PSRoIPool¶
- class paddle.vision.ops. PSRoIPool ( output_size, spatial_scale=1.0 ) [source]
- 
         This interface is used to construct a callable object of the PSRoIPoolclass. Please refer to psroi_pool.- Parameters
- 
           - output_size (int|Tuple(int, int)) The pooled output size(H, W) – 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. 
 
 - Shape:
- 
           - x: 4-D Tensor with shape (N, C, H, W). 
- boxes: 2-D Tensor with shape (num_rois, 4). 
- boxes_num: 1-D Tensor. 
- 
             - output: 4-D tensor with shape (num_rois, output_channels, pooled_h, pooled_w).
- 
               The output_channels equal to C / (pooled_h * pooled_w), where C is the channels of input. 
 
 
 - Returns
- 
           None. 
 Examples import paddle psroi_module = paddle.vision.ops.PSRoIPool(7, 1.0) x = paddle.uniform([2, 490, 28, 28], dtype='float32') boxes = paddle.to_tensor([[1, 5, 8, 10], [4, 2, 6, 7], [12, 12, 19, 21]], dtype='float32') boxes_num = paddle.to_tensor([1, 2], dtype='int32') pool_out = psroi_module(x, boxes, boxes_num) print(pool_out.shape) # [3, 10, 7, 7] - 
            
           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 
 
 
 
