ChannelReductionEncoder

class mmocr.models.textrecog.ChannelReductionEncoder(in_channels, out_channels, init_cfg={'layer': 'Conv2d', 'type': 'Xavier'})

Change the channel number with a one by one convoluational layer.

Parameters

• in_channels (int) – Number of input channels.

• out_channels (int) – Number of output channels.

• init_cfg (dict or list[dict], optional) – Initialization configs. Defaults to dict(type=’Xavier’, layer=’Conv2d’).

Return type

None

forward(feat, data_samples=None)

Parameters

• feat (Tensor) – Image features with the shape of \((N, C_{in}, H, W)\).

• data_samples (list[TextRecogDataSample], optional) – Batch of TextRecogDataSample, containing valid_ratio information. Defaults to None.

Returns

A tensor of shape \((N, C_{out}, H, W)\).

Return type

Tensor