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# Default ignored files |
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/shelf/ |
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/workspace.xml |
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<?xml version="1.0" encoding="UTF-8"?> |
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<module type="PYTHON_MODULE" version="4"> |
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<component name="NewModuleRootManager"> |
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<content url="file://$MODULE_DIR$" /> |
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<orderEntry type="jdk" jdkName="Python 3.10 (algorithm) (3)" jdkType="Python SDK" /> |
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<orderEntry type="sourceFolder" forTests="false" /> |
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</component> |
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</module> |
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<component name="InspectionProjectProfileManager"> |
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<settings> |
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<option name="USE_PROJECT_PROFILE" value="false" /> |
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<version value="1.0" /> |
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</settings> |
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</component> |
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<?xml version="1.0" encoding="UTF-8"?> |
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<project version="4"> |
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<component name="ProjectRootManager" version="2" project-jdk-name="Python 3.10 (algorithm) (3)" project-jdk-type="Python SDK" /> |
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<component name="PyCharmProfessionalAdvertiser"> |
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<option name="shown" value="true" /> |
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</component> |
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</project> |
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<?xml version="1.0" encoding="UTF-8"?> |
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<project version="4"> |
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<component name="ProjectModuleManager"> |
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<modules> |
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<module fileurl="file://$PROJECT_DIR$/.idea/algorithm.iml" filepath="$PROJECT_DIR$/.idea/algorithm.iml" /> |
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</modules> |
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</component> |
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</project> |
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<?xml version="1.0" encoding="UTF-8"?> |
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<project version="4"> |
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<component name="VcsDirectoryMappings"> |
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<mapping directory="$PROJECT_DIR$/.." vcs="Git" /> |
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</component> |
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</project> |
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import datetime |
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import math |
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import os |
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import signal |
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import sys |
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import threading |
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import re |
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import uuid |
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import tempfile |
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import pyexiv2 |
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import numpy as np |
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import requests |
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from PIL import Image |
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from numpy import arctan |
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import cv2 |
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from math import tan, cos, sin |
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import oss2 |
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import paho.mqtt.client as mqtt |
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import concurrent.futures |
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import json |
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|
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# 客户端id |
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client_id='python_gengbao' |
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# 订阅主题 |
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longandlat_mqtt ='task/image/gps/custon' |
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# 订阅主题 |
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appTwo ='task/image/disobey/handle' |
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# 订阅主题 |
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weijian ='task/image/pixel/custon' |
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|
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# 发布通知主题 |
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pushNoticeTopic ='task/image/disobey/confirm' |
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access_key = "LTAI5tMDFvYZRvrJfK7HeuEm" |
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secret_key = "kP7ueRlhLbM9mvkaLtHfcje3GxgawH" |
