import cv2
camera=cv2.VideoCapture(1)
i = 0
while 1:
    (grabbed, img) = camera.read()
    cv2.imshow('img',img)
    if cv2.waitKey(1) & 0xFF == ord('j'):  # 按j保存一張圖片
        i += 1
        u = str(i)
        firename=str('./img'+u+'.jpg')
        cv2.imwrite(firename, img)
        print('寫入：',firename)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# 相機標定
import cv2
# 修改目錄
# 首先讀取圖像并轉(zhuǎn)為灰度圖
img = cv2.imread('c1.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# cv2.imshow("img",img)
# cv2.imshow("gray",gray)
# 使用OpenCV的cv2.findChessboardCorners()函數(shù)找出棋盤圖中的對角（即圖片中黑白相對的點的坐標）,
# 同時使用cv2.drawChessboardCorners()將之畫出來
# cv2.findChessboardCorners參數(shù)patternSize?。?,5）－－棋盤圖中每行和每列交點的個數(shù)
# 其原因在于導入的圖片./camera_cal/calibration1.jpg數(shù)一下交點的數(shù)目，一行有９個，一列有５個
# Adam博客當中?。?,6）原因在于他的圖和我的圖不一樣，認真數(shù)一下可以發(fā)現(xiàn)他的圖確實是一行９個一列６個角點
# 事實證明，可以取任何只要在size小于圖片中的交點數(shù)即可
# 函數(shù)解析參見官網(wǎng)https://docs.opencv.org/3.3.0/dc/dbb/tutorial_py_calibration.html
# It returns the corner points and retval which will be True if pattern is obtained.
# These corners will be placed in an order (from left-to-right, top-to-bottom)
ret, corners = cv2.findChessboardCorners(gray, (9, 5),None)
print(ret)
print(corners)  # 交點坐標
if ret == True:
    img = cv2.drawChessboardCorners(img, (9, 5), corners, ret)
cv2.imshow("final",img)
cv2.waitKey()
cv2.destroyAllWindows()