ResLayer to build ResNet style backbone. Args: block (nn.Module): Residual block used to build ResLayer. num_blocks (int): Nu

ResLayer to build ResNet style backbone. Args: block (nn.Module): Residual block used to build ResLayer. num_blocks (int): Nu

ResLayer to build ResNet style backbone. Args: block (nn.Module): Residual block used to build ResLayer. num_blocks (int): Nu

Base backbone. This class defines the basic functions of a backbone. Any backbone that inherits this class should at least define its own

Base backbone. This class defines the basic functions of a backbone. Any backbone that inherits this class should at least define its own

Bottleneck block for ResNet. Args: in_channels (int): Input channels of this block. out_channels (int): Output channels of th

Bottleneck block for ResNet. Args: in_channels (int): Input channels of this block. out_channels (int): Output channels of th

Bottleneck block for ResNet. Args: in_channels (int): Input channels of this block. out_channels (int): Output channels of th

Feature Pyramid Network. This is an implementation of - Feature Pyramid Networks for Object Detection (https://arxiv.org/abs/1612.03144)

r"""Feature Pyramid Network. This is an implementation of paper `Feature Pyramid Networks for Object Detection <https://arxiv.org/abs/1612

RPN head. Args: in_channels (int): Number of channels in the input feature map.

ResNet backbone. Please refer to the `paper <https://arxiv.org/abs/1512.03385>`_ for details. Args: depth (int): Network d

ResNet backbone. Please refer to the `paper <https://arxiv.org/abs/1512.03385>`_ for details. Args: depth (int): Network d

ResNet backbone. Please refer to the `paper <https://arxiv.org/abs/1512.03385>`_ for details. Args: depth (int): Network d