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endpoint = "oss-cn-hangzhou.aliyuncs.com" |
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bucket_name = "yq-dajiang" |
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auths = oss2.Auth(access_key, secret_key) |
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bucket = oss2.Bucket(auths, endpoint, bucket_name) |
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# 根据像素坐标生成图片和经纬度，放入集合中，返回到前端 |
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client = mqtt.Client(client_id=client_id) |
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#截图 |
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def crop_image(input_image,center_x,center_y): |
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print(center_x,center_y) |
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#固定截图尺寸 1000*1000 |
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l_x = 0 |
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l_y=0 |
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r_x=1000 |
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r_y=1000 |
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if center_x>500: |
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l_x=center_x-500 |
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r_x=center_x+500 |
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if r_x>=4000: |
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r_x=4000 |
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l_x=3000 |
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if center_y>500: |
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l_y=center_y-500 |
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r_y=center_y+500 |
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if r_y>=3000: |
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r_y=3000 |
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l_y=2000 |
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print((l_x,l_y),(r_x,r_y)) |
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# 截取指定区域图像 |
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cropped_image = input_image[l_y:r_y, l_x:r_x] |
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return np.array(cropped_image) |
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#计算两个经纬度之间的距离，用于计算长宽 |
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def dimension(jingduA, weiduA,jingduB, weiduB): |
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R = 6371.393 |
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Pi = math.pi |
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a = (math.sin(math.radians(weiduA / 2 - weiduB / 2))) ** 2 |
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b = math.cos(weiduA * Pi / 180) * math.cos(weiduB * Pi / 180) * ( |
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math.sin((jingduA / 2 - jingduB / 2) * Pi / 180)) ** 2 |
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dimension = 2 * R * math.asin((a + b) ** 0.5) * 1000 |
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return dimension |
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def sum(focalLength,x,altitude): |
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width=4000 |
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#靶面宽 |
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ba=6.2 |
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#实际长度 |
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wr=(x*altitude*ba)/(focalLength*width) |
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return wr |
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def longandlat(pixel_x,pixel_y,imageMap): |
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# 焦距 |
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focalLength =float(imageMap["focalLength"]) |
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# 经纬度 |
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longitude_str=imageMap["longitude"] |
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latitude_str = imageMap["latitude"] |
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# 使用正则表达式提取度、分和秒的数值 |
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pattern = r"(\d+)° (\d+)' ([\d.]+)\"" |
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longitude_match = re.match(pattern, longitude_str) |
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latitude_match = re.match(pattern, latitude_str) |
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print(longitude_match) |
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print(type(longitude_match)) |
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# 度 |
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lg_du =int(longitude_match.group(1)) |
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# 分 |
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lg_fen =int(longitude_match.group(2)) |
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# 秒 |
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lg_seconds = float(longitude_match.group(3)) |
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# 度 |
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la_du = int(latitude_match.group(1)) |
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# 分 |
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la_fen = int(latitude_match.group(2)) |
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# 秒 |
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la_seconds =float(latitude_match.group(3)) |
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# 海拔 |
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altitude = float(imageMap["altitude"]) |
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# 图片宽高 |
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width =float(imageMap["width"]) |
