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school_zone_eye_level's Introduction

개발 의도

  • 아이들을 지키기 위한 '스쿨존'에서 사고가 제일 많이 발생하여, 스쿨존 교통사고에 인공지능을 도입하여 실시간으로 사고를 감지 및 예방하는 .

문제점 분석

  • 어린이안전교육이 부족하며, 현장에서 배우는 것이 아닌 이론으로 배우기 때문에 현장에서 사고가 많으며 돌발행동이 많음

개발

Editor

Pycharm, Unity

Language

Python, C#

learning method

Deep_learning, supervised learning, transfer learning

AI Technology

Object Detection, Find Pose

Optimizer

SGD, Loss, Box_loss, Label_loss, Nan방지
class

class.ymal

nc: 85:
  names: ['Kid', 'Adult', 'R_Signal', 'G_Signal', 'Cross' 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 
        'train', 'truck', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 
        'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 
        'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 
        'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple',
        'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'potted plant', 
        'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 
        'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush']  # class names 
파일구조
CCTV_Detecter
 |---- yolov5
 |    |---- Name_Models
 |    |    |---- Kid_Adult
 |    |    |    |---- Kid_Adult_best (1).pt  -> 어린이_어른 구별 모델
 |    |    |    |---- Kid_Adult_best.pt
 |    |    |    |---- Kid_Adult_last.pt
 |    |    |---- Object
 |    |    |    |---- Object.pt -> 자동차, 버스, 트럭, 사람 감지 모델
 |    |    |---- light
 |    |    |    |---- light_best.pt -> 도로, 빨간불, 파란불 감지 모델
 |    |    |    |---- light_last.pt
 |    |---- Name_Yaml
 |    |    |---- Kid_Adult
 |    |    |    |---- Kid_Adult_data.yaml -> class_name[어린이, 어른]
 |    |    |    |---- Kid_Adult_data2.yaml
 |    |    |---- Object
 |    |    |    |---- Object.yaml -> class_name[자동차, 버스, 트럭, 사람]
 |    |    |---- light
 |    |    |    |---- light_data.yaml -> class_name[도로, 빨간불, 파란불]
 |    |---- mp3file
 |    |    |    |---- bick.mp3--------|
 |    |    |    |---- fcar.mp3--------|________ 상황에 맞는 소리
 |    |    |    |---- kick-bick.mp3---|
 |    |    |    |---- kick.mp3--------|
 |    |---- CCTV_Detecter.py -----| 객체인식 코드
 |    |---- GUI.py ---------------| GUI 코드
 Pose Model
 |---- mp3-flie
 |    |    |    |---- blue.mp3------------|
 |    |    |    |---- hello_school.mp3----|________ 상황에 맞는 소리
 |    |    |    |---- left.mp3-------|
 |    |    |    |---- right.mp3------------|
 |---- Finall.py -----| 포즈 감지 코드

시뮬레이션

PPT URL

Pyhon 코드 파일

CCTV_Detecter.py 객체인식 + 포즈인식

추가 예정

계절 및 날씨에 따른 결과들을 분석으로 상황에 맞는 인공지능을 만들 계획 예) 비가오는 날이면, 우산을 인식함.

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