Refer to the Python documentation/tutorial.
When dealing with documentations in general, you want to understand the underlying use then figure out a way of doing it in another language. For this case for instance, in the C++ API you have to define the type. But in Python, this is not the case. This achieves the same task as the C++ version.
image, contours, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
Now the contours are stored inside contours
EDIT I
A couple things.
- In OpenCV-Python, all images are stored as numpy arrays.
- Due to (1), on top of all the built-in OpenCV functionalities, you can leverage numpy's optimized library to perform quick array manipulations as well. My advise is that you familiarize yourself first with Numpy before moving on to OpenCV.
With that said, here's a small code snippet that addresses your problem and the comments should be self-explanatory.
# findContours returns a tuple
# The first index of this tuple is the image
# Second one holds the actual contours
# The last one gives the respective hierarchy of the contours
image, cnts, hierarchy = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
# from all the contours, extract the largest based off of the area
c = max(cnts, key=cv2.contourArea)
# this will show you that it is an n-dimensional array
print 'Type of c', type(c)
print type(c[0]) # recall that this is a n-dimensional array so we
# have accessed the first row
print c[0][0] # for this row, extract the first column.
# Here is were you have accessed the x, y coordinates.
# Normally, you want this to be stored as a tuple
# to preserve that beautiful (x, y) notation
point = tuple(c[0][0])
x, y = point # there are your coordinates
# you could also do point[0], point[1] to access the x and y respectively.
print x, y
Happy coding!
Cheers :)
