从服务器读取IP并将检测数据写入数据库
This commit is contained in:
124
core/all.py
124
core/all.py
@ -1,9 +1,18 @@
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import cv2
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import numpy as np
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from PIL.Image import Image
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from core.ocr import load_model as ocrLoadModel, detect as ocrDetect
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from core.face import load_model as faceLoadModel, detect as faceDetect
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from core.yolo import load_model as yoloLoadModel, detect as yoloDetect
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# 导入保存路径函数(根据实际文件位置调整导入路径)
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from core.establish import get_image_save_path
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import numpy as np
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import base64
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from io import BytesIO
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from PIL import Image
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from ds.db import db
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from mysql.connector import Error as MySQLError
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# 模型加载状态标记(避免重复加载)
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@ -26,7 +35,28 @@ def load_model():
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print("所有检测模型加载完成")
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def detect(frame):
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def save_db(model_type, client_ip, result):
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conn = None
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cursor = None
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try:
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# 连接数据库
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conn = db.get_connection()
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# 往表插入数据
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cursor = conn.cursor(dictionary=True) # 返回字典格式结果
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insert_query = """
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INSERT INTO device_danger (client_ip, type, result)
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VALUES (%s, %s, %s)
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"""
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cursor.execute(insert_query, (client_ip, model_type, result))
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conn.commit()
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except MySQLError as e:
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raise Exception(f"获取设备列表失败: {str(e)}") from e
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finally:
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db.close_connection(conn, cursor)
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def detect(client_ip, frame):
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"""
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执行模型检测,检测到违规时按指定格式保存图片
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参数:
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@ -38,23 +68,19 @@ def detect(frame):
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yolo_flag, yolo_result = yoloDetect(frame)
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print(f"YOLO检测结果:{yolo_result}")
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if yolo_flag:
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# 元组解构:获取「完整保存路径」和「显示用短路径」
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full_save_path, display_path = get_image_save_path(model_type="yolo")
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if full_save_path: # 只判断完整路径是否有效(用于保存)
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cv2.imwrite(full_save_path, frame)
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# 打印时使用「显示用短路径」,符合需求格式
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print(f"✅ YOLO违规图片已保存:{display_path}")
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save_db(model_type="yolo", client_ip=client_ip, result=numpy_array_to_base64(frame))
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# if full_save_path: # 只判断完整路径是否有效(用于保存)
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# cv2.imwrite(full_save_path, frame)
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# # 打印时使用「显示用短路径」,符合需求格式
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# print(f"✅ YOLO违规图片已保存:{display_path}")
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return (True, yolo_result, "yolo")
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# 2. 人脸检测(优先级2)
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#
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# # 2. 人脸检测(优先级2)
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face_flag, face_result = faceDetect(frame)
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print(f"人脸检测结果:{face_result}")
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if face_flag:
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# 同样解构元组,分离保存路径和显示路径
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full_save_path, display_path = get_image_save_path(model_type="face")
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if full_save_path:
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cv2.imwrite(full_save_path, frame)
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print(f"✅ 人脸违规图片已保存:{display_path}")
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# 将帧转化为 base64 字符串
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save_db(model_type="face", client_ip=client_ip, result=numpy_array_to_base64(frame))