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height =float(imageMap["height"]) |
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# 中点坐标 |
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x, y = width // 2, height // 2 |
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# 通过勾股定理可以计算出 1/2.3 英寸对角线的长度大约为 4.54 毫米。 |
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D = 2 * tan(arctan(9.826 / 2 / focalLength) / 2) * altitude |
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# 因此，每个像素所代表的实际距离为(米)： |
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# p =(9.826*altitude)/(width*focalLength) |
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p = D / width |
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# 经度每秒代表的距离 m |
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# 纬度每秒代表的距离 m |
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lat_p = 23.6 |
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long_p = 30.9 |
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pie=float(imageMap["xmpProperties"]) |
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if pie < 0: |
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pie = -180 + abs(pie) |
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else: |
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pie = 180 - pie |
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# z转换已中心点为原点的坐标体系 |
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px = (pixel_x - x) |
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py = (y - pixel_y) |
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a = math.radians(pie) |
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# 坐标体系旋转后所得到的坐标 |
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c_a_x = cos(a) * px - sin(a) * py |
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c_a_y = sin(a) * px + cos(a) * py |
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ys = c_a_y * p / lat_p |
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xs = c_a_x * p / long_p |
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la_seconds += ys |
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lg_seconds += xs |
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longitude_x = lg_du + lg_fen / 60.0 + lg_seconds / 3600.0 |
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latitude_y = la_du + la_fen / 60.0 + la_seconds / 3600.0 |
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return longitude_x ,latitude_y,focalLength,altitude |
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def upload_image_to_oss(imgeName,data): |
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# imgeName 文件名 列：python/img.jpg |
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bucket.put_object(imgeName, data) |
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# 将对象权限设置为公共读，以便通过URL访问上传的图像 |
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bucket.put_object_acl(imgeName, oss2.OBJECT_ACL_PUBLIC_READ) |
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# 获取对象URL |
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url = bucket.sign_url("GET", imgeName,3600) # URL有效期为1小时 |
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return url.split('?')[0] |
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|
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# 连接回调函数 |
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def on_connect(client, userdata, flags, rc): |
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"""一旦连接成功, 回调此方法""" |
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rc_status = ["连接成功", "协议版本错误", "无效的客户端标识", "服务器无法使用", "用户名或密码错误", "无授权"] |
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print("connect：", rc_status[rc]) |
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topics = [str(weijian), str(longandlat_mqtt), str(appTwo)] |
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# 要订阅的主题列表 |
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for topic in topics: |
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# 订阅主题 |
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print("订阅主题：", topic) |
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client.subscribe(topic) |
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def compute(re): |
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if "sourceImgUrl" in re and "pixelCoordinate" in re: |
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sourceImgUrl = re["sourceImgUrl"] |
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mateSourceImgUrl = re["mateSourceImgUrl"] |
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pixelCoordinate = re["pixelCoordinate"] |
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imageMap = re["imageMap"] |
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maplist=[] |
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# 如果image1和image2都不为空，执行相关操作 |
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# 指向算法比对，获取图片z |
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if pixelCoordinate: |
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coordinateList = json.loads(pixelCoordinate) |
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# 指向算法比对，获取图片 |
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if len(coordinateList) != 0: |
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# 从URL加载图像 |
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resp = requests.get(sourceImgUrl) |
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# 创建临时文件 |
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# 创建临时文件 |
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temp_file = tempfile.NamedTemporaryFile(delete=False) |
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temp_file.write(resp.content) |
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temp_file.close() |
