Transforms bounding boxes so that the boxes remain in the same place in the image after the image is pasted on a larger canvas.
Corner coordinates are transformed according to the following formula:
(x', y') = (x/ratio + paste_x', y/ratio + paste_y')
Box sizes (if
xywhis used) are transformed according to the following formula:
(w', h') = (w/ratio, h/ratio)
paste_x' = paste_x * (ratio - 1)/ratio paste_y' = paste_y * (ratio - 1)/ratio
The paste coordinates are normalized so that
(0,0)aligns the image to top-left of the canvas and
(1,1)aligns it to bottom-right.
- Supported backends
input (TensorList) – Input to the operator.
- Keyword Arguments
ratio (float or TensorList of float) – Ratio of the canvas size to the input size; the value must be at least 1.
bytes_per_sample_hint (int or list of int, optional, default = ) –
Output size hint, in bytes per sample.
If specified, the operator’s outputs residing in GPU or page-locked host memory will be preallocated to accommodate a batch of samples of this size.
ltrb (bool, optional, default = False) – True for
ltrbor False for
paste_x (float or TensorList of float, optional, default = 0.5) – Horizontal position of the paste in image coordinates (0.0 - 1.0).
paste_y (float or TensorList of float, optional, default = 0.5) – Vertical position of the paste in image coordinates (0.0 - 1.0).
preserve (bool, optional, default = False) – Prevents the operator from being removed from the graph even if its outputs are not used.
seed (int, optional, default = -1) –
If not provided, it will be populated based on the global seed of the pipeline.