修复4号命令不能重复执行的bug

hi3861软件
2025-10-19 18:07:06 +08:00 · 2025-10-18 16:05:39 +08:00 · 2025-10-18 16:01:35 +08:00 · 2025-09-04 00:07:52 +08:00 · 2025-09-02 11:40:41 +08:00 · 2025-09-01 15:42:42 +08:00
50 changed files with 1904 additions and 1868 deletions
--- a/.idea/.gitignore
+++ b/.idea/.gitignore
@@ -1,8 +0,0 @@
-# 默认忽略的文件
-/shelf/
-/workspace.xml
-# 基于编辑器的 HTTP 客户端请求
-/httpRequests/
-# Datasource local storage ignored files
-/dataSources/
-/dataSources.local.xml
--- a/.idea/License_plate_recognition.iml
+++ b/.idea/License_plate_recognition.iml
@@ -1,12 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<module type="PYTHON_MODULE" version="4">
-  <component name="NewModuleRootManager">
-    <content url="file://$MODULE_DIR$" />
-    <orderEntry type="jdk" jdkName="Python 3.12" jdkType="Python SDK" />
-    <orderEntry type="sourceFolder" forTests="false" />
-  </component>
-  <component name="PyDocumentationSettings">
-    <option name="format" value="PLAIN" />
-    <option name="myDocStringFormat" value="Plain" />
-  </component>
-</module>
--- a/.idea/inspectionProfiles/profiles_settings.xml
+++ b/.idea/inspectionProfiles/profiles_settings.xml
@@ -1,6 +0,0 @@
-<component name="InspectionProjectProfileManager">
-  <settings>
-    <option name="USE_PROJECT_PROFILE" value="false" />
-    <version value="1.0" />
-  </settings>
-</component>
--- a/.idea/misc.xml
+++ b/.idea/misc.xml
@@ -1,4 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.12" project-jdk-type="Python SDK" />
-</project>
--- a/.idea/modules.xml
+++ b/.idea/modules.xml
@@ -1,8 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="ProjectModuleManager">
-    <modules>
-      <module fileurl="file://$PROJECT_DIR$/.idea/License_plate_recognition.iml" filepath="$PROJECT_DIR$/.idea/License_plate_recognition.iml" />
-    </modules>
-  </component>
-</project>
--- a/.idea/vcs.xml
+++ b/.idea/vcs.xml
@@ -1,7 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="VcsDirectoryMappings">
-    <mapping directory="" vcs="Git" />
-    <mapping directory="$PROJECT_DIR$" vcs="Git" />
-  </component>
-</project>
--- a/BUILD.gn
+++ b/BUILD.gn
@@ -0,0 +1,20 @@
+static_library("barrier_gate_client") {  
+  sources = [
+    # 根据功能划分文件
+    "demo_entry_cmsis.c",     # 入口和主线程 源文件
+    "udp_client_test.c",      # UDP客户端测试 源文件
+    "oled_ssd1306.c",         # oled 显示屏驱动文件
+    "wifi_connecter.c",       # wifi
+    "robot_sg90.c",           # sg90 舵机
+    "json_parser.c",          # JSON解析器
+    "display_helper.c"        # 显示辅助文件
+
+  ]
+
+  include_dirs = [
+    "//utils/native/lite/include",
+    "//kernel/liteos_m/kal/cmsis",
+    "//base/iot_hardware/peripheral/interfaces/kits",
+    "//foundation/communication/wifi_lite/interfaces/wifiservice",    # HAL接口中的WiFi接口
+  ]
+}
--- a/chinese_char_map.h
+++ b/chinese_char_map.h
@@ -0,0 +1,56 @@
+#ifndef CHINESE_CHAR_MAP_H
+#define CHINESE_CHAR_MAP_H
+
+#include <stdint.h>
+
+// 中文字符映射结构体
+typedef struct {
+    const char* utf8_char;  // UTF-8编码的中文字符
+    uint8_t font_index;     // 在fonts3数组中的索引
+} ChineseCharMap;
+
+// 中文字符映射表 - 根据fonts3数组中的字符顺序
+static const ChineseCharMap chinese_char_map[] = {
+    {"京", 0},   // ID:0 - 北京
+    {"沪", 1},   // ID:1 - 上海
+    {"津", 2},   // ID:2 - 天津
+    {"渝", 3},   // ID:3 - 重庆
+    {"冀", 4},   // ID:4 - 河北
+    {"晋", 5},   // ID:5 - 山西
+    {"蒙", 6},   // ID:6 - 内蒙古
+    {"辽", 7},   // ID:7 - 辽宁
+    {"吉", 8},   // ID:8 - 吉林
+    {"黑", 9},   // ID:9 - 黑龙江
+    {"苏", 10},  // ID:10 - 江苏
+    {"浙", 11},  // ID:11 - 浙江
+    {"皖", 12},  // ID:12 - 安徽
+    {"闽", 13},  // ID:13 - 福建
+    {"赣", 14},  // ID:14 - 江西
+    {"鲁", 15},  // ID:15 - 山东
+    {"豫", 16},  // ID:16 - 河南
+    {"鄂", 17},  // ID:17 - 湖北
+    {"湘", 18},  // ID:18 - 湖南
+    {"粤", 19},  // ID:19 - 广东
+    {"桂", 20},  // ID:20 - 广西
+    {"琼", 21},  // ID:21 - 海南
+    {"川", 22},  // ID:22 - 四川
+    {"贵", 23},  // ID:23 - 贵州
+    {"云", 24},  // ID:24 - 云南
+    {"藏", 25},  // ID:25 - 西藏
+    {"陕", 26},  // ID:26 - 陕西
+    {"甘", 27},  // ID:27 - 甘肃
+    {"青", 28},  // ID:28 - 青海
+    {"宁", 29},  // ID:29 - 宁夏
+    {"新", 30},  // ID:30 - 新疆
+    {"禁", 31},  // ID:31 - 禁止
+    {"通", 32},  // ID:32 - 通行
+    {"行", 33}   // ID:33 - 行驶
+};
+
+// 映射表大小
+#define CHINESE_CHAR_MAP_SIZE (sizeof(chinese_char_map) / sizeof(ChineseCharMap))
+
+// 函数声明
+int FindChineseCharIndex(const char* utf8_char);
+
+#endif // CHINESE_CHAR_MAP_H
--- a/demo_entry_cmsis.c
+++ b/demo_entry_cmsis.c
@@ -0,0 +1,525 @@
+#include <stdio.h>          // 标准输入输出
+#include <unistd.h>         // POSIX标准接口
+#include <string.h>         // 字符串处理(操作字符数组)
+
+#include "ohos_init.h"      // 用于初始化服务(services)和功能(features)
+#include "cmsis_os2.h"      // CMSIS-RTOS API V2
+
+#include "wifi_connecter.h" // easy wifi (station模式)
+#include "oled_ssd1306.h"        // OLED驱动接口
+#include "json_parser.h"
+#include "display_helper.h"      // 显示辅助函数
+#include "robot_sg90.h"    // 舵机控制接口
+#include "iot_gpio.h"
+#include "hi_io.h"
+#include "hi_time.h"
+#include "iot_gpio.h"
+#include "hi_adc.h"
+#include "iot_errno.h"
+#if 1
+// 定义一个宏，用于标识SSID。请根据实际情况修改
