CODEWITHSUNDEEP
pythonopencv
stackoverflowuser2010
stackoverflowuser2010

Reputation: 40909

Shape of corners array returned by findChessboardCorners()

I'm using the OpenCV function findChessboardCorners() successfully, but I'm confused by the shape of the corners return value.

Here is my code below. I already know that my chessboard image has 8 x 6 internal corners.

import cv2

nx = 8
ny = 6

img = cv2.imread('test_image2.png')
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

ret, corners = cv2.findChessboardCorners(img, (nx, ny), None)
print(corners.shape)

The last line prints: (48, 1, 2).

Where does the 1 come from? I know there are 8 * 6 = 48 corners, and each corner has 2 coordinates. But what about the 1?

The documentation for findChessboardCorners() doesn't say anything about the corners result:

corners – Output array of detected corners.

Upvotes: 2

Views: 662

Answers (1)

Yunus Temurlenk
Yunus Temurlenk

Reputation: 4367

It is an unwanted and unnecessary dimension, you can eliminate the dimension by using the squeeze function of numpy:

 corners = np.squeeze(corners)

In this documentation, they have also mentioned in comment line as "extraneous singleton dimension" :

corners = np.squeeze(corners) # Get rid of extraneous singleton dimension

Edit:

I simply switched the code to C++ side to dig into. Lastly, here is the code and console output of it:

std::ccorners<<corners.rows<<"  "<<corners.cols<<"  "<<corners.dims<<std::endl;

Output:

48 1  2

So the output you are getting gives respectively:

  • rows number -> corner numbers
  • column number -> 1 as default because there is only one data to give
  • matrix dimensionality -> which is 2, number of data pair in each rows( coordinates )

Upvotes: 2

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