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return (True, face_result, "face")
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# 3. OCR检测(优先级3)
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@ -62,12 +88,70 @@ def detect(frame):
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print(f"OCR检测结果:{ocr_result}")
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if ocr_flag:
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# 解构元组,保存用完整路径,打印用短路径
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full_save_path, display_path = get_image_save_path(model_type="ocr")
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if full_save_path:
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cv2.imwrite(full_save_path, frame)
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print(f"✅ OCR违规图片已保存:{display_path}")
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save_db(model_type="ocr", client_ip=client_ip, result=ocr_result)
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# if full_save_path:
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# cv2.imwrite(full_save_path, frame)
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# print(f"✅ OCR违规图片已保存:{display_path}")
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return (True, ocr_result, "ocr")
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# 4. 无违规内容(不保存图片)
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print(f"❌ 未检测到任何违规内容,不保存图片")
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return (False, "未检测到任何内容", "none")
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return (False, "未检测到任何内容", "none")
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def numpy_array_to_base64(arr, img_format='PNG'):
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"""
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将numpy数组转换为base64字符串
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参数:
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arr: numpy数组,通常是图像数据,形状为(height, width, channels)
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img_format: 图像格式,默认为'PNG',也可以是'JPEG'等PIL支持的格式
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返回:
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str: 转换后的base64字符串
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异常:
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ValueError: 当输入不是有效的numpy数组或不支持的形状时抛出
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Exception: 处理过程中出现的其他异常
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"""
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try:
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# 检查输入是否为numpy数组
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if not isinstance(arr, np.ndarray):
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raise ValueError("输入必须是numpy数组")
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# 处理单通道图像(灰度图)
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if len(arr.shape) == 2:
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arr = np.expand_dims(arr, axis=-1)
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# 检查数组形状是否有效
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if len(arr.shape) != 3 or arr.shape[2] not in [1, 3, 4]:
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raise ValueError("numpy数组必须是形状为(height, width, channels)的图像数据,通道数应为1、3或4")
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# 处理数据类型,确保是uint8类型
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if arr.dtype != np.uint8:
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# 归一化到0-255并转换为uint8
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arr = ((arr - arr.min()) / (arr.max() - arr.min() + 1e-8) * 255).astype(np.uint8)
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# 将单通道图像转换为PIL支持的模式
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if arr.shape[2] == 1:
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arr = arr.squeeze(axis=-1)
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image = Image.fromarray(arr, mode='L') # L模式表示灰度图
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elif arr.shape[2] == 3:
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image = Image.fromarray(arr, mode='RGB')
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else: # 4通道
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image = Image.fromarray(arr, mode='RGBA')
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# 将图像保存到内存缓冲区
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buffer = BytesIO()
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image.save(buffer, format=img_format)
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# 从缓冲区读取数据并编码为base64
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buffer.seek(0)
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base64_str = base64.b64encode(buffer.read()).decode('utf-8')
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return base64_str
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except ValueError as ve:
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raise ve
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except Exception as e:
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raise Exception(f"转换过程中发生错误: {str(e)}")
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@ -2,15 +2,11 @@ import os
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import datetime
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from pathlib import Path
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# 配置IP文件路径(统一使用绝对路径)
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IP_FILE_PATH = Path(r"D:\ccc\IP.txt")
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from service.device_service import get_unique_client_ips
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def create_directory_structure():