+#define PARAM_HOTSPOT_SSID "tarikPura"
+
+// 定义一个宏，用于标识密码。请根据实际情况修改
+#define PARAM_HOTSPOT_PSK "66668888"
+#elif
+#define PARAM_HOTSPOT_SSID "DYJY"
+
+// 定义一个宏，用于标识密码。请根据实际情况修改
+#define PARAM_HOTSPOT_PSK "12345678"
+#endif
+// 定义一个宏，用于标识加密方式
+#define PARAM_HOTSPOT_TYPE WIFI_SEC_TYPE_PSK
+
+// 定义一个宏，用于标识UDP服务器IP地址。请根据实际情况修改
+#define PARAM_SERVER_ADDR "192.168.43.137"
+
+#define GPIO5 5
+#define     ADC_TEST_LENGTH             (20)
+#define     VLT_MIN                     (100)
+#define     KEY_INTERRUPT_PROTECT_TIME        (30)
+
+unsigned short  g_adc_buf[ADC_TEST_LENGTH] = { 0 };
+unsigned short  g_gpio5_adc_buf[ADC_TEST_LENGTH] = { 0 };
+unsigned int  g_gpio5_tick = 0;
+
+int control_flag = 0;
+extern char response[128];
+extern JsonCommand g_current_command;  // 外部声明JSON命令变量
+
+// 舵机控制函数声明
+extern void servo_rotate_clockwise_90(void);
+extern void servo_rotate_counter_clockwise_90(void);
+extern void regress_middle(void);
+
+uint8_t fonts3[] = {
+
+    /*-- ID:0,字符:"京",ASCII编码:BEA9,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x08,0x08,0x08,0xe8,0x28,0x28,0x29,0x2e,0x28,0x28,0x28,0xf8,0x28,0x0c,0x08,0x00,
+    0x00,0x00,0x40,0x23,0x1a,0x42,0x82,0x7e,0x02,0x0a,0x12,0x33,0x60,0x00,0x00,0x00,
+
+    /*-- ID:1,字符:"沪",ASCII编码:BBA6,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x10,0x22,0x64,0x0c,0x80,0x00,0xf8,0x88,0x89,0x8a,0x8e,0x88,0x88,0xfc,0x08,0x00,
+    0x04,0x04,0xfc,0x03,0x80,0x60,0x1f,0x00,0x00,0x00,0x00,0x00,0x00,0x01,0x00,0x00,
+
+    /*-- ID:2,字符:"津",ASCII编码:BDF2,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x20,0x42,0xc4,0x0c,0x10,0x54,0x54,0x54,0xff,0x54,0x54,0x54,0x7e,0x14,0x10,0x00,
+    0x04,0x04,0xfc,0x02,0x11,0x12,0x12,0x12,0xff,0x12,0x12,0x13,0x1a,0x10,0x00,0x00,
+
+    /*-- ID:3,字符:"渝",ASCII编码:D3E5,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x10,0x22,0x64,0x0c,0xa0,0xd0,0x48,0x54,0xd2,0x13,0x94,0x08,0xd0,0x30,0x10,0x00,
+    0x04,0x04,0xfe,0x01,0x00,0xff,0x12,0x92,0xff,0x00,0x5f,0x80,0x7f,0x00,0x00,0x00,
+
+    /*-- ID:4,字符:"冀",ASCII编码:BCBD,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x08,0x0a,0xea,0xaa,0xaa,0xaa,0xaf,0xe0,0xaf,0xaa,0xaa,0xaa,0xfa,0x28,0x0c,0x00,
+    0x20,0xa0,0xab,0x6a,0x2a,0x3e,0x2a,0x2b,0x2a,0x3e,0x2a,0x6a,0xab,0xa0,0x20,0x00,
+
+    /*-- ID:5,字符:"晋",ASCII编码:BDFA,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x40,0x42,0x4a,0x52,0x42,0x7e,0x42,0x42,0x42,0x7e,0x42,0xd2,0x4b,0x62,0x40,0x00,
+    0x00,0x00,0x00,0xff,0x49,0x49,0x49,0x49,0x49,0x49,0x49,0xff,0x01,0x00,0x00,0x00,
+
+    /*-- ID:6,字符:"蒙",ASCII编码:C3C9,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x20,0x9a,0x8a,0x8a,0xaa,0xaf,0xaa,0xaa,0xaa,0xaf,0xaa,0x8a,0x8b,0xaa,0x18,0x00,
+    0x00,0x50,0x52,0x2a,0x2a,0x15,0x4b,0x86,0x7c,0x04,0x0a,0x13,0x20,0x60,0x20,0x00,
+
+    /*-- ID:7,字符:"辽",ASCII编码:C1C9,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x00,0x21,0x22,0xe6,0x00,0x02,0x02,0x02,0x02,0xf2,0x12,0x0a,0x06,0x02,0x00,0x00,
+    0x00,0x40,0x20,0x1f,0x20,0x40,0x40,0x48,0x50,0x4f,0x40,0x40,0x40,0x60,0x20,0x00,
+
+    /*-- ID:8,字符:"吉",ASCII编码:BCAA,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x08,0x08,0x88,0x88,0x88,0x88,0x88,0xff,0x88,0x88,0x88,0xc8,0x88,0x0c,0x08,0x00,
+    0x00,0x00,0x00,0xfc,0x44,0x44,0x44,0x44,0x44,0x44,0x44,0xfe,0x04,0x00,0x00,0x00,
+
+    /*-- ID:9,字符:"黑",ASCII编码:BADA,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x00,0x00,0xfe,0x8a,0x92,0xb2,0x82,0xfe,0x82,0xa2,0x9a,0x92,0xff,0x02,0x00,0x00,
+    0x08,0x8a,0x6a,0x0a,0x2a,0xca,0x0a,0x0f,0x2a,0xca,0x0a,0x2a,0x4a,0xca,0x08,0x00,
+
+    /*-- ID:10,字符:"苏",ASCII编码:CBD5,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x04,0x04,0x44,0x44,0x5f,0x44,0xf4,0x44,0x44,0x44,0x5f,0xe4,0x44,0x06,0x04,0x00,
+    0x00,0x88,0x46,0x20,0x10,0x0c,0x03,0x00,0x00,0x40,0x80,0x7f,0x02,0x04,0x0c,0x00,
+
+    /*-- ID:11,字符:"浙",ASCII编码:D5E3,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x10,0x22,0x64,0x0c,0x90,0x10,0xff,0x10,0x90,0xfc,0x44,0x44,0xc2,0x62,0x40,0x00,
+    0x04,0x04,0xfe,0x01,0x42,0x82,0x7f,0x41,0x20,0x1f,0x00,0x00,0xff,0x00,0x00,0x00,
+
+    /*-- ID:12,字符:"皖",ASCII编码:CDEE,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x00,0xf8,0x8c,0x8b,0x88,0xf8,0x10,0x0c,0x24,0x25,0x26,0x34,0x24,0x94,0x0c,0x00,
+    0x00,0x3f,0x10,0x10,0x10,0xbf,0x41,0x31,0x0f,0x01,0x01,0x3f,0x41,0x41,0x71,0x00,
+
+    /*-- ID:13,字符:"闽",ASCII编码:C3F6,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x00,0xfc,0x01,0x02,0xe6,0x20,0x22,0xfa,0x22,0x22,0xf2,0x22,0x02,0xff,0x02,0x00,
+    0x00,0xff,0x00,0x20,0x27,0x22,0x22,0x3f,0x12,0x12,0x1b,0x70,0x80,0x7f,0x00,0x00,
+
+    /*-- ID:14,字符:"赣",ASCII编码:B8D3,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x12,0xd6,0x5a,0x53,0x5a,0xd6,0x12,0x28,0x64,0x57,0xca,0x56,0x52,0x20,0x20,0x00,
+    0x10,0x17,0x15,0xfd,0x15,0x17,0x10,0x81,0xbd,0x45,0x35,0x45,0x7d,0x81,0x00,0x00,
+
+    /*-- ID:15,字符:"鲁",ASCII编码:C2B3,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x10,0x10,0xf8,0xac,0xaa,0xab,0xaa,0xfa,0xae,0xaa,0xaa,0xa8,0xfc,0x08,0x00,0x00,
+    0x02,0x02,0x02,0xfa,0xaa,0xaa,0xaa,0xaa,0xaa,0xaa,0xaa,0xfe,0x0a,0x02,0x02,0x00,