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# 前端缩放了，比例是：scale=4 |
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for item in coordinateList: |
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lef_x = item["lef_x"] |
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lef_y = item["lef_y"] |
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right_x = item["right_x"] |
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right_y = item["right_y"] |
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# 将比例还原 |
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scale = 4 |
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lef_x = int(lef_x * scale) |
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lef_y = int(lef_y * scale) |
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right_x = int(right_x * scale) |
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right_y = int(right_y * scale) |
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x=right_x-lef_x |
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y=right_y-lef_y |
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# 中心坐标 |
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# 计算矩形框的中心点坐标 |
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center_x = int((lef_x + right_x) / 2) |
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center_y = int((lef_y + right_y) / 2) |
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# 经纬度转换 |
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long, lat ,focalLength,altitude= longandlat(center_x, center_y, imageMap) |
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img_array = np.frombuffer(resp.content, np.uint8) |
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# 将矩形框绘制到图片上 |
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img_copy = cv2.imdecode(img_array, cv2.IMREAD_COLOR) |
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# 在图像上绘制矩形框 |
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cv2.rectangle(img_copy, (lef_x,lef_y), (right_x,right_y), (0, 255, 255), 10) |
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# OpenCV图像对象转换为字节流格式。 |
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_, buffer = cv2.imencode('.jpg', img_copy) |
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img_bytes = buffer.tobytes() |
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# 文件名称 |
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unique_id = str(uuid.uuid4()) |
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imgName = 'python/' + unique_id + "违建图.jpg" |
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# 将图片上传到阿里云OSS |
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url = upload_image_to_oss(imgName, img_bytes) |
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# 获取长 |
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w = sum(focalLength,x,altitude) |
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# 获取宽 |
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h = sum(focalLength,y,altitude) |
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# 计算矩形面积并保留两位小数 |
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area = round(w * h, 2) |
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#截图 对比图放大 |
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cropped_image1=crop_image(img_copy, center_x,center_y) |
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# OpenCV图像对象转换为字节流格式。 |
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_, buffer1 = cv2.imencode('.jpg',cropped_image1) |
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img_bytes1 = buffer1.tobytes() |
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# 文件名称 |
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unique_id1 = str(uuid.uuid4()) |
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imgNameOne = 'python/' + unique_id1 + "对比图违建放大图.jpg" |
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# 将图片上传到阿里云OSS |
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maxImages = upload_image_to_oss(imgNameOne, img_bytes1) |
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# 从URL加载图像 |
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resp1 = requests.get(mateSourceImgUrl) |
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# 创建临时文件 |
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temp_file1 = tempfile.NamedTemporaryFile(delete=False) |
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temp_file1.write(resp1.content) |
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temp_file1.close() |
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# 模板图画框 |
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img_array2 = np.frombuffer(resp1.content, np.uint8) |
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# 将矩形框绘制到图片上 |
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img_copy2 = cv2.imdecode(img_array2, cv2.IMREAD_COLOR) |
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# 在图像上绘制矩形框 |
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cv2.rectangle(img_copy2, (lef_x, lef_y), (right_x, right_y), (255, 255, 0), 10) |
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# OpenCV图像对象转换为字节流格式。 |
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_, buffer2 = cv2.imencode('.jpg', img_copy2) |
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img_bytes2 = buffer2.tobytes() |
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# 文件名称 |
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unique_id3 = str(uuid.uuid4()) |
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imgName3 = 'python/' + unique_id3 + "违建图.jpg" |
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# 将图片上传到阿里云OSS |
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url3 = upload_image_to_oss(imgName3, img_bytes2) |
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cropped_image2 = crop_image(img_copy2,center_x,center_y) # OpenCV图像对象转换为字节流格式。 |
