https://github.com/liux0614/yolo_nano

Unofficial implementation of yolo nano
https://github.com/liux0614/yolo_nano

Last synced: 3 months ago
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Unofficial implementation of yolo nano

• Host: GitHub
• URL: https://github.com/liux0614/yolo_nano
• Owner: liux0614
• License: mit
• Created: 2019-10-15T20:46:33.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2023-10-03T21:38:03.000Z (over 1 year ago)
• Last Synced: 2024-08-02T01:18:27.149Z (7 months ago)
• Language: Python
• Homepage:
• Size: 447 KB
• Stars: 254
• Watchers: 12
• Forks: 72
• Open Issues: 22
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-yolo-object-detection - liux0614/yolo_nano
• awesome-yolo-object-detection - liux0614/yolo_nano

README

        
# Introduction

YOLO nano is from this [paper](https://arxiv.org/abs/1910.01271).

# TODO

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

- [x] Finish a draft version of implementation

- [x] Add README

- [x] Add checkpoint support

- [x] Add COCO dataset support (Code still needs cleaning. I'm working on it.)

- [x] Add _multi scale_ and _horizontal flip_ transforms

- [x] Reconstruct the code of visualizer

- [x] Add val and test

- [ ] Add VOC support

- [ ] Test accuracy

# Installation

```bash

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.

```bash 

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

```

To train on COCO dataset:

```bash

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

```