+
+    /*-- ID:16,字符:"豫",ASCII编码:D4A5,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x40,0x42,0x52,0xe2,0x5a,0xc6,0x50,0xf8,0x94,0xd3,0xba,0x96,0x92,0xf8,0x10,0x00,
+    0x00,0x40,0x80,0x7f,0x00,0x10,0x54,0x4a,0x25,0x92,0xfc,0x0c,0x12,0x61,0x20,0x00,
+
+    /*-- ID:17,字符:"鄂",ASCII编码:B6F5,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x00,0x5e,0x52,0x5e,0x40,0x5e,0x52,0x5e,0x00,0xfe,0x02,0x42,0xb2,0x0e,0x00,0x00,
+    0x01,0x01,0x0d,0x4b,0x89,0x89,0x7d,0x09,0x01,0xff,0x08,0x10,0x20,0x11,0x0e,0x00,
+
+    /*-- ID:18,字符:"湘",ASCII编码:CFE6,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x10,0x22,0x64,0x0c,0x10,0xd0,0xff,0x90,0x10,0xfc,0x44,0x44,0x44,0xfe,0x04,0x00,
+    0x04,0x04,0xfe,0x05,0x03,0x00,0xff,0x00,0x01,0xff,0x44,0x44,0x44,0xff,0x00,0x00,
+
+    /*-- ID:19,字符:"粤",ASCII编码:D4C1,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x00,0x00,0x00,0xfe,0x92,0xd6,0x93,0xfe,0x92,0xd6,0x92,0xff,0x02,0x00,0x00,0x00,
+    0x02,0x02,0x02,0x02,0x0a,0x0e,0x0a,0x0a,0x4a,0x8a,0x4a,0x3a,0x02,0x03,0x02,0x00,
+
+    /*-- ID:20,字符:"桂",ASCII编码:B9F0,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x10,0x10,0xd0,0xff,0x90,0x50,0x48,0x48,0x48,0xff,0x48,0x48,0x4c,0x68,0x40,0x00,
+    0x04,0x03,0x00,0xff,0x40,0x41,0x44,0x44,0x44,0x7f,0x44,0x44,0x46,0x64,0x40,0x00,
+
+    /*-- ID:21,字符:"琼",ASCII编码:C7ED,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x44,0x44,0xfc,0x46,0x44,0x08,0xe8,0x28,0x29,0x2a,0x28,0x28,0xf8,0x2c,0x08,0x00,
+    0x10,0x30,0x1f,0x08,0x08,0x20,0x13,0x5a,0x82,0x7e,0x02,0x0a,0x13,0x30,0x00,0x00,
+
+    /*-- ID:22,字符:"川",ASCII编码:B4A8,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x00,0x00,0x00,0xfe,0x00,0x00,0x00,0x00,0xfc,0x00,0x00,0x00,0x00,0xff,0x00,0x00,
+    0x00,0x40,0x20,0x1f,0x00,0x00,0x00,0x00,0x1f,0x00,0x00,0x00,0x00,0xff,0x00,0x00,
+
+    /*-- ID:23,字符:"贵",ASCII编码:B9F3,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x40,0x40,0x5c,0x54,0x54,0x54,0x54,0x7f,0x54,0x54,0x54,0xd4,0x5e,0x44,0x40,0x00,
+    0x00,0x00,0x80,0x9f,0x41,0x41,0x21,0x1d,0x21,0x21,0x41,0x5f,0x81,0x00,0x00,0x00,
+
+    /*-- ID:24,字符:"云",ASCII编码:D4C6,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x40,0x40,0x40,0x44,0x44,0x44,0xc4,0x44,0x44,0x44,0x46,0x44,0x40,0x60,0x40,0x00,
+    0x00,0x00,0x40,0x60,0x58,0x46,0x41,0x40,0x40,0x40,0x50,0x60,0xc0,0x00,0x00,0x00,
+
+    /*-- ID:25,字符:"藏",ASCII编码:B2D8,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x02,0xf2,0x82,0xf2,0x12,0xdf,0x52,0xd2,0x5f,0x12,0xfe,0x12,0x16,0x9b,0x12,0x00,
+    0x90,0x4e,0x22,0x1f,0x00,0x7f,0x25,0x3d,0xa7,0x40,0x2f,0x30,0x4c,0x83,0xe0,0x00,
+
+    /*-- ID:26,字符:"陕",ASCII编码:C9C2,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x00,0xfe,0x22,0x5a,0x86,0x08,0x28,0x48,0x08,0xff,0x08,0x48,0x2c,0x88,0x00,0x00,
+    0x00,0xff,0x04,0x08,0x87,0x41,0x21,0x11,0x0d,0x03,0x0d,0x11,0x61,0xc1,0x41,0x00,
+
+    /*-- ID:27,字符:"甘",ASCII编码:B8CA,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x10,0x10,0x10,0x10,0xff,0x10,0x10,0x10,0x10,0x10,0xff,0x10,0x10,0x18,0x10,0x00,
+    0x00,0x00,0x00,0x00,0xff,0x42,0x42,0x42,0x42,0x42,0xff,0x00,0x00,0x00,0x00,0x00,
+
+    /*-- ID:28,字符:"青",ASCII编码:C7E0,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x40,0x44,0x54,0x54,0x54,0x54,0x54,0x7f,0x54,0x54,0x54,0xd4,0x56,0x44,0x40,0x00,
+    0x00,0x00,0x00,0xff,0x15,0x15,0x15,0x15,0x15,0x55,0x95,0x7f,0x01,0x00,0x00,0x00,
+
+    /*-- ID:29,字符:"宁",ASCII编码:C4FE,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x50,0x4c,0x44,0x44,0x44,0x44,0x45,0xc6,0x44,0x44,0x44,0x44,0x44,0x54,0x4c,0x00,
+    0x00,0x00,0x00,0x00,0x00,0x40,0x80,0x7f,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,
+
+    /*-- ID:30,字符:"新",ASCII编码:D0C2,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x40,0x44,0x54,0x65,0xc6,0x64,0xd6,0x44,0x40,0xfc,0x44,0x42,0xc3,0x62,0x40,0x00,
+    0x20,0x11,0x49,0x81,0x7f,0x01,0x05,0x29,0x18,0x07,0x00,0x00,0xff,0x00,0x00,0x00,
+
+    /*-- ID:31,字符:"禁",ASCII编码:BDFB,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x40,0x24,0x14,0x0c,0x7f,0x14,0x24,0x20,0x14,0x0c,0x7f,0x0c,0x16,0x24,0x40,0x00,
+    0x04,0x04,0x45,0x25,0x15,0x45,0x85,0x7d,0x05,0x05,0x15,0x25,0x65,0x04,0x04,0x00,
+
+    /*-- ID:32,字符:"通",ASCII编码:CDA8,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x40,0x42,0x44,0xcc,0x00,0x00,0xf1,0x91,0x95,0xf9,0x95,0x93,0xf9,0x10,0x00,0x00,
+    0x00,0x40,0x20,0x1f,0x20,0x40,0xbf,0x84,0x84,0xbf,0x94,0xa4,0x9f,0xc0,0x40,0x00,
+
+    /*-- ID:33,字符:"行",ASCII编码:D0D0,对应字:宽x高=16x16,画布:宽W=16 高H=16,共32字节*/
+    0x00,0x10,0x88,0xc4,0x23,0x40,0x42,0x42,0x42,0x42,0x42,0xc2,0x43,0x62,0x40,0x00,
+    0x02,0x01,0x00,0xff,0x00,0x00,0x00,0x00,0x00,0x40,0x80,0x7f,0x00,0x00,0x00,0x00};
+
+// 定义一个宏，用于标识UDP服务器端口
+#define PARAM_SERVER_PORT 8081
+
+void switch_init(void)
+{
+    IoTGpioInit(5);
+    hi_io_set_func(5, 0);
+    IoTGpioSetDir(5, IOT_GPIO_DIR_IN);
+    hi_io_set_pull(5, 1);
+}
+
+//按键中断响应函数
+void gpio5_isr_func_mode(void)
+{
+    printf("gpio5_isr_func_mode start\n");
+    unsigned int tick_interval = 0;
+    unsigned int current_gpio5_tick = 0; 
+
+    current_gpio5_tick = hi_get_tick();