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_, buffer1 = cv2.imencode('.jpg',cropped_image2) |
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img_bytes2 = buffer1.tobytes() |
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# 文件名称 |
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unique_id2 = str(uuid.uuid4()) |
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imgNameTwo = 'python/' + unique_id2 + "放大模板图.jpg" |
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# 将图片上传到阿里云OSS |
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maxMateSourceImgUrl = upload_image_to_oss(imgNameTwo, img_bytes2) |
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id = re["id"] |
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taskId = re["taskId"] |
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map = {"lng": long, "lat": lat, "url": url, "taskImageId": id, "taskId": taskId, "images": url, |
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"handleType": 1,"areaL":w,"areaW":h,"area":area,"maxMateSourceImgUrl":maxMateSourceImgUrl, |
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"maxImages":maxImages,"mateSourceImgUrl":url3} |
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maplist.append(map) |
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return maplist |
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# 根据像素坐标生成图片和经纬度，放入集合中，返回到前端 |
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def result(re,imgeurl,coordinateList): |
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if len(coordinateList)!=0: |
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print("读取") |
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# 从URL加载图像 |
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imgeurl=str(imgeurl).replace("https", "http") |
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resp = requests.get(imgeurl,stream=True) |
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# 创建临时文件 |
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with tempfile.NamedTemporaryFile(delete=False) as temp_file: |
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for chunk in resp.iter_content(chunk_size=1024): |
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temp_file.write(chunk) |
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print("创建") |
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# 创建pyexiv2.Image对象 |
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# 从临时文件读取图像数据 |
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image = cv2.imread(temp_file.name) |
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if image is not None: |
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# 文件名称 |
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unique_id = str(uuid.uuid4()) |
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print("生成") |
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#前端缩放了，比例是：scale=4 |
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for item in coordinateList: |
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print(type(item)) |
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lef_x=item["lef_x"] |
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lef_y=item["lef_y"] |
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right_x = item["right_x"] |
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right_y = item["right_y"] |
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|
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#将比例还原 |
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scale=4 |
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lef_x=lef_x*scale |
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lef_y=lef_y*scale |
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right_x=right_x*scale |
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right_y=right_y*scale |
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# # 中心坐标 |
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# # 计算矩形框的中心点坐标 |
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# center_x = int(lef_x+right_x / 2) |
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# center_y = int(lef_y+right_y / 2) |
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# # # 经纬度转换 |
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# # long,lat=longandlat(image,center_x,center_y) |
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# # 将矩形框绘制到图片上 |
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# nparr = np.frombuffer(resp.content, np.uint8) |
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# img_copy = cv2.imdecode(nparr, cv2.IMREAD_COLOR) |
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# 在图像上绘制矩形框 |
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cv2.rectangle(image, (int(lef_x),int(lef_y)), (int(right_x),int(right_y)), (0,0,255), 10) |
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# OpenCV图像对象转换为字节流格式。 |
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_, buffer = cv2.imencode('.jpg', image) |
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img_bytes = buffer.tobytes() |
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imgName = 'python/' + unique_id + "违建图.jpg" |
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print("上传") |
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# 将图片上传到阿里云OSS |
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url = upload_image_to_oss(imgName, img_bytes) |
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id = re["id"] |
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taskId = re["taskId"] |
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map = {"id": id, "taskId": taskId,"discernImgUrl": url} |
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os.remove(temp_file.name) |
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return map |
