问题描述
如何在 Tensorflow 中将图像裁剪到边界框?我正在使用 Python API.
来自文档,
tf.image.crop_to_bounding_box(image, offset_height, offset_width, target_height, target_width)
将图像裁剪到指定的边界框.
此操作从图像中切出矩形部分.返回图像的左上角在offset_height,offset_width in image,右下角在offset_height + target_height, offset_width + target_width.
我可以在标准化坐标中获得边界框的坐标,
ymin = box[0,i,0]xmin = 盒子[0,i,1]ymax = 盒子[0,i,2]xmax = 盒子[0,i,3]
并将这些转换为绝对坐标,
(xminn, xmaxx, yminn, ymaxx) = (xmin * im_width, xmax * im_width, ymin * im_height, ymax * im_height)
但是我不知道如何在 crop_to_bounding_box
函数中使用这些坐标.
由于我们认为 x
是水平的,而 y
是垂直的,下面将裁剪指定框的图像.
cropped_image = tf.image.crop_to_bounding_box(image, yminn, xminn,ymaxx - yminn,xmaxx - xminn)
How can I crop an image to the bounding box in Tensorflow? I am using the Python API.
From the documentation,
tf.image.crop_to_bounding_box(image, offset_height, offset_width, target_height, target_width)
I can get the coordinates of a bounding box in normalized coordinates as,
ymin = boxes[0,i,0]
xmin = boxes[0,i,1]
ymax = boxes[0,i,2]
xmax = boxes[0,i,3]
and convert these to absolute coordinates,
(xminn, xmaxx, yminn, ymaxx) = (xmin * im_width, xmax * im_width, ymin * im_height, ymax * im_height)
However I cant figure out how to use these coordinates in the crop_to_bounding_box
function.
Since we consider x
as horizontal and y
as vertical, following would crop the image with specified box.
cropped_image = tf.image.crop_to_bounding_box(image, yminn, xminn,
ymaxx - yminn, xmaxx - xminn)
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