+    tick_interval = current_gpio5_tick - g_gpio5_tick;
+    
+    if (tick_interval < KEY_INTERRUPT_PROTECT_TIME) {  
+        return NULL;
+    }
+    g_gpio5_tick = current_gpio5_tick;
+    control_flag = !control_flag;
+    
+}
+
+unsigned char get_gpio5_voltage(void *param)
+{
+    int i;
+    unsigned short data;
+    unsigned int ret;
+    unsigned short vlt;
+    float voltage;
+    float vlt_max = 0;
+    float vlt_min = VLT_MIN;
+
+    hi_unref_param(param);
+    memset_s(g_gpio5_adc_buf, sizeof(g_gpio5_adc_buf), 0x0, sizeof(g_gpio5_adc_buf));
+    for (i = 0; i < ADC_TEST_LENGTH; i++) {
+        ret = hi_adc_read(HI_ADC_CHANNEL_2, &data, HI_ADC_EQU_MODEL_4, HI_ADC_CUR_BAIS_DEFAULT, 0xF0); 
+		//ADC_Channal_2  自动识别模式  CNcomment:4次平均算法模式 CNend */
+        if (ret != IOT_SUCCESS) {
+            printf("ADC Read Fail\n");
+            return  NULL;
+        }    
+        g_gpio5_adc_buf[i] = data;
+    }
+
+    for (i = 0; i < ADC_TEST_LENGTH; i++) {  
+        vlt = g_gpio5_adc_buf[i]; 
+        voltage = (float)vlt * 1.8 * 4 / 4096.0;  
+		/* vlt * 1.8* 4 / 4096.0为将码字转换为电压 */
+        vlt_max = (voltage > vlt_max) ? voltage : vlt_max;
+        vlt_min = (voltage < vlt_min) ? voltage : vlt_min;
+    }
+    printf("vlt_max is %f\r\n", vlt_max);
+    if (vlt_max > 0.6 && vlt_max < 1.0) {
+        gpio5_isr_func_mode();
+    } 
+}
+
+//按键中断
+void interrupt_monitor(void)
+{
+    unsigned int  ret = 0;
+    /*gpio5 switch2 mode*/
+    g_gpio5_tick = hi_get_tick();
+    ret = IoTGpioRegisterIsrFunc(GPIO5, IOT_INT_TYPE_EDGE, IOT_GPIO_EDGE_FALL_LEVEL_LOW, get_gpio5_voltage, NULL);
+    if (ret == IOT_SUCCESS) {
+        printf(" register gpio5\r\n");
+    }
+}
+void OledShowChinese3(uint8_t x, uint8_t y, uint8_t idx)
+{
+    // 控制循环
+    uint8_t t;
+
+    // 显示汉字的上半部分
+    OledSetPosition(x, y);
+    for (t = 0; t < 16; t++)
+    {
+        WriteData(fonts3[32 * idx + t]);
+    }
+
+    // 显示汉字的下半部分
+    OledSetPosition(x, y + 1);
+    for (t = 16; t < 32; t++)
+    {
+        WriteData(fonts3[32 * idx + t]);
+    }
+}
+static void controlTask(void *arg)
+{
+    (void)arg;
+    int control_temp = control_flag;
+    int count = 0;
+    static int display_timer = 0;  // 显示计时器
+    
+    while (1)
+    {
+        if(control_flag != control_temp)
+        {
+            count = 0;
+            display_timer = 0;
+            OledClearScreen();  // 使用新的清屏函数
+            control_temp = control_flag;
+            
+            // 处理新的JSON命令格式
+            if(control_flag == CMD_ROTATE_DISPLAY_CLEAR)  // 命令1：顺时针90°+显示字符串+10秒后逆时针90°+清屏
+            {
+                printf("Command 1: Rotate clockwise, display text, wait 10s, rotate back, clear\r\n");
+                
+                // 顺时针旋转90度
+                servo_rotate_clockwise_90();
+                
+                // 显示字符串
+                if (strlen(g_current_command.text) > 0) {
+                    printf("Displaying text: %s\r\n", g_current_command.text);
+                    DisplayMixedString(0, 0, g_current_command.text);
+                }
+                
+                display_timer = 10;  // 设置10秒计时器
+            }
+            else if(control_flag == CMD_ROTATE_CLOCKWISE)  // 命令2：顺时针90°
+            {
+                printf("Command 2: Rotate clockwise 90 degrees\r\n");
+                servo_rotate_clockwise_90();
+            }
+            else if(control_flag == CMD_ROTATE_COUNTER)  // 命令3：逆时针90°
+            {
+                printf("Command 3: Rotate counter-clockwise 90 degrees\r\n");
+                servo_rotate_counter_clockwise_90();
+            }
+            else if(control_flag == CMD_DISPLAY_ONLY)  // 命令4：只显示字符串，舵机不动
+            {
+                printf("Command 4: Display text only, no servo movement\r\n");
+                
+                // 只显示字符串，不控制舵机
+                if (strlen(g_current_command.text) > 0) {
+                    printf("Displaying text: %s\r\n", g_current_command.text);
+                    DisplayMixedString(0, 0, g_current_command.text);
+                }
+                
+                display_timer = 2;  // 设置2秒计时器
+            }
+            // 兼容旧命令的处理逻辑（只有在非JSON命令时才执行）
+            else if(control_flag == 0 && g_current_command.cmd == 0)  // 兼容旧命令：关闭
+            {
+                regress_middle();
+                printf("barrier off\n");
+            }
+            else if(control_flag == 1 && g_current_command.cmd == 0)  // 兼容旧命令：开启（只有非JSON命令时）
+            {
+                servo_rotate_counter_clockwise_90();
+                printf("barrier on\n");
+            }
+            
+            // 兼容旧的复杂字符串解析逻辑 - 只有在非JSON命令时才执行
+            if(control_flag == 2 && g_current_command.cmd == 0)
+            {
+                char prefix[20];  // 存储前部分字符串
+                int num;          // 存储后部分数字
+                int index1 = 0;
+                
+                // 使用 sscanf 解析字符串
+                int result = sscanf(response, "%[^i]index:%dflag:%d", prefix, &num,&index1);
+
+                if (result == 3) {  
+                    memset(response,0,sizeof(response));
