third_party/mmyolo/projects/example_project/README.md

Dummy YOLOv5CSPDarknet Wrapper

This is an example README for community projects/. We have provided detailed explanations for each field in the form of html comments, which are visible when you read the source of this README file. If you wish to submit your project to our main repository, then all the fields in this README are mandatory for others to understand what you have achieved in this implementation. For more details, read our contribution guide or approach us in Discussions.

Description

This project implements a dummy YOLOv5CSPDarknet wrapper, which literally does nothing new but prints "hello world" during initialization.

Usage

Training commands

In MMYOLO's root directory, run the following command to train the model:

python tools/train.py projects/example_project/configs/yolov5_s_dummy-backbone_v61_syncbn_8xb16-300e_coco.py

Testing commands

In MMYOLO's root directory, run the following command to test the model:

python tools/test.py projects/example_project/configs/yolov5_s_dummy-backbone_v61_syncbn_8xb16-300e_coco.py ${CHECKPOINT_PATH}

Results

Method	Backbone	Pretrained Model	Training set	Test set	#epoch	box AP	Download
YOLOv5 dummy	DummyYOLOv5CSPDarknet	-	COCO2017 Train	COCO2017 Val	300	37.7	model | log

Citation

@software{glenn_jocher_2022_7002879,
  author       = {Glenn Jocher and
                  Ayush Chaurasia and
                  Alex Stoken and
                  Jirka Borovec and
                  NanoCode012 and
                  Yonghye Kwon and
                  TaoXie and
                  Kalen Michael and
                  Jiacong Fang and
                  imyhxy and
                  Lorna and
                  Colin Wong and
                  曾逸夫(Zeng Yifu) and
                  Abhiram V and
                  Diego Montes and
                  Zhiqiang Wang and
                  Cristi Fati and
                  Jebastin Nadar and
                  Laughing and
                  UnglvKitDe and
                  tkianai and
                  yxNONG and
                  Piotr Skalski and
                  Adam Hogan and
                  Max Strobel and
                  Mrinal Jain and
                  Lorenzo Mammana and
                  xylieong},
  title        = {{ultralytics/yolov5: v6.2 - YOLOv5 Classification
                   Models, Apple M1, Reproducibility, ClearML and
                   Deci.ai integrations}},
  month        = aug,
  year         = 2022,
  publisher    = {Zenodo},
  version      = {v6.2},
  doi          = {10.5281/zenodo.7002879},
  url          = {https://doi.org/10.5281/zenodo.7002879}
}

Checklist

• Milestone 1: PR-ready, and acceptable to be one of the projects/.

  • Finish the code

  • Basic docstrings & proper citation

  • Test-time correctness

  • A full README

• Milestone 2: Indicates a successful model implementation.

  • Training-time correctness

• Milestone 3: Good to be a part of our core package!

  • Type hints and docstrings

  • Unit tests

  • Code polishing

  • Metafile.yml

• Move your modules into the core package following the codebase's file hierarchy structure.

• Refactor your modules into the core package following the codebase's file hierarchy structure.