Gender and age classification for wearing mask image

This project is the Naver Boost Camp CV11 team's submission code for the trash object detection competition. Given an image containing a garbage object, it is a matter of specifying the location of the garbage and classifying the class.

Team Members

김용희	박승희	이윤표	이준하	주재영

Environment

• OS : Linux Ubuntu 18.04.5
• GPU : Tesla V100 (32GB)

Folder Structure

├─eda
├─ensemble
├─mmdetection
├─mmdetection3
├─UniverseNet
├─yolov8
├─multilabel_kfold.py
└─streamlit

Usage

Install Requirements

• pip install -r requirements.txt

Multilabel_Kfold.py

You can enter the multilabel_kfold.py folder path and enter the command or enter the multilabel_kfold directly into the command

python3 level2_objectdetection-cv-11/multilabel_Kfold.py --K {kfold split count}

train.sh

1. Move the path to the tools folder where the train.sh file is located

2. Write python3 main.py command in train.sh file

   python3 main.py --model {.py name} --folder {folder_name} --resize {size} --max_epoch {epoch} --inference_epoch {best/latest}

3. Run

   nohup sh train.sh

Result

Augmentation experiment result

Metric : mAP score

augmentation	mAP50	General trash(0)	Plastic(5)	total
Normalize	0.346174	0.173843	0.280453	0.80047
HorizontalFlip	0.317365	0.17596	0.254375	0.7477
Mosaic	0.328192	0.16313	0.252239	0.743561
RGBShift	0.324352	0.152785	0.248293	0.72543
MedianBlur	0.317173	0.145847	0.25099	0.71401
HueSaturation	0.310931	0.163762	0.238093	0.712786
Cutout	0.311202	0.157962	0.2429	0.712064
CLAHE	0.308945	0.158813	0.240687	0.708445
JpegCompression	0.32155	0.16028	0.22024	0.70207
RandomBrightnessContrast	0.312545	0.144382	0.238167	0.695094
Multiresize	0.29278	0.15752	0.235295	0.685595

Final Solution

Metric : mAP score

Library	TYPE	Method	Backbone	Neck	Datasets	Scheduler	Runtime	Optimizer	mAP(public)
mmdetection2	2stage	Cascade RCNN	Swin transformer base	FPN	albu_coco_detection	schedule	default_runtime	AdamW	0.6671
UniverseNet	1stage	UniverseNet	Res2Net_101	FPN / SEPC	albu_coco_detection	schedule_20e	default_runtime	AdamW	0.61
UniverseNet	1stage	ATSS	Swin transformer large	FPN / Dyhead	albu_coco_detection	schedule_20e	default_runtime	AdamW	0.6237
UniverseNet	2stage	GFLv2	PVT_v2	FPN	albu_coco_detection	schedule_2x	default_runtime	SGD	0.5693
UniverseNet	1stage	TOOD	Swin transformer v2 tiny	FPN	albu_coco_detection	schedule_adamw	default_runtime	AdamW	0.54
YOLOv8	1stage	YOLOv8_l	Darknet	-	recycle.yaml	-	-	-	0.3822

Ensemble

• Final submission : Public : 0.6878(5th) / Private : 0.6720(5th)