+                    OledShowChinese3(0,0,num);
+                    OledShowString(18, 0, prefix, FONT8x16);
+                    OledShowChinese3(0 , 2, index1); 
+                    OledShowChinese3(18 , 2, 33);        
+                }
+                if (index1 == 32)
+                {
+                    servo_rotate_counter_clockwise_90();
+                }
+            }
+        }
+
+        // 处理命令1的10秒计时器
+        if(control_flag == CMD_ROTATE_DISPLAY_CLEAR && display_timer > 0)
+        {
+            display_timer--;
+            if(display_timer == 0)
+            {
+                printf("10 seconds elapsed, rotating back and clearing screen\r\n");
+                // 逆时针旋转90度
+                servo_rotate_counter_clockwise_90();
+                // 清屏
+                OledClearScreen();
+                // 重置控制标志
+                control_flag = 0;
+            }
+        }
+
+        // 处理命令4的2秒计时器
+        if(control_flag == CMD_DISPLAY_ONLY && display_timer > 0)
+        {
+            display_timer--;
+            if(display_timer == 0)
+            {
+                printf("2 seconds elapsed, clearing screen for command 4\r\n");
+                // 清屏
+                OledClearScreen();
+                // 重置控制标志，使其能够响应下一个命令4
+                control_flag = 0;
+            }
+        }
+
+        // 兼容旧的计时逻辑
+        if(control_flag == 2 && g_current_command.cmd == 0)
+        {
+            count++;
+            if(count > 10)
+            {
+                control_flag = 0;
+                count = 0;
+            }
+        }
+        
+        sleep(1);
+    }
+}
+// 主线程函数
+static void NetDemoTask(void *arg)
+{
+    (void)arg;
+    
+    int control_temp = 0;
+    // 定义热点配置
+    WifiDeviceConfig config = {0};
+
+    // 设置热点配置中的SSID
+    strcpy(config.ssid, PARAM_HOTSPOT_SSID);
+
+    // 设置热点配置中的密码
+    strcpy(config.preSharedKey, PARAM_HOTSPOT_PSK);
+
+    // 设置热点配置中的加密方式(Wi-Fi security types)
+    config.securityType = PARAM_HOTSPOT_TYPE;
+
+    // 显示启动信息
+    printf("=== Hi3861 智能闸机控制系统启动 ===\r\n");
+    printf("正在连接WiFi: %s\r\n", PARAM_HOTSPOT_SSID);
+    printf("服务器地址: %s:%d\r\n", PARAM_SERVER_ADDR, PARAM_SERVER_PORT);
+    
+    // 在OLED上显示启动信息
+    OledFillScreen(0x00);
+    OledShowString(0, 0, "Starting...", FONT8x16);
+    OledShowString(0, 2, PARAM_HOTSPOT_SSID, FONT8x16);
+
+    // 等待100ms
+    osDelay(10);
+
+    // 连接到热点
+    printf("开始连接WiFi...\r\n");
+    int netId = ConnectToHotspot(&config);
+
+    // 检查是否成功连接到热点
+    if (netId < 0)
+    {
+        // 连接到热点失败
+        printf("WiFi连接失败！错误代码: %d\r\n", netId); 
+        OledFillScreen(0x00);                                    
+        OledShowString(0, 0, "WiFi Failed!", FONT8x16);
+        OledShowString(0, 2, "Check Config", FONT8x16);
+        return;
+    }
+    
+    // 连接到热点成功，显示连接成功信息
+    printf("WiFi连接成功！网络ID: %d\r\n", netId);
+    OledFillScreen(0x00);
+    OledShowString(0, 0, "WiFi Connected", FONT8x16);
+    OledShowString(0, 2, "Starting UDP...", FONT8x16);
+    
+    // 等待一段时间确保连接稳定
+    printf("等待网络稳定...\r\n");
+    sleep(3);
+    
+    // 运行UDP客户端测试，发送IP地址到服务器
+    printf("启动UDP客户端，连接服务器 %s:%d\r\n", PARAM_SERVER_ADDR, PARAM_SERVER_PORT);
+    UdpClientTest(PARAM_SERVER_ADDR, PARAM_SERVER_PORT);
+
+    // 断开热点连接
+    printf("断开WiFi连接...\r\n");
+    DisconnectWithHotspot(netId);
+    printf("WiFi连接已断开！\r\n");
+}
+
+// 入口函数
+static void NetDemoEntry(void)
+{
+    switch_init();
+    interrupt_monitor();
+    // 初始化OLED
+    OledInit();
+
+    // 全屏填充黑色
+    OledFillScreen(0x00);
+
+    // OLED显示APP标题
+    OledShowString(0, 0, "UdpClient Test", FONT8x16);
+
+
+    // 定义线程属性
+    osThreadAttr_t attr;
+    attr.name = "NetDemoTask";
+    attr.attr_bits = 0U;
+    attr.cb_mem = NULL;
+    attr.cb_size = 0U;
+    attr.stack_mem = NULL;
+    attr.stack_size = 10240;
+    attr.priority = osPriorityNormal;
+    // 创建线程
+    if (osThreadNew(NetDemoTask, NULL, &attr) == NULL)
+    {
+        printf("[NetDemoEntry] Falied to create NetDemoTask!\n");
+    }
+    attr.name = "controlTask";
+    attr.stack_size = 2048;
+    if (osThreadNew(controlTask, NULL, &attr) == NULL)
+    {
+        printf("[control] Falied to create NetDemoTask!\n");
+    }
+}
+
+// 运行入口函数
+SYS_RUN(NetDemoEntry);
--- a/display_helper.c
+++ b/display_helper.c
@@ -0,0 +1,64 @@
+#include "display_helper.h"
+#include "chinese_char_map.h"
+#include "json_parser.h"
+#include "oled_ssd1306.h"
+#include <string.h>
+#include <stdio.h>
+
+// 显示混合字符串（中文+英文数字）
+void DisplayMixedString(uint8_t start_x, uint8_t start_y, const char* text) {
+    if (!text) {
+        return;
+    }
+    
+    uint8_t x = start_x;
+    uint8_t y = start_y;
+    int i = 0;
+    int text_len = strlen(text);
+    
+    printf("DisplayMixedString: Processing text '%s' (length: %d)\r\n", text, text_len);
+    
+    while (i < text_len) {
+        // 检查是否为UTF-8中文字符（通常以0xE开头的3字节序列）
+        if ((unsigned char)text[i] >= 0xE0 && i + 2 < text_len) {
+            // 提取3字节的UTF-8中文字符
+            char chinese_char[4] = {0};