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def messageData(msg): |
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topic = msg.topic |
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print("处理消息,时间：" + str(datetime.datetime.now())) |
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data = json.loads(msg.payload.decode()) |
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# 获取图片路径、图片名称和MQTT消息的时间戳 |
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if data: |
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if topic==appTwo: |
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print("通知") |
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if "id" in data: |
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print("数据情况",data) |
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id=data["id"] |
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notice = {"id":id } |
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on_publish(pushNoticeTopic, json.dumps(notice), 0) |
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if topic==weijian: |
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print("画违建矩形框") |
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if "sourceImgUrl" in data and "pixelCoordinate" in data: |
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image = data["sourceImgUrl"] |
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pixelCoordinate = data["pixelCoordinate"] |
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# 指向算法比对，获取图片 |
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coordinateList = json.loads(pixelCoordinate) |
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print(type(coordinateList)) |
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map = result(data, image, coordinateList) |
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if map is None: |
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print("生成图片出错，为null") |
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else: |
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url = "http://106.13.50.125:9006/ploughe-boot/wayline/waylineTaskImage/leakEdit" |
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# url = "http://192.168.1.20:9005/ploughe-boot/wayline/waylineTaskImage/leakEdit" |
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# 调取接口 |
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response = requests.post(url, json=map) |
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message = response.text |
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print("接口返回值：", message) |
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print("结束时间:" + str(datetime.datetime.now())) |
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elif topic==longandlat_mqtt: |
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print("提交违建，生产预警") |
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# 创建线程池 |
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with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor: |
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if data and "waylineTaskImages" in data: |
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waylineImgList = data["waylineTaskImages"] |
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# 提交任务给线程池 |
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futurelist = [executor.submit(compute, re) for re in waylineImgList] |
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# 等待所有任务完成 |
|||
concurrent.futures.wait(futurelist) |
|||
# 获取每个任务的处理结果 |
|||
final_results = [item for sublist in |
|||
[future.result() for future in futurelist if future.result() is not None] for item |
|||
in |
|||
sublist] |
|||
print("返回的结果", final_results) |
|||
print("返回的结果数量", len(final_results)) |
|||
if len(final_results) != 0: |
|||
data['waylineTaskHandles'] = final_results |
|||
print("提交数据：", data) |
|||
url = "http://106.13.50.125:9006/ploughe-boot/wayline/waylineTaskWhee/leakEdit" |
|||
# url = "http://192.168.1.20:9005/ploughe-boot/wayline/waylineTaskWhee/leakEdit" |
|||
# 调取接口 |
|||
# 将list作为JSON数据 |
|||
# 发送POST请求，并将data作为请求体 |
|||
response = requests.post(url, json=data, headers={'Content-Type': 'application/json'}) |
|||
# 获取响应结果 |
|||
body = response.json() |
|||
print("接口返回值：", body) |
|||
print("结束时间:" + str(datetime.datetime.now())) |
|||
# 关闭线程池 |
|||
executor.shutdown() |
|||
|
|||
|
|||
def on_message(client, userdata, msg): |
|||
# """一旦订阅到消息, 回调此方法""" |
|||
print("主题:" + msg.topic + " 消息:" + msg.payload.decode('utf-8')) # 客户端返回的消息,使用gb2312编码中文不会报错 |
|||
# 多线程执行 |
|||
threading.Thread(target=messageData, args=((msg,))).start() |
|||
|
|||
|
|||
def signal_handler(signal, frame): |
|||
print('接收到键盘中断信号，程序将退出') |
|||
sys.exit(0) |
|||
def on_publish(topic, payload, qos): |
|||
re=client.publish(topic, payload, qos) |
|||
print("结果："+str(re)+"时间："+str(datetime.datetime.now())) |
|||
|
|||
def run(): |
|||
# 创建客户端对象 |
|||
|
|||
client.username_pw_set("adminRQ", "yongqiang666") |
|||
# 设置连接回调函数 |
|||
client.on_connect = on_connect |
|||
# 设置接收消息回调函数 |
|||
client.on_message = on_message |
|||
# 连接到MQTT代理 |
|||
client.connect("106.13.50.125", 1883, 60) |
|||
# 注册信号处理程序 |
|||
signal.signal(signal.SIGINT, signal_handler) |
|||
# 保持连接并接收消息 |
|||
client.loop_forever() |
|||
|
|||
if __name__ == '__main__': |
|||
run() |
|||
|
|||
@ -0,0 +1,170 @@ |
|||
import datetime |
|||
|
|||
import threading |
|||
|
|||
|
|||
import paho.mqtt.client as mqtt |
|||
|
|||
from requests_toolbelt.adapters.source import SourceAddressAdapter |
|||
import json |
|||
|
|||
import requests |
|||
import io |
|||
# 客户端id |
|||
client_id='python_mqqt_syncdevice111' |
|||
|
|||
|
|||
|
|||
|
|||
|
|||
# 连接回调函数 |
|||
def on_connect(client, userdata, flags, rc): |
|||
"""一旦连接成功, 回调此方法""" |
|||
rc_status = ["连接成功", "协议版本错误", "无效的客户端标识", "服务器无法使用", "用户名或密码错误", "无授权"] |