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"""创建项目所需的目录结构"""
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"""创建项目所需的目录结构,为所有客户端IP预创建基础目录"""
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try:
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# 1. 创建根目录下的resource文件夹
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# 1. 创建根目录下的resource文件夹(存在则跳过,不覆盖子内容)
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resource_dir = Path("resource")
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resource_dir.mkdir(exist_ok=True)
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print(f"确保resource目录存在: {resource_dir.absolute()}")
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@ -27,87 +23,95 @@ def create_directory_structure():
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model_dir.mkdir(exist_ok=True)
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print(f"确保{model}模型目录存在: {model_dir.absolute()}")
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# 4. 读取ip.txt文件获取IP地址
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# 4. 调用外部方法获取所有客户端IP地址
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try:
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with open(IP_FILE_PATH, "r") as f:
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ip_addresses = [line.strip() for line in f if line.strip()]
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# 调用外部ip_read()方法获取所有客户端IP地址列表
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all_ip_addresses = get_unique_client_ips()
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if not ip_addresses:
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print("警告: ip.txt文件中未找到有效的IP地址")
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# 确保返回的是列表类型
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if not isinstance(all_ip_addresses, list):
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all_ip_addresses = [all_ip_addresses]
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# 过滤有效IP(去除空字符串和空格)
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valid_ips = [ip.strip() for ip in all_ip_addresses if ip.strip()]
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if not valid_ips:
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print("警告: 未获取到有效的客户端IP地址")
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return
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print(f"从ip.txt中读取到的IP地址: {ip_addresses}")
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print(f"获取到的所有客户端IP地址: {valid_ips}")
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# 5. 获取当前日期
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# 5. 获取当前日期(年、月)
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now = datetime.datetime.now()
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current_year = str(now.year)
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current_month = str(now.month)
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# 6. 为每个IP在每个模型文件夹下创建年->月的目录结构
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for ip in ip_addresses:
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# 直接使用原始IP格式
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safe_ip = ip
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# 6. 为每个客户端IP在每个模型文件夹下创建年->月的基础目录结构
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for ip in valid_ips:
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# 处理IP地址中的特殊字符(将.替换为_,避免路径问题)
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safe_ip = ip.replace(".", "_")
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for model in model_dirs:
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# 构建路径: resource/dect/{model}/{ip}/{year}/{month}
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# 构建路径: resource/dect/{model}/{safe_ip}/{year}/{month}
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ip_dir = dect_dir / model / safe_ip
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year_dir = ip_dir / current_year
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month_dir = year_dir / current_month
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# 创建目录(如果不存在)
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# 递归创建目录(存在则跳过,不覆盖)
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month_dir.mkdir(parents=True, exist_ok=True)
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print(f"创建/确保目录存在: {month_dir.absolute()}")
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print(f"为客户端IP {ip} 创建/确保目录存在: {month_dir.absolute()}")
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except FileNotFoundError:
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print(f"错误: 未找到ip.txt文件,请确保该文件存在于 {IP_FILE_PATH}")
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except Exception as e:
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print(f"处理IP和日期目录时发生错误: {str(e)}")
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print(f"处理客户端IP和日期目录时发生错误: {str(e)}")
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except Exception as e:
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print(f"创建目录结构时发生错误: {str(e)}")
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print(f"创建基础目录结构时发生错误: {str(e)}")
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def get_image_save_path(model_type: str) -> tuple:
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def get_image_save_path(model_type: str, client_ip: str) -> tuple:
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"""
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获取图片保存的完整路径和显示用路径
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获取图片保存的「完整路径」和「显示用短路径」
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参数:
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model_type: 模型类型,应为"ocr"、"face"或"yolo"
