ResNet31OCR¶

class mmocr.models.textrecog.ResNet31OCR(base_channels=3, layers=[1, 2, 5, 3], channels=[64, 128, 256, 256, 512, 512, 512], out_indices=None, stage4_pool_cfg={'kernel_size': (2, 1), 'stride': (2, 1)}, last_stage_pool=False, init_cfg=[{'type': 'Kaiming', 'layer': 'Conv2d'}, {'type': 'Uniform', 'layer': 'BatchNorm2d'}])[source]¶

Implement ResNet backbone for text recognition, modified from: ResNet

Parameters

base_channels (int) – Number of channels of input image tensor.
layers (list[int]) – List of BasicBlock number for each stage.
channels (list[int]) – List of out_channels of Conv2d layer.
out_indices (None | Sequence[int]) – Indices of output stages.
stage4_pool_cfg (dict) – Dictionary to construct and configure pooling layer in stage 4.
last_stage_pool (bool) – If True, add MaxPool2d layer to last stage.

forward(x)[source]¶

Defines the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.