如何找到旋转图像边界框的新坐标以修改其xml文件以进行Tensorflow数据增强? [英] How can I find new coordinates of boundary box of rotated image to modify its xml file for Tensorflow data augmentation?

问题描述

我正在尝试创建更多数据集以在Tensorflow中训练我的模型以获取数据提示.我将边界框的标签添加到原始图像.我想将图像旋转45度，并为新的精确边界框(矩形)修改xml文件，以标记新创建的图像.它正在调整大小并提取到窗口以不丢失图像上的任何内容.

I'm trying to make more dataset to train my model in Tensorflow for data augmantaion. I added the labels of boundary boxes to original image. I want to rotate image 45 degree and modify the xml file for the new exact boundary box(rectangle) to label new created image. It's resizing and fetching to window to not to loose anything on image.

让我告诉你我如何尝试:

Let me show you how I try:

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)

旋转后，图像如下所示:

After rotation the image is like this:

顺便说一句，我正在使用Python和OpenCV.我无法计算出确切的新坐标来标记图像.

By the way, I'm using Python and OpenCV. I can't calculate the exact new coordinates to label the image.

谢谢

推荐答案

我无法在上面的帖子中添加评论，因此对这篇帖子感到抱歉.您所需要做的就是在 corners

I cannot add a comment in the post above, so sorry for the post. All you need is print after rotation values from corners

img = cv2.imread("test.jpg")
rotated, corners = rotateImage(img, 30)
print(corners)

，如果要特定值，请使用

and if you want a specific value just use

print(corners[0])
print(corners[1])
print(corners[2])
print(corners[3])

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