Wooks

sudo apt-get install php-mysql

/var/www/html   경로에 test.php 생성후 실행 

test.php

 <?php 
$mysql_hostname = '127.0.0.1';
$mysql_username = 'root';
$mysql_password = 'shinhan3262';
$mysql_database = 'iot_main';
$mysql_port = '3306';
$mysql_charset = 'UTF8';
    
$connect = new mysqli($mysql_hostname, $mysql_username, $mysql_password, $mysql_database, $mysql_port, $mysql_charset);
 
if($connect->connect_errno){
    echo '!연결실패'.$connect->connect_error.'';
}else{
    echo '연결성공!';
}
      
    
?>
 <?php echo 'End Hellow'; ?>

sudo apt-get install mysql-server

"Y" 누르면 설치가 진행된다.

외버 접속 허용 

sudo ufw allow mysql  

실행

sudo systemctl start mysql

자동실행등록 

 sudo systemctl enable mysql

접속

sudo mysql -u root

접속 방법 변경 

select user, plugin  from user;

update user set plugin='mysql_native_password' where user='root';

종료후 

sudo mysql -u root -p

PHP 설치

sudo apt-get install php

아파치 기본 폴더  /var/www/html

폴더 권한 부여 

sudo chmod 777 /var/www/html -R

폴더 권한이 부여되어 문서 생성이 됨

test.php 생성

파일 편집기로  test.php 파일 편집

<?php echo "Hello PHP" ?> 

.php  => 확장자 없이 사용 하는 법

/etc/apache2/apache2.conf 

권한부여

 sudo chmod 7777 /etc/apache2/apache.conf

파일열기

<Directory /var/www/>
Options FollowSymLinks MultiViews
AddType application/x-httpd-php .php .jsp
AllowOverride FileInfo
Require all granted
</Directory>

수정후 저장

아파치 재시작

sudo service apache2 stop

sudo service apache2 start 

터미널을 열고 

페키지 업데이트

 sudo apt update 

 sudo apt upgrade

아파치 설치 

sudo apt install apache2

아파치 서버 가동

sudo service apache2 start

브라우저를 열고  주소에 127.0.0.1   아파치 기본 페이지가 나오면 성공

import cv2
from ultralytics import YOLO

model = YOLO('yolov8x.pt')
webcam = cv2.VideoCapture(0)

blue_color = (255,0,0)

if not webcam.isOpened():
    print("Could not open webcam")
    exit()

while webcam.isOpened():
    status, frame = webcam.read()

    if status:
        results = model.predict(classes=0, device=0, conf=0.5, source=frame)

        for result in results:
            annotated_frame = result.plot(line_width=2, labels=False, boxes=False)
            boxes = result.boxes

            if boxes :
                for box in boxes :
                    x1 = int(box.xyxy[0,0])
                    y1 = int(box.xyxy[0,1])
                    x2 = int(box.xyxy[0,2])
                    y2 = int(box.xyxy[0,3])
                    cv2.rectangle(annotated_frame, (x1,y1), (x2,y2), blue_color, 3 )

                cv2.imshow("cam", annotated_frame)

    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

webcam.release()
cv2.destroyAllWindows()

     참조

      https://docs.ultralytics.com/modes/predict/#sources

        weights=ROOT / 'yolov5s.pt',  # model path or triton URL
        source=ROOT / 'data/images',  # file/dir/URL/glob/screen/0(webcam)
        data=ROOT / 'data/coco128.yaml',  # dataset.yaml path
        imgsz=(640, 640),  # inference size (height, width)
        conf_thres=0.25,  # confidence threshold
        iou_thres=0.45,  # NMS IOU threshold
        max_det=1000,  # maximum detections per image
        device='',  # cuda device, i.e. 0 or 0,1,2,3 or cpu
        view_img=False,  # show results
        save_txt=False,  # save results to *.txt
        save_conf=False,  # save confidences in --save-txt labels
        save_crop=False,  # save cropped prediction boxes
        nosave=False,  # do not save images/videos
        classes=None,  # filter by class: --class 0, or --class 0 2 3
        agnostic_nms=False,  # class-agnostic NMS
        augment=False,  # augmented inference
        visualize=False,  # visualize features
        update=False,  # update all models
        project=ROOT / 'runs/detect',  # save results to project/name
        name='exp',  # save results to project/name
        exist_ok=False,  # existing project/name ok, do not increment
        line_thickness=3,  # bounding box thickness (pixels)
        hide_labels=False,  # hide labels
        hide_conf=False,  # hide confidences
        half=False,  # use FP16 half-precision inference
        dnn=False,  # use OpenCV DNN for ONNX inference
        vid_stride=1,  # video frame-rate stride

1. Person
2. Bicycle
3. Car
4. Motorcycle
5. Airplane
6. Bus
7. Train
8. Truck
9. Boat
10. Traffic light
11. Fire hydrant
12. Stop sign
13. Parking meter
14. Bench
15. Bird
16. Cat
17. Dog
18. Horse
19. Sheep
20. Cow
21. Elephant
22. Bear
23. Zebra
24. Giraffe
25. Backpack
26. Umbrella
27. Handbag
28. Tie
29. Suitcase
30. Frisbee
31. Skis
32. Snowboard
33. Sports ball
34. Kite
35. Baseball bat
36. Baseball glove
37. Skateboard
38. Surfboard
39. Tennis racket
40. Bottle
41. Wine glass
42. Cup
43. Fork
44. Knife
45. Spoon
46. Bowl
47. Banana
48. Apple
49. Sandwich
50. Orange
51. Broccoli
52. Carrot
53. Hot dog
54. Pizza
55. Donut
56. Cake
57. Chair
58. Couch
59. Potted plant
60. Bed
61. Dining table
62. Toilet
63. TV
64. Laptop
65. Mouse
66. Remote
67. Keyboard
68. Cell phone
69. Microwave
70. Oven
71. Toaster
72. Sink
73. Refrigerator
74. Book
75. Clock
76. Vase
77. Scissors
78. Teddy bear
79. Hair drier
80. Toothbrush

classes=0  하면 사람만 감지한다. 

yolo 모델을 변경합니다. "yolov8s.pt