如何找到旋转图像边界框的新坐标来修改其xml文件以进行Tensorflow数据扩充?

我正在尝试制作更多的数据集,以便在Tensorflow中为数据挖掘训练模型。我将边界框的标签添加到原始图像中。我想将图像旋转45度,并修改新的精确边界框(矩形)的xml文件来标记新创建的图像。它正在调整大小并提取到窗口,以避免丢失图像上的任何内容。

让我告诉你我是如何尝试的:

def rotateImage(mat, angle):
    height, width = mat.shape[:2]
    image_center = (width / 2, height / 2)

    rotation_mat = cv2.getRotationMatrix2D(image_center, angle, 1)

    radians = math.radians(angle)
    sin = math.sin(radians)
    cos = math.cos(radians)
    bound_w = int((height * abs(sin)) + (width * abs(cos)))
    bound_h = int((height * abs(cos)) + (width * abs(sin)))

    rotation_mat[0, 2] += ((bound_w / 2) - image_center[0])
    rotation_mat[1, 2] += ((bound_h / 2) - image_center[1])

    rotated_mat = cv2.warpAffine(mat, rotation_mat, (bound_w, bound_h))
    return rotated_mat


image = cv2.imread("test.jpg")

angle = 45

rotated_45_image = image.copy()

rotated_45_image = rotateImage(rotated_45_image, angle=45)

tree_for_45_rotated = ET.parse(file_name + ".xml")
root = tree_for_xml.getroot()

for object in root.iter("object"):
    xmin = object.find("bndbox").find("xmin")
    ymin = object.find("bndbox").find("ymin")
    xmax = object.find("bndbox").find("xmax")
    ymax = object.find("bndbox").find("ymax")
    print(xmin.text, ymin.text, xmax.text, ymax.text)
    print("new")
    new_xmin = math.cos(angle) * int(xmin.text) - math.sin(angle) * int(ymin.text)
    new_xmax = math.cos(angle) * int(xmax.text) - math.sin(angle) * int(ymin.text)
    new_ymin = math.sin(angle) * int(xmin.text) + math.cos(angle) * int(ymin.text)
    new_ymax = math.sin(angle) * int(xmin.text) + math.cos(angle) * int(ymax.text)
    print(new_xmin, new_ymin, new_xmax, new_ymax)

顺便说一下,我正在使用Python和OpenCV。我无法计算精确的新坐标来标记图像。

谢谢