# mmseg 模型支持列表 mmseg 是一个基于 PyTorch 的开源对象分割工具箱,也是 [OpenMMLab](https://openmmlab.com/) 项目的一部分。 ## 安装 mmseg 参照 [get_started.md](https://github.com/open-mmlab/mmsegmentation/blob/master/docs/en/get_started.md#installation)。 ## 支持列表 | Model | OnnxRuntime | TensorRT | ncnn | PPLNN | OpenVino | Model config | | :--------------------------- | :---------: | :------: | :--: | :---: | :------: | :--------------------------------------------------------------------------------------: | | FCN | Y | Y | Y | Y | Y | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/fcn) | | PSPNet[\*](#static_shape) | Y | Y | Y | Y | Y | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/pspnet) | | DeepLabV3 | Y | Y | Y | Y | Y | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/deeplabv3) | | DeepLabV3+ | Y | Y | Y | Y | Y | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/deeplabv3plus) | | Fast-SCNN[\*](#static_shape) | Y | Y | N | Y | Y | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/fastscnn) | | UNet | Y | Y | Y | Y | Y | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/unet) | | ANN[\*](#static_shape) | Y | Y | N | N | N | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/ann) | | APCNet | Y | Y | Y | N | N | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/apcnet) | | BiSeNetV1 | Y | Y | Y | N | Y | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/bisenetv1) | | BiSeNetV2 | Y | Y | Y | N | Y | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/bisenetv2) | | CGNet | Y | Y | Y | N | Y | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/cgnet) | | DMNet | Y | N | N | N | N | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/dmnet) | | DNLNet | Y | Y | Y | N | Y | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/dnlnet) | | EMANet | Y | Y | N | N | Y | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/emanet) | | EncNet | Y | Y | N | N | Y | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/encnet) | | ERFNet | Y | Y | Y | N | Y | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/erfnet) | | FastFCN | Y | Y | Y | N | Y | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/fastfcn) | | GCNet | Y | Y | N | N | N | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/gcnet) | | ICNet[\*](#static_shape) | Y | Y | N | N | Y | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/icnet) | | ISANet | Y | Y | N | N | Y | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/isanet) | | NonLocal Net | Y | Y | Y | N | Y | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/nonlocal_net) | | OCRNet | Y | Y | Y | N | Y | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/ocrnet) | | PointRend | Y | Y | N | N | Y | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/point_rend) | | Semantic FPN | Y | Y | Y | N | Y | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/sem_fpn) | | STDC | Y | Y | Y | N | Y | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/stdc) | | UPerNet[\*](#static_shape) | Y | Y | N | N | N | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/upernet) | | DANet | Y | Y | N | N | Y | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/danet) | | Segmenter[\*](#static_shape) | Y | Y | Y | N | Y | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/segmenter) | | SegFormer[\*](#static_shape) | Y | Y | N | N | Y | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/segformer) | | SETR | Y | N | N | N | Y | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/setr) | | CCNet | N | N | N | N | N | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/ccnet) | | PSANet | N | N | N | N | N | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/psanet) | | DPT | N | N | N | N | N | [config](https://github.com/open-mmlab/mmsegmentation/tree/master/configs/dpt) | ## 注意事项 - 所有 mmseg 模型仅支持 "whole" 推理模式。 - PSPNet,Fast-SCNN 仅支持静态输入,因为多数推理框架的 [nn.AdaptiveAvgPool2d](https://github.com/open-mmlab/mmsegmentation/blob/97f9670c5a4a2a3b4cfb411bcc26db16b23745f7/mmseg/models/decode_heads/psp_head.py#L38) 不支持动态输入。 - 对于仅支持静态形状的模型,应使用静态形状的部署配置文件,例如 `configs/mmseg/segmentation_tensorrt_static-1024x2048.py`