+            chinese_char[0] = text[i];
+            chinese_char[1] = text[i + 1];
+            chinese_char[2] = text[i + 2];
+            chinese_char[3] = '\0';
+            
+            printf("Found Chinese char: %02X %02X %02X\r\n", 
+                   (unsigned char)chinese_char[0], 
+                   (unsigned char)chinese_char[1], 
+                   (unsigned char)chinese_char[2]);
+            
+            // 查找字符在fonts3数组中的索引
+            int font_index = FindChineseCharIndex(chinese_char);
+            if (font_index >= 0) {
+                printf("Displaying Chinese char at index %d, position (%d, %d)\r\n", font_index, x, y);
+                OledShowChinese3(x, y, font_index);
+                x += 16; // 中文字符宽度为16像素
+            } else {
+                printf("Chinese char not found in font table, displaying as '?'\r\n");
+                // 如果找不到字符，显示问号
+                OledShowString(x, y, "?", FONT8x16);
+                x += 8; // 英文字符宽度为8像素
+            }
+            i += 3; // 跳过3字节的UTF-8字符
+        } else {
+            // 处理ASCII字符（英文、数字、符号）
+            char ascii_char[2] = {text[i], '\0'};
+            printf("Found ASCII char: '%c' (0x%02X)\r\n", text[i], (unsigned char)text[i]);
+            OledShowString(x, y, ascii_char, FONT8x16);
+            x += 8; // 英文字符宽度为8像素
+            i++;
+        }
+        
+        // 检查是否需要换行（假设屏幕宽度为128像素）
+        if (x >= 120) {
+            x = start_x;
+            y += 2; // 每行高度为2个单位（16像素）
+        }
+    }
+}
--- a/display_helper.h
+++ b/display_helper.h
@@ -0,0 +1,9 @@
+#ifndef DISPLAY_HELPER_H
+#define DISPLAY_HELPER_H
+
+#include <stdint.h>
+
+// 显示混合字符串（中文+英文数字）
+void DisplayMixedString(uint8_t start_x, uint8_t start_y, const char* text);
+
+#endif // DISPLAY_HELPER_H
--- a/json_parser.c
+++ b/json_parser.c
@@ -0,0 +1,72 @@
+#include "json_parser.h"
+#include "chinese_char_map.h"
+#include <stdio.h>
+#include <string.h>
+#include <stdlib.h>
+
+// 简单的JSON解析函数，解析格式: {"cmd":1,"text":"hello"}
+int ParseJsonCommand(const char* json_str, JsonCommand* command) {
+    if (!json_str || !command) {
+        return -1;
+    }
+    
+    // 初始化结构体
+    command->cmd = 0;
+    memset(command->text, 0, MAX_TEXT_LENGTH);
+    
+    // 查找cmd字段
+    const char* cmd_pos = strstr(json_str, "\"cmd\":");
+    if (cmd_pos) {
+        cmd_pos += 6; // 跳过"cmd":
+        // 跳过空格
+        while (*cmd_pos == ' ') cmd_pos++;
+        command->cmd = atoi(cmd_pos);
+    }
+    
+    // 查找text字段
+    const char* text_pos = strstr(json_str, "\"text\":");
+    if (text_pos) {
+        text_pos += 7; // 跳过"text":
+        // 跳过空格和引号
+        while (*text_pos == ' ' || *text_pos == '\"') text_pos++;
+        
+        // 复制文本直到遇到引号或字符串结束
+        int i = 0;
+        while (*text_pos && *text_pos != '\"' && i < MAX_TEXT_LENGTH - 1) {
+            command->text[i++] = *text_pos++;
+        }
+        command->text[i] = '\0';
+    }
+    
+    return 0;
+}
+
+// 创建IP地址消息，格式: {"type":"ip","address":"192.168.1.100"}
+int CreateIpMessage(char* buffer, int buffer_size, const char* ip_address) {
+    if (!buffer || !ip_address || buffer_size < 50) {
+        return -1;
+    }
+    
+    int len = snprintf(buffer, buffer_size, 
+                      "{\"type\":\"ip\",\"address\": \"%s\"}", 
+                      ip_address);
+    
+    return (len > 0 && len < buffer_size) ? 0 : -1;
+}
+
+// 查找中文字符在fonts3数组中的索引
+int FindChineseCharIndex(const char* utf8_char) {
+    if (!utf8_char) {
+        return -1;
+    }
+    
+    // 遍历映射表查找匹配的字符
+    for (int i = 0; i < CHINESE_CHAR_MAP_SIZE; i++) {
+        if (strcmp(utf8_char, chinese_char_map[i].utf8_char) == 0) {
+            return chinese_char_map[i].font_index;
+        }
+    }
+    
+    // 未找到匹配的字符
+    return -1;
+}
--- a/json_parser.h
+++ b/json_parser.h
@@ -0,0 +1,29 @@
+#ifndef JSON_PARSER_H
+#define JSON_PARSER_H
+
+#include <stdint.h>
+
+// 定义命令类型
+#define CMD_ROTATE_DISPLAY_CLEAR 1  // 顺时针90°+显示字符串+10秒后逆时针90°+清屏
+#define CMD_ROTATE_CLOCKWISE     2  // 顺时针90°
+#define CMD_ROTATE_COUNTER       3  // 逆时针90°
+#define CMD_DISPLAY_ONLY         4  // 只显示字符串，舵机不动
+
+// 定义最大字符串长度
+#define MAX_TEXT_LENGTH 64
+
+// JSON命令结构体
+typedef struct {
+    int cmd;                        // 命令类型
+    char text[MAX_TEXT_LENGTH];     // 显示文本
+} JsonCommand;
+
+// 函数声明
+int ParseJsonCommand(const char* json_str, JsonCommand* command);
+// 创建IP地址消息，格式: {"type":"ip","address":"192.168.1.100"}
+int CreateIpMessage(char* buffer, int buffer_size, const char* ip_address);
+
+// 查找中文字符在fonts3数组中的索引
+int FindChineseCharIndex(const char* utf8_char);
+
+#endif // JSON_PARSER_H
--- a/oled_fonts.h
+++ b/oled_fonts.h
@@ -0,0 +1,211 @@
+// 字库头文件
+
+// 定义条件编译宏，防止头文件的重复包含和编译
+#ifndef OLOED_FONTS_H
+#define OLOED_FONTS_H
+
+/************************************6*8的点阵************************************/
+// 取模方式：纵向8点下高位
+// 采用N*6的二维数组
+// 第一维表示字符
+// 每个字符对应第二维的6个数组元素，每个数组元素1字节，表示1列像素，一共6列8行
+static unsigned char F6x8[][6] =
+{
+    { 0x00, 0x00, 0x00, 0x00, 0x00, 0x00 }, // 空格
+    { 0x00, 0x00, 0x00, 0x2f, 0x00, 0x00 }, // !
