From 056e3a0b8cd2bfe5c1c7b48ef8da136734088673 Mon Sep 17 00:00:00 2001
From: yq183 <645046984@qq.com>
Date: Tue, 1 Oct 2024 21:09:03 +0800
Subject: [PATCH] =?UTF-8?q?=E5=86=85=E7=BD=91=E5=8F=91=E9=80=81?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
---
.idea/.gitignore | 3 +
.idea/algorithm.iml | 8 +
.../inspectionProfiles/profiles_settings.xml | 6 +
.idea/misc.xml | 7 +
.idea/modules.xml | 8 +
.idea/vcs.xml | 6 +
gengbao.py | 462 ++++++++++++++++++
internalNet/internalNet.py | 170 +++++++
pi.py | 16 +
9 files changed, 686 insertions(+)
create mode 100644 .idea/.gitignore
create mode 100644 .idea/algorithm.iml
create mode 100644 .idea/inspectionProfiles/profiles_settings.xml
create mode 100644 .idea/misc.xml
create mode 100644 .idea/modules.xml
create mode 100644 .idea/vcs.xml
create mode 100644 gengbao.py
create mode 100644 internalNet/internalNet.py
create mode 100644 pi.py
diff --git a/.idea/.gitignore b/.idea/.gitignore
new file mode 100644
index 0000000..26d3352
--- /dev/null
+++ b/.idea/.gitignore
@@ -0,0 +1,3 @@
+# Default ignored files
+/shelf/
+/workspace.xml
diff --git a/.idea/algorithm.iml b/.idea/algorithm.iml
new file mode 100644
index 0000000..5410dcd
--- /dev/null
+++ b/.idea/algorithm.iml
@@ -0,0 +1,8 @@
+
+
+
+
+
+
+
+
\ No newline at end of file
diff --git a/.idea/inspectionProfiles/profiles_settings.xml b/.idea/inspectionProfiles/profiles_settings.xml
new file mode 100644
index 0000000..105ce2d
--- /dev/null
+++ b/.idea/inspectionProfiles/profiles_settings.xml
@@ -0,0 +1,6 @@
+
+
+
+
+
+
\ No newline at end of file
diff --git a/.idea/misc.xml b/.idea/misc.xml
new file mode 100644
index 0000000..f0589af
--- /dev/null
+++ b/.idea/misc.xml
@@ -0,0 +1,7 @@
+
+
+
+
+
+
+
\ No newline at end of file
diff --git a/.idea/modules.xml b/.idea/modules.xml
new file mode 100644
index 0000000..2ba6d76
--- /dev/null
+++ b/.idea/modules.xml
@@ -0,0 +1,8 @@
+
+
+
+
+
+
+
+
\ No newline at end of file
diff --git a/.idea/vcs.xml b/.idea/vcs.xml
new file mode 100644
index 0000000..6c0b863
--- /dev/null
+++ b/.idea/vcs.xml
@@ -0,0 +1,6 @@
+
+
+
+
+
+
\ No newline at end of file
diff --git a/gengbao.py b/gengbao.py
new file mode 100644
index 0000000..87ed862
--- /dev/null
+++ b/gengbao.py
@@ -0,0 +1,462 @@
+import datetime
+import math
+import os
+import signal
+import sys
+import threading
+import re
+import uuid
+import tempfile
+import pyexiv2
+import numpy as np
+
+import requests
+from PIL import Image
+
+from numpy import arctan
+import cv2
+from math import tan, cos, sin
+import oss2
+import paho.mqtt.client as mqtt
+import concurrent.futures
+import json
+
+
+
+# 客户端id
+client_id='python_gengbao'
+# 订阅主题
+longandlat_mqtt ='task/image/gps/custon'
+# 订阅主题
+appTwo ='task/image/disobey/handle'
+# 订阅主题
+weijian ='task/image/pixel/custon'
+
+# 发布通知主题
+pushNoticeTopic ='task/image/disobey/confirm'
+
+
+access_key = "LTAI5tMDFvYZRvrJfK7HeuEm"
+secret_key = "kP7ueRlhLbM9mvkaLtHfcje3GxgawH"
+endpoint = "oss-cn-hangzhou.aliyuncs.com"
+bucket_name = "yq-dajiang"
+
+
+
+auths = oss2.Auth(access_key, secret_key)
+bucket = oss2.Bucket(auths, endpoint, bucket_name)
+# 根据像素坐标生成图片和经纬度，放入集合中，返回到前端
+
+
+client = mqtt.Client(client_id=client_id)
+#截图
+def crop_image(input_image,center_x,center_y):
+ print(center_x,center_y)