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client_ip: 检测到违禁的客户端IP地址(原始格式,如192.168.1.101)
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返回:
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元组 (完整保存路径, 显示用路径)
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元组 (完整保存路径, 显示用短路径);若出错则返回 ("", "")
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"""
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try:
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# 读取IP地址(假设只有一个IP或使用第一个IP)
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with open(IP_FILE_PATH, "r") as f:
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ip_addresses = [line.strip() for line in f if line.strip()]
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# 1. 验证客户端IP有效性(检查是否在已知IP列表中)
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all_ip_addresses = get_unique_client_ips()
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if not isinstance(all_ip_addresses, list):
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all_ip_addresses = [all_ip_addresses]
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valid_ips = [ip.strip() for ip in all_ip_addresses if ip.strip()]
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if not ip_addresses:
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raise ValueError("ip.txt文件中未找到有效的IP地址")
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if client_ip.strip() not in valid_ips:
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raise ValueError(f"客户端IP {client_ip} 不在已知IP列表中,无法保存文件")
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ip = ip_addresses[0]
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safe_ip = ip # 直接使用原始IP格式
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# 2. 处理IP地址(与目录创建逻辑一致,将.替换为_)
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safe_ip = client_ip.strip().replace(".", "_")
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# 获取当前日期和时间(精确到毫秒,确保文件名唯一)
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# 3. 获取当前日期和毫秒级时间戳(确保文件名唯一)
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now = datetime.datetime.now()
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current_year = str(now.year)
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current_month = str(now.month)
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current_day = str(now.day)
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# 生成时间戳字符串(格式:年月日时分秒毫秒)
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timestamp = now.strftime("%Y%m%d%H%M%S%f")[:-3] # 去除最后三位,保留到毫秒
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# 时间戳格式:年月日时分秒毫秒(如20250910143050123)
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timestamp = now.strftime("%Y%m%d%H%M%S%f")[:-3]
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# 构建基础目录路径
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base_dir = Path("resource") / "dect"
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# 构建完整路径: resource/dect/{model}/{ip}/{year}/{month}/{day}
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# 4. 定义基础目录(用于生成相对路径)
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base_dir = Path("resource") / "dect" # 显示路径会去掉这个前缀
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# 构建日级目录(完整路径:resource/dect/{model}/{safe_ip}/{年}/{月}/{日})
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day_dir = base_dir / model_type / safe_ip / current_year / current_month / current_day
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day_dir.mkdir(parents=True, exist_ok=True)
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day_dir.mkdir(parents=True, exist_ok=True) # 确保日目录存在
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# 构建图片文件名(简化名称,去掉resource_dect_前缀)
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image_filename = f"{model_type}_{safe_ip}_{current_year}_{current_month}_{current_day}_{timestamp}.jpg"
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full_path = day_dir / image_filename
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# 5. 构建唯一文件名
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image_filename = f"dect_{model_type}_{safe_ip}_{current_year}{current_month}{current_day}_{timestamp}.jpg"
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# 计算显示用路径(相对于resource/dect的路径)
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display_path = full_path.relative_to(base_dir)
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# 6. 生成完整路径(用于实际保存图片)和显示路径(用于打印)
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full_path = day_dir / image_filename # 完整路径:resource/dect/.../xxx.jpg
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display_path = full_path.relative_to(base_dir) # 短路径:{model}/.../xxx.jpg(去掉resource/dect)
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return str(full_path), str(display_path)
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@ -236,3 +236,29 @@ async def get_device_list(
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raise Exception(f"获取设备列表失败: {str(e)}") from e
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finally:
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db.close_connection(conn, cursor)
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def get_unique_client_ips() -> list[str]:
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"""
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获取所有去重的客户端IP列表
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:return: 去重后的客户端IP字符串列表,如果没有数据则返回空列表
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"""
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conn = None
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cursor = None
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try:
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conn = db.get_connection()
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cursor = conn.cursor(dictionary=True)
