Assertion failed (m.dims >= 2) in Mat - python-3.x

Question

Here is the code for image thresholding I am getting the error at line 22,
which is:-
ret,thresh2 = cv2.threshold(img,127,255,cv2.THRESH_BINARY_INV)
Here in this code I want to capture image frames from the video camera and then perform various kinds of thresholding operations on the captured image frames.
I have stored image frames at various instances of time. My objective is to segment the moving objects in the video. Hence I am applying thresholding operation.
Does anybody have any idea, how to do it?
Thanks in advance.
import cv2
import numpy as np
import time
from matplotlib import pyplot as plt
import sys
cam = cv2.VideoCapture(0)
while(cam.isOpened()):
ret, frame = cam.read() #Keep on capturing the frames continuously
while (ret==True):
#img = cv2.imread('/home/shrikrishna/Detection&Tracking/OpenCV-Tutorial',6)
cv2.imwrite('At time'+ str(time.clock()) + '.jpg', frame)
img2 = cv2.imread('At time'+ str(time.clock()) + '.jpg',6)
t = str(time.clock())
cv2.imshow('Orignal',frame)
k = cv2.waitKey(0) & 0xffff
if(k==27):
#img = cv2.imread('At time'+ str(time.clock()) + '.jpg',6)
break
if(k==ord('q')):
sys.exit(0)
break
#cv2.imwrite('At time'+ t + '.jpg', frame)
img = cv2.imread('At time'+ t + '.jpg',6)
ret,thresh1 = cv2.threshold(img,127,255,cv2.THRESH_BINARY)
ret,thresh2 = cv2.threshold(img,127,255,cv2.THRESH_BINARY_INV)
ret,thresh3 = cv2.threshold(img,127,255,cv2.THRESH_TRUNC)
ret,thresh4 = cv2.threshold(img,127,255,cv2.THRESH_TOZERO)
ret,thresh5 = cv2.threshold(img,127,255,cv2.THRESH_TOZERO_INV)
titles = ['Original Image','BINARY','BINARY_INV','TRUNC','TOZERO','TOZERO_INV']
images = [img, thresh1, thresh2, thresh3, thresh4, thresh5]
for i in xrange(6):
plt.subplot(2,3,i+1),plt.imshow(images[i],'gray')
plt.title(titles[i])
plt.xticks([]),plt.yticks([])
plt.show()
cv2.waitKey(0)
cv2.destroyAllWindows()

Answer 1

In the following line, you read in an image as colour image (based on the second parameter -- flags).
img = cv2.imread('At time'+ t + '.jpg',6)
This means that img contains 3 channels, which in Python is represented by a 3-dimensional array.
You immediately use this image as the source for thresholding:
ret,thresh1 = cv2.threshold(img,127,255,cv2.THRESH_BINARY)
According to the documentation, the first parameter to threshold() is:
src – input array (single-channel, 8-bit or 32-bit floating point).
That means you need a single channel image, e.g. a grayscale image:
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
ret,thresh1 = cv2.threshold(img_gray,127,255,cv2.THRESH_BINARY)
# ...
Another option would be to just read the image as grayscale in first place:
img_gray = cv2.imread('At time'+ t + '.jpg',0)
# ...