FPN_UNet

class mmocr.models.textdet.FPN_UNet(in_channels, out_channels, init_cfg={'distribution': 'uniform', 'layer': ['Conv2d', 'ConvTranspose2d'], 'type': 'Xavier'})

The class for implementing DRRG and TextSnake U-Net-like FPN.

DRRG: Deep Relational Reasoning Graph Network for Arbitrary Shape Text Detection.

TextSnake: A Flexible Representation for Detecting Text of Arbitrary Shapes.

Parameters

• in_channels (list[int]) – Number of input channels at each scale. The length of the list should be 4.

• out_channels (int) – The number of output channels.

• init_cfg (dict or list[dict], optional) – Initialization configs.

Return type

None

forward(x)

Parameters

x (list[Tensor] | tuple[Tensor]) – A list of four tensors of shape \((N, C_i, H_i, W_i)\), representing C2, C3, C4, C5 features respectively. \(C_i\) should matches the number in in_channels.

Returns

Shape \((N, C, H, W)\) where \(H=4H_0\) and \(W=4W_0\).

Return type

Tensor