+ #固定截图尺寸 1000*1000
+ l_x = 0
+ l_y=0
+ r_x=1000
+ r_y=1000
+ if center_x>500:
+ l_x=center_x-500
+ r_x=center_x+500
+ if r_x>=4000:
+ r_x=4000
+ l_x=3000
+
+ if center_y>500:
+ l_y=center_y-500
+ r_y=center_y+500
+ if r_y>=3000:
+ r_y=3000
+ l_y=2000
+ print((l_x,l_y),(r_x,r_y))
+ # 截取指定区域图像
+ cropped_image = input_image[l_y:r_y, l_x:r_x]
+ return np.array(cropped_image)
+#计算两个经纬度之间的距离，用于计算长宽
+def dimension(jingduA, weiduA,jingduB, weiduB):
+ R = 6371.393
+ Pi = math.pi
+
+ a = (math.sin(math.radians(weiduA / 2 - weiduB / 2))) ** 2
+ b = math.cos(weiduA * Pi / 180) * math.cos(weiduB * Pi / 180) * (
+ math.sin((jingduA / 2 - jingduB / 2) * Pi / 180)) ** 2
+ dimension = 2 * R * math.asin((a + b) ** 0.5) * 1000
+ return dimension
+
+def sum(focalLength,x,altitude):
+ width=4000
+ #靶面宽
+ ba=6.2
+ #实际长度
+ wr=(x*altitude*ba)/(focalLength*width)
+ return wr
+
+def longandlat(pixel_x,pixel_y,imageMap):
+
+ # 焦距
+ focalLength =float(imageMap["focalLength"])
+ # 经纬度
+ longitude_str=imageMap["longitude"]
+ latitude_str = imageMap["latitude"]
+ # 使用正则表达式提取度、分和秒的数值
+ pattern = r"(\d+)° (\d+)' ([\d.]+)\""
+ longitude_match = re.match(pattern, longitude_str)
+ latitude_match = re.match(pattern, latitude_str)
+ print(longitude_match)
+ print(type(longitude_match))
+
+ # 度
+ lg_du =int(longitude_match.group(1))
+ # 分
+ lg_fen =int(longitude_match.group(2))
+ # 秒
+ lg_seconds = float(longitude_match.group(3))
+
+ # 度
+ la_du = int(latitude_match.group(1))
+ # 分
+ la_fen = int(latitude_match.group(2))
+ # 秒
+ la_seconds =float(latitude_match.group(3))
+
+
+ # 海拔
+ altitude = float(imageMap["altitude"])
+ # 图片宽高
+ width =float(imageMap["width"])
+ height =float(imageMap["height"])
+
+
+ # 中点坐标
+ x, y = width // 2, height // 2
+ # 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。
+
+ D = 2 * tan(arctan(9.826 / 2 / focalLength) / 2) * altitude
+
+ # 因此，每个像素所代表的实际距离为(米)：
+ # p =(9.826*altitude)/(width*focalLength)
+
+ p = D / width
+ # 经度每秒代表的距离 m
+ # 纬度每秒代表的距离 m
+ lat_p = 23.6
+ long_p = 30.9
+
+ pie=float(imageMap["xmpProperties"])
+
+ if pie < 0:
+ pie = -180 + abs(pie)
+ else:
+ pie = 180 - pie
+ # z转换已中心点为原点的坐标体系
+ px = (pixel_x - x)
+ py = (y - pixel_y)
+
+ a = math.radians(pie)
+
+ # 坐标体系旋转后所得到的坐标
+ c_a_x = cos(a) * px - sin(a) * py
+ c_a_y = sin(a) * px + cos(a) * py
+
+ ys = c_a_y * p / lat_p
+ xs = c_a_x * p / long_p
+
+ la_seconds += ys
+ lg_seconds += xs
+
+ longitude_x = lg_du + lg_fen / 60.0 + lg_seconds / 3600.0
+
+ latitude_y = la_du + la_fen / 60.0 + la_seconds / 3600.0
+ return longitude_x ,latitude_y,focalLength,altitude
+
+
+
+def upload_image_to_oss(imgeName,data):
+
+ # imgeName 文件名 列：python/img.jpg
+ bucket.put_object(imgeName, data)
+ # 将对象权限设置为公共读，以便通过URL访问上传的图像
+ bucket.put_object_acl(imgeName, oss2.OBJECT_ACL_PUBLIC_READ)
+ # 获取对象URL
+ url = bucket.sign_url("GET", imgeName,3600) # URL有效期为1小时
+ return url.split('?')[0]
+
+# 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 = [str(weijian), str(longandlat_mqtt), str(appTwo)]
+ # 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 compute(re):
+ if "sourceImgUrl" in re and "pixelCoordinate" in re:
+ sourceImgUrl = re["sourceImgUrl"]
+ mateSourceImgUrl = re["mateSourceImgUrl"]
+ pixelCoordinate = re["pixelCoordinate"]
+ imageMap = re["imageMap"]