+    { 0x00, 0x00, 0x07, 0x00, 0x07, 0x00 }, // "
+    { 0x00, 0x14, 0x7f, 0x14, 0x7f, 0x14 }, // #
+    { 0x00, 0x24, 0x2a, 0x7f, 0x2a, 0x12 }, // $
+    { 0x00, 0x62, 0x64, 0x08, 0x13, 0x23 }, // %
+    { 0x00, 0x36, 0x49, 0x55, 0x22, 0x50 }, // &
+    { 0x00, 0x00, 0x05, 0x03, 0x00, 0x00 }, // '
+    { 0x00, 0x00, 0x1c, 0x22, 0x41, 0x00 }, // (
+    { 0x00, 0x00, 0x41, 0x22, 0x1c, 0x00 }, // )
+    { 0x00, 0x14, 0x08, 0x3E, 0x08, 0x14 }, // *
+    { 0x00, 0x08, 0x08, 0x3E, 0x08, 0x08 }, // +
+    { 0x00, 0x00, 0x00, 0xA0, 0x60, 0x00 }, // ,
+    { 0x00, 0x08, 0x08, 0x08, 0x08, 0x08 }, // -
+    { 0x00, 0x00, 0x60, 0x60, 0x00, 0x00 }, // .
+    { 0x00, 0x20, 0x10, 0x08, 0x04, 0x02 }, // /
+    { 0x00, 0x3E, 0x51, 0x49, 0x45, 0x3E }, // 0
+    { 0x00, 0x00, 0x42, 0x7F, 0x40, 0x00 }, // 1
+    { 0x00, 0x42, 0x61, 0x51, 0x49, 0x46 }, // 2
+    { 0x00, 0x21, 0x41, 0x45, 0x4B, 0x31 }, // 3
+    { 0x00, 0x18, 0x14, 0x12, 0x7F, 0x10 }, // 4
+    { 0x00, 0x27, 0x45, 0x45, 0x45, 0x39 }, // 5
+    { 0x00, 0x3C, 0x4A, 0x49, 0x49, 0x30 }, // 6
+    { 0x00, 0x01, 0x71, 0x09, 0x05, 0x03 }, // 7
+    { 0x00, 0x36, 0x49, 0x49, 0x49, 0x36 }, // 8
+    { 0x00, 0x06, 0x49, 0x49, 0x29, 0x1E }, // 9
+    { 0x00, 0x00, 0x36, 0x36, 0x00, 0x00 }, // :
+    { 0x00, 0x00, 0x56, 0x36, 0x00, 0x00 }, // ;
+    { 0x00, 0x08, 0x14, 0x22, 0x41, 0x00 }, // <
+    { 0x00, 0x14, 0x14, 0x14, 0x14, 0x14 }, // =
+    { 0x00, 0x00, 0x41, 0x22, 0x14, 0x08 }, // >
+    { 0x00, 0x02, 0x01, 0x51, 0x09, 0x06 }, // ?
+    { 0x00, 0x32, 0x49, 0x59, 0x51, 0x3E }, // @
+    { 0x00, 0x7C, 0x12, 0x11, 0x12, 0x7C }, // A
+    { 0x00, 0x7F, 0x49, 0x49, 0x49, 0x36 }, // B
+    { 0x00, 0x3E, 0x41, 0x41, 0x41, 0x22 }, // C
+    { 0x00, 0x7F, 0x41, 0x41, 0x22, 0x1C }, // D
+    { 0x00, 0x7F, 0x49, 0x49, 0x49, 0x41 }, // E
+    { 0x00, 0x7F, 0x09, 0x09, 0x09, 0x01 }, // F
+    { 0x00, 0x3E, 0x41, 0x49, 0x49, 0x7A }, // G
+    { 0x00, 0x7F, 0x08, 0x08, 0x08, 0x7F }, // H
+    { 0x00, 0x00, 0x41, 0x7F, 0x41, 0x00 }, // I
+    { 0x00, 0x20, 0x40, 0x41, 0x3F, 0x01 }, // J
+    { 0x00, 0x7F, 0x08, 0x14, 0x22, 0x41 }, // K
+    { 0x00, 0x7F, 0x40, 0x40, 0x40, 0x40 }, // L
+    { 0x00, 0x7F, 0x02, 0x0C, 0x02, 0x7F }, // M
+    { 0x00, 0x7F, 0x04, 0x08, 0x10, 0x7F }, // N
+    { 0x00, 0x3E, 0x41, 0x41, 0x41, 0x3E }, // O
+    { 0x00, 0x7F, 0x09, 0x09, 0x09, 0x06 }, // P
+    { 0x00, 0x3E, 0x41, 0x51, 0x21, 0x5E }, // Q
+    { 0x00, 0x7F, 0x09, 0x19, 0x29, 0x46 }, // R
+    { 0x00, 0x46, 0x49, 0x49, 0x49, 0x31 }, // S
+    { 0x00, 0x01, 0x01, 0x7F, 0x01, 0x01 }, // T
+    { 0x00, 0x3F, 0x40, 0x40, 0x40, 0x3F }, // U
+    { 0x00, 0x1F, 0x20, 0x40, 0x20, 0x1F }, // V
+    { 0x00, 0x3F, 0x40, 0x38, 0x40, 0x3F }, // W
+    { 0x00, 0x63, 0x14, 0x08, 0x14, 0x63 }, // X
+    { 0x00, 0x07, 0x08, 0x70, 0x08, 0x07 }, // Y
+    { 0x00, 0x61, 0x51, 0x49, 0x45, 0x43 }, // Z
+    { 0x00, 0x00, 0x7F, 0x41, 0x41, 0x00 }, // [
+    { 0x00, 0x55, 0x2A, 0x55, 0x2A, 0x55 }, /* \ */
+    { 0x00, 0x00, 0x41, 0x41, 0x7F, 0x00 }, // ]
+    { 0x00, 0x04, 0x02, 0x01, 0x02, 0x04 }, // ^
+    { 0x00, 0x40, 0x40, 0x40, 0x40, 0x40 }, // _
+    { 0x00, 0x00, 0x01, 0x02, 0x04, 0x00 }, // '
+    { 0x00, 0x20, 0x54, 0x54, 0x54, 0x78 }, // a
+    { 0x00, 0x7F, 0x48, 0x44, 0x44, 0x38 }, // b
+    { 0x00, 0x38, 0x44, 0x44, 0x44, 0x20 }, // c
+    { 0x00, 0x38, 0x44, 0x44, 0x48, 0x7F }, // d
