mindspore.ops.CheckValid
- class mindspore.ops.CheckValid[源代码]
Checks bounding box.
Checks whether the bounding box cross data and data border are valid.
Warning
specifying the valid boundary (heights x ratio, weights x ratio).
- Inputs:
bboxes (Tensor) - Bounding boxes tensor with shape (N, 4). “N” indicates the number of bounding boxes, the value “4” indicates “x0”, “x1”, “y0”, and “y1”. Data type must be float16 or float32.
img_metas (Tensor) - Raw image size information with the format of (height, width, ratio), specifying the valid boundary(height * ratio, width * ratio). Data type must be float16 or float32.
- Outputs:
Tensor, with shape of (N,) and dtype of bool, specifying whether the bounding boxes is in the image. “True” indicates valid, while “False” indicates invalid.
- Raises
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> import mindspore >>> import mindspore.nn as nn >>> import numpy as np >>> from mindspore import Tensor, ops >>> class Net(nn.Cell): ... def __init__(self): ... super(Net, self).__init__() ... self.check_valid = ops.CheckValid() ... def construct(self, x, y): ... valid_result = self.check_valid(x, y) ... return valid_result ... >>> bboxes = Tensor(np.linspace(0, 6, 12).reshape(3, 4), mindspore.float32) >>> img_metas = Tensor(np.array([2, 1, 3]), mindspore.float32) >>> net = Net() >>> output = net(bboxes, img_metas) >>> print(output) [ True False False]