OpenCV 2.4.9 for Python, cannot find chessboard (camera calibration tutorial)

Question

I am trying to calibrate camera using OpenCV tools according to the following this guide.

The problem is that function findChessboardCorners cannot find any chessboard on images I tried. I used a lot of them - even just plain chessboard pattern. In any case, nothing was detected.

Here is the code (almost the same as from link above):

import numpy as np
import cv2
import glob

# termination criteria
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)

# prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
objp = np.zeros((6*7,3), np.float32)
objp[:,:2] = np.mgrid[0:7,0:6].T.reshape(-1,2)

# Arrays to store object points and image points from all the images.
objpoints = [] # 3d point in real world space
imgpoints = [] # 2d points in image plane.

images = glob.glob('*.png')

for fname in images:
    img = cv2.imread(fname)
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

    # Find the chess board corners
    ret, corners = cv2.findChessboardCorners(gray, (7,6),None)

    # If found, add object points, image points (after refining them)
    if ret == True:
        objpoints.append(objp)

        corners2 = cv2.cornerSubPix(gray,corners,(11,11),(-1,-1),criteria)
        imgpoints.append(corners2)

        # Draw and display the corners
        img = cv2.drawChessboardCorners(img, (7,6), corners2,ret)
        cv2.imshow('img',img)
        cv2.waitKey(500)

cv2.destroyAllWindows()

The only change I made is that i switched from .jpg files to .png files - for some reason, function imread cannot read jpg images (that's another strange problem for other topic).

Thank you in advance for advices!

Image ref:

Seema

This function must be provided with the grid size of the chessboard, which is usually a source of confusion. Could you provide one of your test image to check if it corresponds with a (7,6) chessboard ? – Lewie

Thank you for response. I added one of the images I tried (plain pattern). – Seema

This is a (8,5) pattern. Only the inner squares are considered. – Lewie

Thank you! Actually, this is (9,6) pattern (dimensions = common points of black squares). – Seema

See? Source of confusion :) You're right, the corners of the inner squares should be considered. – Lewie

Answer 1

Just for other Python newbies that may go down this road. Working code:

import numpy as np
import cv2
import glob

# termination criteria
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
# Arrays to store object points and image points from all the images.
imgpoints = [] # 2d points in image plane.
images = glob.glob('*.png')

for fname in images:
    img = cv2.imread(fname)
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    ret = False
    # Find the chess board corners
    ret, corners = cv2.findChessboardCorners(gray, (7,7))
    # If found, add object points, image points (after refining them)
    if ret == True:
        cv2.cornerSubPix(gray, corners, (11,11), (-1,-1), criteria)
        imgpoints.append(corners)
        # Draw and display the corners
        cv2.drawChessboardCorners(img, (7,7), corners, ret)
        cv2.imshow('img',img)
        cv2.waitKey(0)
cv2.destroyAllWindows()

Two main points:

1. You have to carefully count dimension of you pattern. (7,7) is for usual chessboard.

2. Line img = cv2.drawChessboardCorners(img, (7,6), corners2,ret) doesn't work, you have to change it to cv2.drawChessboardCorners(img, (7,6), corners2,ret) (function doesn't return image).

Thanks to AldurDisciple!

Seema