Skip to content
This repository has been archived by the owner on Jan 2, 2021. It is now read-only.
/ yolo_nano Public archive
forked from liux0614/yolo_nano

Unofficial implementation of yolo nano

License

Notifications You must be signed in to change notification settings

Sxela/yolo_nano

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

41 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Introduction

YOLO nano is from this paper.

TODO

Since I'm too busy at the end of the semester, I will continue working on this project after my exams.

  • Finish a draft version of implementation
  • Add README
  • Add checkpoint support
  • Add COCO dataset support (Code still needs cleaning. I'm working on it.)
  • Add multi scale and horizontal flip transforms
  • Reconstruct the code of visualizer
  • Add val and test
  • Add VOC support
  • Test accuracy

Installation

git clone https://github.com/liux0614/yolo_nano
pip3 install -r requirements.txt

COCO

Project Structure

root/
  results/
  datasets/
    coco/
      images/
        train/
        val/
      annotation/
        instances_train2017.json
        instances_val2017.json

Train

To use COCO dataset loader, pycocotools should be installed via the following command.

pip install "git+https://github.com/philferriere/cocoapi.git#egg=pycocotools&subdirectory=PythonAPI"

To train on COCO dataset:

python3 main.py --dataset_path datasets/coco/images --annotation_path datasets/coco/annotation/instances_train2017.json 
                --dataset coco --lr 0.0001 --conf_thres 0.8 --nms_thres 0.5

About

Unofficial implementation of yolo nano

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%