mmsegmentation/configs/fastscnn
sennnnn d3dc4f9583 [Enhancement] Add Dev tools to boost develop (#798)
* Modify default work dir when training.

* Refactor gather_models.py.

* Add train and test matching list.

* Regression benchmark list.

* lower readme name to upper readme name.

* Add url check tool and model inference test tool.

* Modify tool name.

* Support duplicate mode of log json url check.

* Add regression benchmark evaluation automatic tool.

* Add train script generator.

* Only Support script running.

* Add evaluation results gather.

* Add exec Authority.

* Automatically make checkpoint root folder.

* Modify gather results save path.

* Coarse-grained train results gather tool.

* Complete benchmark train script.

* Make some little modifications.

* Fix checkpoint urls.

* Fix unet checkpoint urls.

* Fix fast scnn & fcn checkpoint url.

* Fix fast scnn checkpoint urls.

* Fix fast scnn url.

* Add differential results calculation.

* Add differential results of regression benchmark train results.

* Add an extra argument to select model.

* Update nonlocal_net & hrnet checkpoint url.

* Fix checkpoint url of hrnet and Fix some tta evaluation results and modify gather models tool.

* Modify fast scnn checkpoint url.

* Resolve new comments.

* Fix url check status code bug.

* Resolve some comments.

* Modify train scripts generator.

* Modify work_dir of regression benchmark results.

* model gather tool modification.
2021-09-02 09:44:51 -07:00
..
README.md [Enhancement] Add Dev tools to boost develop (#798) 2021-09-02 09:44:51 -07:00
fast_scnn_lr0.12_8x4_160k_cityscapes.py [Fix] fix fast scnn (#606) 2021-07-02 17:58:35 +08:00
fastscnn.yml [Enhancement] Add Dev tools to boost develop (#798) 2021-09-02 09:44:51 -07:00

README.md

Fast-SCNN for Semantic Segmentation

Introduction

@article{poudel2019fast,
  title={Fast-scnn: Fast semantic segmentation network},
  author={Poudel, Rudra PK and Liwicki, Stephan and Cipolla, Roberto},
  journal={arXiv preprint arXiv:1902.04502},
  year={2019}
}

Results and models

Cityscapes

Method Backbone Crop Size Lr schd Mem (GB) Inf time (fps) mIoU mIoU(ms+flip) config download
Fast-SCNN Fast-SCNN 512x1024 160000 3.3 56.45 70.96 72.65 config model | log