TAG-MAC03118/test.py

import numpy as np
import cv2
import glob

filename = '1.jpg'
img = cv2.imread(filename)
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

# out1 = cv2.filter2D(gray, -1, np.array(([-1, -2, -1],[0, 0, 0],[1,2,1])))
# opencvOutput = cv2.filter2D(gray, -1, np.array(([-1, 0, 1],[-2, 0, 2],[-1,0,1])))
# cv2.imshow('dst',opencvOutput+out1)
cv2.imshow('dst',img[:,:,0])
cv2.waitKey(0)
cv2.imshow('dst',img[:,:,1])
cv2.waitKey(0)
cv2.imshow('dst',img[:,:,2])
cv2.waitKey(0)

gray = np.float32(gray)
dst = cv2.cornerHarris(gray,2,3,0.04)

#result is dilated for marking the corners, not important
dst = cv2.dilate(dst,None)

# Threshold for an optimal value, it may vary depending on the image.
img[dst>0.01*dst.max()]=[0,0,255]


if cv2.waitKey(0):
    cv2.destroyAllWindows()

# # 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('*.jpg')


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

#     cv2.imshow('img',img)
#     cv2.waitKey(1000)
#     # # 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)

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

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

# cv2.destroyAllWindows()