RoIPool¶
- class paddle.vision.ops. RoIPool ( output_size, spatial_scale=1.0 ) [source]
-
This interface is used to construct a callable object of the RoIPool class. Please refer to roi_pool.
- Parameters
-
output_size (int or tuple[int, int]) – the pooled output size(h, w), data type is int32. If int, h and w are both equal to output_size.
spatial_scale (float, optional) – multiplicative spatial scale factor to translate ROI coords from their input scale to the scale used when pooling. Default: 1.0.
- Returns
-
the pooled feature, 4D-Tensor with the shape of [num_boxes, C, output_size[0], output_size[1]].
- Return type
-
pool_out (Tensor)
Examples
>>> import paddle >>> from paddle.vision.ops import RoIPool >>> data = paddle.rand([1, 256, 32, 32]) >>> boxes = paddle.rand([3, 4]) >>> boxes[:, 2] += boxes[:, 0] + 3 >>> boxes[:, 3] += boxes[:, 1] + 4 >>> boxes_num = paddle.to_tensor([3]).astype('int32') >>> roi_pool = RoIPool(output_size=(4, 3)) >>> pool_out = roi_pool(data, boxes, boxes_num) >>> print(pool_out.shape) [3, 256, 4, 3]
-
forward
(
x,
boxes,
boxes_num
)
forward¶
-
Defines the computation performed at every call. Should be overridden by all subclasses.
- Parameters
-
*inputs (tuple) – unpacked tuple arguments
**kwargs (dict) – unpacked dict arguments
-
extra_repr
(
)
extra_repr¶
-
Extra representation of this layer, you can have custom implementation of your own layer.