Awesome

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

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

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