前言

進行校準相機，使圖像不失真並進行視角轉換。
目標編寫一個函數，將失真的圖像作為輸入，並完成以下步驟：

1.利用帶有mtx和dist參數之cv2.undistort（）函數使圖像不失真
2.轉換為灰階圖
3.找到棋盤角落
4.畫出角落
5.定義4個源點（棋盤圖案中檢測到的外部4個角）
6.定義4個目標點（必須以與src點相同的順序列出！）
6.使用cv2.getPerspectiveTransform（）來獲得M，即轉換矩陣
7.使用cv2.warpPerspective（）來應用M並將圖像包為自上而下的視圖
提示：源點是棋盤上任意四個角的x和y像素值，可以從cv2.findChessboardCorners（）的角數組輸出中提取這些值。目標點是您希望在輸出圖像中將這四個角映射到的位置的x和y像素值。

實作

我定義了一個函數，corner_unwarp（）。 該函數引數包括圖像和我們先前計算的相機矩陣，mtx和失真係數dist。

# Define a function that takes an image, number of x and y points, 
# camera matrix and distortion coefficients
def corners_unwarp(img, nx, ny, mtx, dist):
    # Use the OpenCV undistort() function to remove distortion
    undist = cv2.undistort(img, mtx, dist, None, mtx)
    # Convert undistorted image to grayscale
    gray = cv2.cvtColor(undist, cv2.COLOR_BGR2GRAY)
    # Search for corners in the grayscaled image
    ret, corners = cv2.findChessboardCorners(gray, (nx, ny), None)

    if ret == True:
        # If we found corners, draw them! (just for fun)
        cv2.drawChessboardCorners(undist, (nx, ny), corners, ret)
        # Choose offset from image corners to plot detected corners
        # This should be chosen to present the result at the proper aspect ratio
        # My choice of 100 pixels is not exact, but close enough for our purpose here
        offset = 100 # offset for dst points
        # Grab the image shape
        img_size = (gray.shape[1], gray.shape[0])

        # For source points I'm grabbing the outer four detected corners
        src = np.float32([corners[0], corners[nx-1], corners[-1], corners[-nx]])
        # For destination points, I'm arbitrarily choosing some points to be
        # a nice fit for displaying our warped result 
        # again, not exact, but close enough for our purposes
        dst = np.float32([[offset, offset], [img_size[0]-offset, offset], 
                                     [img_size[0]-offset, img_size[1]-offset], 
                                     [offset, img_size[1]-offset]])
        # Given src and dst points, calculate the perspective transform matrix
        M = cv2.getPerspectiveTransform(src, dst)
        # Warp the image using OpenCV warpPerspective()
        warped = cv2.warpPerspective(undist, M, img_size)

    # Return the resulting image and matrix
    return warped, M
    

輸出成果：