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# 查询去重的客户端IP
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query = "SELECT DISTINCT client_ip FROM devices WHERE client_ip IS NOT NULL"
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cursor.execute(query)
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# 提取结果并转换为字符串列表
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results = cursor.fetchall()
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return [item['client_ip'] for item in results]
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except MySQLError as e:
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raise Exception(f"获取客户端IP列表失败: {str(e)}") from e
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finally:
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db.close_connection(conn, cursor)
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35
ws/ws.py
35
ws/ws.py
@ -33,7 +33,7 @@ def get_current_time_file_str() -> str:
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class ClientConnection:
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def __init__(self, websocket: WebSocket, client_ip: str):
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self.websocket = websocket
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self.client_ip = client_ip
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self.client_ip = client_ip # 已初始化客户端IP,用于传递给detect
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self.last_heartbeat = datetime.datetime.now()
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self.frame_queue = asyncio.Queue(maxsize=FRAME_QUEUE_SIZE)
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self.consumer_task: Optional[asyncio.Task] = None
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@ -84,7 +84,7 @@ class ClientConnection:
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print(f"[{get_current_time_str()}] 客户端{self.client_ip}: 帧消费逻辑错误 - {str(e)}")
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async def process_frame(self, frame_data: bytes) -> None:
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"""处理单帧图像数据(核心修复:按3个返回值解包)"""
|
||||
"""处理单帧图像数据(核心修改:detect函数传入 client_ip + img 双参数)"""
|
||||
# 二进制转OpenCV图像
|
||||
nparr = np.frombuffer(frame_data, np.uint8)
|
||||
img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
|
||||
@ -93,19 +93,21 @@ class ClientConnection:
|
||||
return
|
||||
|
||||
try:
|
||||
# -------------------------- 修复核心:匹配detect返回的3个值 --------------------------
|
||||
# 假设detect返回 (是否违规, 结果数据, 检测器类型)
|
||||
# -------------------------- 核心修改:按要求传入参数(1.client_ip 2.img) --------------------------
|
||||
# detect函数参数顺序:第一个为client_ip,第二个为图像数据img
|
||||
# 保持返回值解包(是否违规, 结果数据, 检测器类型)不变
|
||||
has_violation, data, detector_type = await asyncio.to_thread(
|
||||
detect, # 调用检测函数
|
||||
img # 传入图像参数
|
||||
detect, # 调用检测函数
|
||||
self.client_ip, # 第一个参数:客户端IP(新增,按需求顺序)
|
||||
img # 第二个参数:图像数据(原参数,调整顺序)
|
||||
)
|
||||
# -------------------------------------------------------------------------------------
|
||||
|
||||
# 打印检测结果(移除task_id相关内容)
|
||||
# 打印检测结果(包含客户端IP,与传入参数对应)
|
||||
print(f"[{get_current_time_str()}] 客户端{self.client_ip}: 检测结果 - "
|
||||
f"违规: {has_violation}, 类型: {detector_type}, 数据: {data}")
|
||||
|
||||
# 处理违规逻辑
|
||||
# 处理违规逻辑(逻辑不变,基于detect返回结果执行)
|
||||
if has_violation:
|
||||
print(f"[{get_current_time_str()}] 客户端{self.client_ip}: 检测到违规 - "
|
||||
f"类型: {detector_type}, 详情: {data}")
|
||||
@ -227,7 +229,7 @@ ws_router = APIRouter()
|
||||
|
||||
@ws_router.websocket(WS_ENDPOINT)
|
||||
async def websocket_endpoint(websocket: WebSocket):
|
||||
load_model()
|
||||
load_model() # 加载检测模型(仅在连接建立时加载一次,避免重复加载)
|
||||
await websocket.accept()
|
||||
client_ip = websocket.client.host if websocket.client else "unknown_ip"
|
||||
current_time = get_current_time_str()
|
||||
@ -236,7 +238,7 @@ async def websocket_endpoint(websocket: WebSocket):
|
||||
is_online_updated = False
|
||||
|
||||
try:
|
||||
# 处理重复连接
|
||||
# 处理重复连接(同一IP断开旧连接)
|
||||
if client_ip in connected_clients:
|
||||
old_conn = connected_clients[client_ip]
|
||||
if old_conn.consumer_task and not old_conn.consumer_task.done():
|
||||
@ -245,13 +247,13 @@ async def websocket_endpoint(websocket: WebSocket):
|
||||
connected_clients.pop(client_ip)
|
||||
print(f"[{current_time}] 客户端{client_ip}: 已关闭旧连接")
|
||||
|
||||
# 注册新连接
|
||||
# 注册新连接(绑定client_ip和WebSocket)
|
||||
new_conn = ClientConnection(websocket, client_ip)
|
||||
connected_clients[client_ip] = new_conn
|
||||
new_conn.start_consumer()
|
||||
await new_conn.send_frame_permit()
|
||||
new_conn.start_consumer() # 启动帧消费任务
|
||||
await new_conn.send_frame_permit() # 发送首次帧许可
|
||||
|
||||
# 标记上线
|
||||
# 标记客户端上线
|
||||
try:
|
||||
await asyncio.to_thread(update_online_status_by_ip, client_ip, 1)
|
||||
action_data = DeviceActionCreate(client_ip=client_ip, action=1)
|
||||
@ -263,7 +265,7 @@ async def websocket_endpoint(websocket: WebSocket):
|
||||
|
||||
print(f"[{current_time}] 客户端{client_ip}: 新连接注册成功、在线数: {len(connected_clients)}")
|
||||
|
||||
# 消息循环
|
||||
# 消息循环(持续接收客户端消息)
|
||||
while True:
|
||||
data = await websocket.receive()
|
||||
if "text" in data:
|
||||
@ -276,12 +278,13 @@ async def websocket_endpoint(websocket: WebSocket):
|
||||
except Exception as e:
|
||||
print(f"[{get_current_time_str()}] 客户端{client_ip}: 连接异常 - {str(e)[:50]}")
|
||||
finally:
|
||||
# 清理资源
|
||||
# 清理资源(断开后标记离线+删除连接)
|
||||
if client_ip in connected_clients:
|
||||
conn = connected_clients[client_ip]
|
||||
if conn.consumer_task and not conn.consumer_task.done():
|
||||
conn.consumer_task.cancel()
|
||||
|
||||
# 仅当上线状态更新成功时,才执行离线更新
|
||||
if is_online_updated:
|
||||
try:
|
||||
await asyncio.to_thread(update_online_status_by_ip, client_ip, 0)
|
||||
|
Reference in New Issue
Block a user