Batwan01 / 2024-Autonomous-Driving-Artificial-Intelligence-Challenge

κ³Όν•™κΈ°μˆ μ •λ³΄ν†΅μ‹ λΆ€ - 2024λ…„ μžμœ¨μ£Όν–‰ 인곡지λŠ₯ μ±Œλ¦°μ§€ : μ‹ ν˜Έλ“± 인식 λΆ€λ¬Έ (KaKao-mobility λŒ€ν‘œμƒ)
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πŸ’‘ ν”„λ‘œμ νŠΈ μ†Œκ°œ

car2

:sunglasses:νŒ€μ› μ†Œκ°œ

μ •ν˜„μš° μž„μ°¬ν˜ 박지완 μ΅œμž¬ν›ˆ

데이터셋 정보

데이터셋 톡계

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데이터 ν˜•νƒœ

μ‹ ν˜Έλ“± μœ ν˜• 클래슀 이름(번호) μ‹ ν˜Έλ“± μœ ν˜• 클래슀 이름(번호)
μ°¨λŸ‰ μ‹ ν˜Έλ“± Go (0) λ³΄ν–‰μž μ‹ ν˜Έλ“± Go (7)
GoLeft (1) NoSign (8)
NoSign (2) Stop (9)
Stop (3) λ²„μŠ€ μ‹ ν˜Έλ“± Go (10)
StopLeft (4) NoSign (11)
StopWarning (5) Stop (12)
Warning (6) Warning (13)

Models

Model Backbone Pre-trained Epochs oversampling Image size val mAP50
yolo C3K2 yolo11x 20 X 1280x1280 0.6010
Co-DINO Swin-L Object365,COCO 1 X 1024x1024 0.6407
Co-DINO Swin-L Object365,COCO 2 X 1024x1024 0.6821
Co-DINO Swin-L Object365,COCO 3 X 1024x1024 0.6833
Co-DINO Swin-L Object365,COCO 1 O 1024x1024 0.6990
Cascade-RCNN Swin-L COCO 5 X 1024x1024 0.6819
Cascade-RCNN Swin-L COCO 2 X 1024x1024 0.6390
Cascade-RCNN Swin-L COCO 2 O 1024x1024 0.6875

This project is released OpenMMLab / λͺ¨λΈ μ„±λŠ₯ν‘œ

Ensemble

앙상블 기법 Co-DINO 1ep over Co-DINO 1ep Co-DINO 2ep Co-DINO 3ep Cascade-RCNN 5ep Cascade-RCNN 2ep Cascade-RCNN 2ep over Test mAP50
NMW o o o o 0.6945
NMW o o o o 0.7344
Classwise o o o o o o 0.7362

Results

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How to use