|||
print("connect：", rc_status[rc]) |
|||
topics = ["syncdevice", "syncvirtualdevice", "device"] |
|||
# 要订阅的主题列表 |
|||
for topic in topics: |
|||
# 订阅主题 |
|||
print("订阅主题：",topic) |
|||
client.subscribe(topic) |
|||
|
|||
|
|||
def messageData(msg): |
|||
topic=msg.topic |
|||
print("处理消息,时间：" + str(datetime.datetime.now())) |
|||
data = json.loads(msg.payload.decode()) |
|||
print("数据",data) |
|||
try: |
|||
if data: |
|||
s = requests.Session() |
|||
# 指定特定网卡的IP地址'192.168.121.1'，使用该网卡发送POST请求 |
|||
s.mount('http://', SourceAddressAdapter('192.168.8.143')) |
|||
map = { "tenantId": 81} |
|||
|
|||
if topic=="syncdevice": |
|||
deviceLogList=data["deviceLogList"] |
|||
print("数据对象==",deviceLogList) |
|||
for device in deviceLogList: |
|||
filePath=device["filePath"] |
|||
filePath = filePath.replace("\\", "/") |
|||
url="http://192.168.101.11:9000/detect/api/data/upload/remote" |
|||
fileUrl='http://106.13.50.125:9999/detect' + filePath |
|||
#本地测试ip |
|||
#res = requests.get('http://192.168.1.51:9099/detect' + filePath) |
|||
#file = io.BytesIO(res.content) |
|||
res = requests.get(fileUrl) |
|||
file = io.BytesIO(res.content) |
|||
files = {"file": file} |
|||
mapPath={"path":filePath} |
|||
response=s.post(url=url, data=mapPath,files=files) |
|||
message = response.text |
|||
|
|||
print("音频接口返回值：", message) |
|||
print("音频结束时间:" + str(datetime.datetime.now())) |
|||
if "userPhoto" in data: |
|||
userPhoto= data["userPhoto"] |
|||
if userPhoto: |
|||
for user in userPhoto: |
|||
filePath = user["url"] |
|||
filePath = filePath.replace("\\", "/") |
|||
url = "http://192.168.101.11:9000/detect/api/data/upload/remote" |
|||
res1 = requests.get('http://106.13.50.125:9999/detect' + filePath) |
|||
# 本地测试ip |
|||
#res = requests.get('http://192.168.1.51:9099/detect' + filePath) |
|||
file1 = io.BytesIO(res1.content) |
|||
files1={"file":file1} |
|||
mapPath = {"path": filePath} |
|||
response = s.post(url=url, data=mapPath, files=files1) |
|||
message = response.text |
|||
print("图片接口返回值：", message) |
|||
print("图片结束时间:" + str(datetime.datetime.now())) |
|||
#将数据上传到内网 |
|||
url = "http://192.168.101.11:9000/detect/admin/inspect/task_user/synchrodata" |
|||
response = s.post(url=url, json=data,headers={'Content-Type':'application/json'}) |
|||
message = response.text |
|||
print("同步数据接口返回值：", message) |
|||
print("同步数据结束时间:" + str(datetime.datetime.now())) |
|||
map["type"] = 2 |
|||
map["annotation"] = message |
|||
elif topic=="syncvirtualdevice": |
|||
# 将数据上传到内网 |
|||
url = "http://192.168.101.11:9000/detect/admin/iot/device/snycdevice/receive" |
|||
response = s.post(url=url, json=data, headers={'Content-Type': 'application/json'}) |
|||
message = response.text |
|||
print("同步设备数据接口返回值：", message) |
|||
map["type"] = 3 |
|||
map["annotation"] = message |
|||
elif topic=="device": |
|||
deviceLogDTOS = data["deviceLogDTOS"] |
|||
print("数据对象==", deviceLogDTOS) |
|||
for device in deviceLogDTOS: |
|||
filePath = device["filePath"] |
|||
filePath = filePath.replace("\\", "/") |
|||
url = "http://192.168.101.11:9000/detect/api/data/upload/remote" |
|||
fileUrl = 'http://106.13.50.125:9999/detect' + filePath |
|||
# res = requests.get('http://106.13.50.125:9999/detect' + filePath) |
|||
# 本地测试ip |
|||
# fileUrl='http://192.168.1.10:9099/detect' + filePath |
|||
print("地址路径" + fileUrl) |
|||
res = requests.get(fileUrl) |
|||
file = io.BytesIO(res.content) |
|||
mapPath = {"path": filePath} |
|||
files = {"file": file} |
|||
response = s.post(url=url, data=mapPath, files=files) |
|||
message = response.text |
|||
print("音频接口返回值：", message) |
|||
print("音频结束时间:" + str(datetime.datetime.now())) |
|||
# 将数据上传到内网 |
|||
url = "http://192.168.101.11:9000/detect/admin/iot/device_log/send/warningTwo" |
|||
response = s.post(url=url, json=data, headers={'Content-Type': 'application/json'}) |
|||
message = response.text |
|||
print("数据接口返回值：", message) |
|||
print("数据结束时间:" + str(datetime.datetime.now())) |
|||
map["type"] = 1 |
|||
map["annotation"] = message |
|||
waiurl = "http://106.13.50.125:9099/detect/admin/iot/internalLog/save" |
|||
print("日志数据",map) |
|||
result = requests.post(waiurl, json=map, headers={'Content-Type': 'application/json'}) |
|||
print("日志接口返回值：", result.text) |
|||
|
|||
except requests.exceptions.ConnectTimeout as e: |
|||
# 处理连接超时异常 |
|||
print("连接超时：", e) |
|||
run() |
|||
|
|||
except Exception as e: |
|||
# 处理其他异常 |
|||
print("发生异常：", e) |
|||
run() |
|||
def on_message(client, userdata, msg): |
|||
"""一旦订阅到消息, 回调此方法""" |
|||
print("主题:" + msg.topic + " 消息:" + str(msg.payload.decode('utf-8'))) # 客户端返回的消息,使用gb2312编码中文不会报错 |
|||
# 将收到的消息转换为JSON格式 |
|||
threading.Thread(target=messageData, args=((msg,))).start() |
|||
|
|||
|
|||
|
|||
|
|||
|
|||
def run(): |
|||
# 创建客户端对象 |
|||
client = mqtt.Client(client_id=client_id) |
|||
client.username_pw_set("adminRQ", "yongqiang666") |
|||
# 设置连接回调函数 |
|||
client.on_connect = on_connect |
|||
# 设置接收消息回调函数 |
|||
client.on_message = on_message |
|||
# 连接到MQTT代理 |
|||
client.connect("106.13.50.125", 1883, 60) |
|||
# 保持连接并接收消息 |
|||
client.loop_forever() |
|||
|
|||
if __name__ == '__main__': |
|||
run() |
|||
|
|||
|
|||
|
|||
|
|||
|
|||
|
|||
@ -0,0 +1,16 @@ |
|||
import os |
|||
|
|||
folder_path = "C:/Users/yq183/Desktop/img" # 文件夹路径 |
|||
new_name_prefix = "img_" # 新名称前缀 |
|||
|
|||
# 获取文件夹下所有图片文件名 |
|||
image_files = [f for f in os.listdir(folder_path) if f.endswith(".jpg") or f.endswith(".png")or f.endswith(".jpeg")] |
|||
|
|||
# 遍历所有图片文件，进行重命名 |
|||
for i, image_file in enumerate(image_files): |
|||
old_path = os.path.join(folder_path, image_file) |
|||
new_name = f"{new_name_prefix}{i+1}.jpg" # 新名称格式 |
|||
new_path = os.path.join(folder_path, new_name) |
|||
os.rename(old_path, new_path) |
|||
|
|||
print("All images have been renamed successfully!") |
|||
Loading…
Reference in new issue