這兩種方法在旋轉圖像時，可能會產生一些不同的效果：

rotate_image_new()旋轉后的圖像完全包含旋轉前的內容，并且填充邊界盡可能小

rotate_image() 保持原始圖像的大小，并根據填充選項決定是否填充邊界為白色。如果 if_fill_white 參數為 True，則填充邊界為白色；否則，邊界將保持原始圖像的值。這種方法可以更快速地旋轉圖像，但可能會導致旋轉后的圖像包含額外的空白區(qū)域或丟失部分圖像信息。文章來源地址http://www.zghlxwxcb.cn/news/detail-682386.html

def rotate_image_new(image, degree):
    '''
    旋轉圖片角度
    '''
    from math import *
    # dividing height and width by 2 to get the center of the image
    height, width = image.shape[:2]

    heightNew = int(width * fabs(sin(radians(degree))) + height * fabs(cos(radians(degree))))
    widthNew = int(height * fabs(sin(radians(degree))) + width * fabs(cos(radians(degree))))

    matRotation = cv2.getRotationMatrix2D((width / 2, height / 2), degree, 1)
    matRotation[0, 2] += (widthNew - width) / 2  # 重點在這步，目前不懂為什么加這步
    matRotation[1, 2] += (heightNew - height) / 2  # 重點在這步

    imgRotation = cv2.warpAffine(image, matRotation, (widthNew, heightNew), borderValue=(255, 255, 255))

    return imgRotation

def rotate_image( image, angle,if_fill_white = False):
    '''
    順時針旋轉
    '''
    # dividing height and width by 2 to get the center of the image
    height, width = image.shape[:2]
    # get the center coordinates of the image to create the 2D rotation matrix
    center = (width / 2, height / 2)

    # using cv2.getRotationMatrix2D() to get the rotation matrix
    rotate_matrix = cv2.getRotationMatrix2D(center=center, angle=angle, scale=1)

    # rotate the image using cv2.warpAffine
    if not if_fill_white:
        rotated_image = cv2.warpAffine(src=image, M=rotate_matrix, dsize=(width, height) )
    else:
        color = (255, 255) if len(image.shape)==2 else (255, 255,255)
        rotated_image = cv2.warpAffine(src=image, M=rotate_matrix, dsize=(width, height), borderValue=color)
    return rotated_image

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