-05-29 15:47:50Z

0

In order to detect the object based on color in OpenCV-python, I think this repo will help you check out this GitHub repo:

https://github.com/shashiben/Opencv/blob/master/Object%20Detection/object_detect_with_hsv.py

I did track the object based on HSV color using trackbar

answered May 29, 2020 at 15:47

Shashiben

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1 Comment

dboy Over a year ago

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