DeformConv2dPack

class mmcv.ops.DeformConv2dPack(*args, **kwargs)

A Deformable Conv Encapsulation that acts as normal Conv layers.

The offset tensor is like [y0, x0, y1, x1, y2, x2, …, y8, x8]. The spatial arrangement is like:

(x0, y0) (x1, y1) (x2, y2)
(x3, y3) (x4, y4) (x5, y5)
(x6, y6) (x7, y7) (x8, y8)

Parameters

• in_channels (int) – Same as nn.Conv2d.

• out_channels (int) – Same as nn.Conv2d.

• kernel_size (int or tuple[int]) – Same as nn.Conv2d.

• stride (int or tuple[int]) – Same as nn.Conv2d.

• padding (int or tuple[int]) – Same as nn.Conv2d.

• dilation (int or tuple[int]) – Same as nn.Conv2d.

• groups (int) – Same as nn.Conv2d.

• bias (bool or str) – If specified as auto, it will be decided by the norm_cfg. Bias will be set as True if norm_cfg is None, otherwise False.

forward(x: torch.Tensor) → torch.Tensor

Deformable Convolutional forward function.

Parameters

• x (Tensor) – Input feature, shape (B, C_in, H_in, W_in)

• offset (Tensor) –

  Offset for deformable convolution, shape (B, deform_groups*kernel_size[0]*kernel_size[1]*2, H_out, W_out), H_out, W_out are equal to the output’s.

  An offset is like [y0, x0, y1, x1, y2, x2, …, y8, x8]. The spatial arrangement is like:

  (x0, y0) (x1, y1) (x2, y2)
  (x3, y3) (x4, y4) (x5, y5)
  (x6, y6) (x7, y7) (x8, y8)
  

Returns

Output of the layer.

Return type

Tensor