+ maplist=[]
+ # 如果image1和image2都不为空，执行相关操作
+ # 指向算法比对，获取图片z
+ if pixelCoordinate:
+ coordinateList = json.loads(pixelCoordinate)
+ # 指向算法比对，获取图片
+ if len(coordinateList) != 0:
+ # 从URL加载图像
+ resp = requests.get(sourceImgUrl)
+ # 创建临时文件
+ # 创建临时文件
+ temp_file = tempfile.NamedTemporaryFile(delete=False)
+ temp_file.write(resp.content)
+ temp_file.close()
+
+
+ # 前端缩放了，比例是：scale=4
+ for item in coordinateList:
+ lef_x = item["lef_x"]
+ lef_y = item["lef_y"]
+ right_x = item["right_x"]
+ right_y = item["right_y"]
+ # 将比例还原
+ scale = 4
+ lef_x = int(lef_x * scale)
+ lef_y = int(lef_y * scale)
+ right_x = int(right_x * scale)
+ right_y = int(right_y * scale)
+ x=right_x-lef_x
+ y=right_y-lef_y
+ # 中心坐标
+ # 计算矩形框的中心点坐标
+ center_x = int((lef_x + right_x) / 2)
+ center_y = int((lef_y + right_y) / 2)
+ # 经纬度转换
+ long, lat ,focalLength,altitude= longandlat(center_x, center_y, imageMap)
+ img_array = np.frombuffer(resp.content, np.uint8)
+ # 将矩形框绘制到图片上
+ img_copy = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
+ # 在图像上绘制矩形框
+ cv2.rectangle(img_copy, (lef_x,lef_y), (right_x,right_y), (0, 255, 255), 10)
+ # OpenCV图像对象转换为字节流格式。
+ _, buffer = cv2.imencode('.jpg', img_copy)
+ img_bytes = buffer.tobytes()
+ # 文件名称
+ unique_id = str(uuid.uuid4())
+ imgName = 'python/' + unique_id + "违建图.jpg"
+ # 将图片上传到阿里云OSS
+ url = upload_image_to_oss(imgName, img_bytes)
+
+ # 获取长
+ w = sum(focalLength,x,altitude)
+ # 获取宽
+ h = sum(focalLength,y,altitude)
+ # 计算矩形面积并保留两位小数
+ area = round(w * h, 2)
+
+ #截图 对比图放大
+ cropped_image1=crop_image(img_copy, center_x,center_y)
+ # OpenCV图像对象转换为字节流格式。
+ _, buffer1 = cv2.imencode('.jpg',cropped_image1)
+ img_bytes1 = buffer1.tobytes()
+ # 文件名称
+ unique_id1 = str(uuid.uuid4())
+ imgNameOne = 'python/' + unique_id1 + "对比图违建放大图.jpg"
+ # 将图片上传到阿里云OSS
+ maxImages = upload_image_to_oss(imgNameOne, img_bytes1)
+ # 从URL加载图像
+ resp1 = requests.get(mateSourceImgUrl)
+ # 创建临时文件
+ temp_file1 = tempfile.NamedTemporaryFile(delete=False)
+ temp_file1.write(resp1.content)
+ temp_file1.close()
+ # 模板图画框
+ img_array2 = np.frombuffer(resp1.content, np.uint8)
+ # 将矩形框绘制到图片上
+ img_copy2 = cv2.imdecode(img_array2, cv2.IMREAD_COLOR)
+ # 在图像上绘制矩形框
+ cv2.rectangle(img_copy2, (lef_x, lef_y), (right_x, right_y), (255, 255, 0), 10)
+ # OpenCV图像对象转换为字节流格式。
+ _, buffer2 = cv2.imencode('.jpg', img_copy2)
+ img_bytes2 = buffer2.tobytes()
+ # 文件名称
+ unique_id3 = str(uuid.uuid4())
+ imgName3 = 'python/' + unique_id3 + "违建图.jpg"
+ # 将图片上传到阿里云OSS
+ url3 = upload_image_to_oss(imgName3, img_bytes2)
+ cropped_image2 = crop_image(img_copy2,center_x,center_y) # OpenCV图像对象转换为字节流格式。
+ _, buffer1 = cv2.imencode('.jpg',cropped_image2)
+ img_bytes2 = buffer1.tobytes()
+ # 文件名称
+ unique_id2 = str(uuid.uuid4())
+ imgNameTwo = 'python/' + unique_id2 + "放大模板图.jpg"
+ # 将图片上传到阿里云OSS
+ maxMateSourceImgUrl = upload_image_to_oss(imgNameTwo, img_bytes2)
+
+ id = re["id"]
+ taskId = re["taskId"]
+ map = {"lng": long, "lat": lat, "url": url, "taskImageId": id, "taskId": taskId, "images": url,
+ "handleType": 1,"areaL":w,"areaW":h,"area":area,"maxMateSourceImgUrl":maxMateSourceImgUrl,
+ "maxImages":maxImages,"mateSourceImgUrl":url3}
+ maplist.append(map)
+
+ return maplist
+# 根据像素坐标生成图片和经纬度，放入集合中，返回到前端
+def result(re,imgeurl,coordinateList):
+ if len(coordinateList)!=0:
+ print("读取")
+ # 从URL加载图像
+ imgeurl=str(imgeurl).replace("https", "http")
+ resp = requests.get(imgeurl,stream=True)
+ # 创建临时文件
+ with tempfile.NamedTemporaryFile(delete=False) as temp_file:
+ for chunk in resp.iter_content(chunk_size=1024):
+ temp_file.write(chunk)
+ print("创建")
+ # 创建pyexiv2.Image对象
+ # 从临时文件读取图像数据
+ image = cv2.imread(temp_file.name)
+ if image is not None:
+ # 文件名称
+ unique_id = str(uuid.uuid4())
+ print("生成")
+ #前端缩放了，比例是：scale=4
+ for item in coordinateList:
+ print(type(item))
+ lef_x=item["lef_x"]
+ lef_y=item["lef_y"]
+ right_x = item["right_x"]
+ right_y = item["right_y"]
+
+ #将比例还原
+ scale=4
+ lef_x=lef_x*scale
+ lef_y=lef_y*scale
+ right_x=right_x*scale
+ right_y=right_y*scale
+
+
+ # # 中心坐标
+ # # 计算矩形框的中心点坐标
+ # center_x = int(lef_x+right_x / 2)
+ # center_y = int(lef_y+right_y / 2)
+ # # # 经纬度转换
+ # # long,lat=longandlat(image,center_x,center_y)
+ # # 将矩形框绘制到图片上
+ # nparr = np.frombuffer(resp.content, np.uint8)
+ # img_copy = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
+ # 在图像上绘制矩形框
+ cv2.rectangle(image, (int(lef_x),int(lef_y)), (int(right_x),int(right_y)), (0,0,255), 10)
+ # OpenCV图像对象转换为字节流格式。
+ _, buffer = cv2.imencode('.jpg', image)
+ img_bytes = buffer.tobytes()
+ imgName = 'python/' + unique_id + "违建图.jpg"
+ print("上传")
+ # 将图片上传到阿里云OSS
+ url = upload_image_to_oss(imgName, img_bytes)
+ id = re["id"]
+ taskId = re["taskId"]
+ map = {"id": id, "taskId": taskId,"discernImgUrl": url}
+ os.remove(temp_file.name)
+ return map
+def messageData(msg):
+ topic = msg.topic
+ print("处理消息,时间：" + str(datetime.datetime.now()))
+ data = json.loads(msg.payload.decode())
+ # 获取图片路径、图片名称和MQTT消息的时间戳
+ if data:
+ if topic==appTwo:
+ print("通知")
+ if "id" in data:
+ print("数据情况",data)
+ id=data["id"]
+ notice = {"id":id }
+ on_publish(pushNoticeTopic, json.dumps(notice), 0)
+ if topic==weijian:
+ print("画违建矩形框")
+ if "sourceImgUrl" in data and "pixelCoordinate" in data:
+ image = data["sourceImgUrl"]
+ pixelCoordinate = data["pixelCoordinate"]
+ # 指向算法比对，获取图片
+ coordinateList = json.loads(pixelCoordinate)
+ print(type(coordinateList))
+ map = result(data, image, coordinateList)
+ if map is None:
+ print("生成图片出错，为null")
+ else:
+ url = "http://106.13.50.125:9006/ploughe-boot/wayline/waylineTaskImage/leakEdit"
+ # url = "http://192.168.1.20:9005/ploughe-boot/wayline/waylineTaskImage/leakEdit"
+ # 调取接口
+ response = requests.post(url, json=map)
+ message = response.text
+ print("接口返回值：", message)
+ print("结束时间:" + str(datetime.datetime.now()))
+ elif topic==longandlat_mqtt:
+ print("提交违建，生产预警")
+ # 创建线程池
+ with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor:
+ if data and "waylineTaskImages" in data:
+ waylineImgList = data["waylineTaskImages"]
+ # 提交任务给线程池
+ futurelist = [executor.submit(compute, re) for re in waylineImgList]
+ # 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()
+
diff --git a/internalNet/internalNet.py b/internalNet/internalNet.py
new file mode 100644
index 0000000..b77de70
--- /dev/null
+++ b/internalNet/internalNet.py
@@ -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()
+
+
+
+
+
+
diff --git a/pi.py b/pi.py
new file mode 100644
index 0000000..7be74b3
--- /dev/null
+++ b/pi.py
@@ -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!")