+    { 0x00, 0x38, 0x54, 0x54, 0x54, 0x18 }, // e
+    { 0x00, 0x08, 0x7E, 0x09, 0x01, 0x02 }, // f
+    { 0x00, 0x18, 0xA4, 0xA4, 0xA4, 0x7C }, // g
+    { 0x00, 0x7F, 0x08, 0x04, 0x04, 0x78 }, // h
+    { 0x00, 0x00, 0x44, 0x7D, 0x40, 0x00 }, // i
+    { 0x00, 0x40, 0x80, 0x84, 0x7D, 0x00 }, // j
+    { 0x00, 0x7F, 0x10, 0x28, 0x44, 0x00 }, // k
+    { 0x00, 0x00, 0x41, 0x7F, 0x40, 0x00 }, // l
+    { 0x00, 0x7C, 0x04, 0x18, 0x04, 0x78 }, // m
+    { 0x00, 0x7C, 0x08, 0x04, 0x04, 0x78 }, // n
+    { 0x00, 0x38, 0x44, 0x44, 0x44, 0x38 }, // o
+    { 0x00, 0xFC, 0x24, 0x24, 0x24, 0x18 }, // p
+    { 0x00, 0x18, 0x24, 0x24, 0x18, 0xFC }, // q
+    { 0x00, 0x7C, 0x08, 0x04, 0x04, 0x08 }, // r
+    { 0x00, 0x48, 0x54, 0x54, 0x54, 0x20 }, // s
+    { 0x00, 0x04, 0x3F, 0x44, 0x40, 0x20 }, // t
+    { 0x00, 0x3C, 0x40, 0x40, 0x20, 0x7C }, // u
+    { 0x00, 0x1C, 0x20, 0x40, 0x20, 0x1C }, // v
+    { 0x00, 0x3C, 0x40, 0x30, 0x40, 0x3C }, // w
+    { 0x00, 0x44, 0x28, 0x10, 0x28, 0x44 }, // x
+    { 0x00, 0x1C, 0xA0, 0xA0, 0xA0, 0x7C }, // y
+    { 0x00, 0x44, 0x64, 0x54, 0x4C, 0x44 }, // z
+    { 0x14, 0x14, 0x14, 0x14, 0x14, 0x14 }, // horiz lines
+};
+
+/****************************************8*16的点阵************************************/
+// 取模方式：纵向8点下高位
+// 采用一维数组，每个字符对应16个数组元素
+// 每16个数组元素的前8个表示字符的上半部分（8*8点阵），后8个表示字符的下半部分（8*8点阵），一共8列16行
+static const unsigned char F8X16[]=
+{
+    0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,//空格 0
+    0x00,0x00,0x00,0xF8,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x33,0x30,0x00,0x00,0x00,//! 1
+    0x00,0x10,0x0C,0x06,0x10,0x0C,0x06,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,//" 2
+    0x40,0xC0,0x78,0x40,0xC0,0x78,0x40,0x00,0x04,0x3F,0x04,0x04,0x3F,0x04,0x04,0x00,//# 3
+    0x00,0x70,0x88,0xFC,0x08,0x30,0x00,0x00,0x00,0x18,0x20,0xFF,0x21,0x1E,0x00,0x00,//$ 4
+    0xF0,0x08,0xF0,0x00,0xE0,0x18,0x00,0x00,0x00,0x21,0x1C,0x03,0x1E,0x21,0x1E,0x00,//% 5
+    0x00,0xF0,0x08,0x88,0x70,0x00,0x00,0x00,0x1E,0x21,0x23,0x24,0x19,0x27,0x21,0x10,//& 6
+    0x10,0x16,0x0E,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,//' 7
+    0x00,0x00,0x00,0xE0,0x18,0x04,0x02,0x00,0x00,0x00,0x00,0x07,0x18,0x20,0x40,0x00,//( 8
+    0x00,0x02,0x04,0x18,0xE0,0x00,0x00,0x00,0x00,0x40,0x20,0x18,0x07,0x00,0x00,0x00,//) 9
+    0x40,0x40,0x80,0xF0,0x80,0x40,0x40,0x00,0x02,0x02,0x01,0x0F,0x01,0x02,0x02,0x00,//* 10
+    0x00,0x00,0x00,0xF0,0x00,0x00,0x00,0x00,0x01,0x01,0x01,0x1F,0x01,0x01,0x01,0x00,//+ 11
+    0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x80,0xB0,0x70,0x00,0x00,0x00,0x00,0x00,//, 12
+    0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x01,0x01,0x01,0x01,0x01,0x01,0x01,//- 13
+    0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x30,0x30,0x00,0x00,0x00,0x00,0x00,//. 14
+    0x00,0x00,0x00,0x00,0x80,0x60,0x18,0x04,0x00,0x60,0x18,0x06,0x01,0x00,0x00,0x00,/// 15
+    0x00,0xE0,0x10,0x08,0x08,0x10,0xE0,0x00,0x00,0x0F,0x10,0x20,0x20,0x10,0x0F,0x00,//0 16
+    0x00,0x10,0x10,0xF8,0x00,0x00,0x00,0x00,0x00,0x20,0x20,0x3F,0x20,0x20,0x00,0x00,//1 17
+    0x00,0x70,0x08,0x08,0x08,0x88,0x70,0x00,0x00,0x30,0x28,0x24,0x22,0x21,0x30,0x00,//2 18
+    0x00,0x30,0x08,0x88,0x88,0x48,0x30,0x00,0x00,0x18,0x20,0x20,0x20,0x11,0x0E,0x00,//3 19
+    0x00,0x00,0xC0,0x20,0x10,0xF8,0x00,0x00,0x00,0x07,0x04,0x24,0x24,0x3F,0x24,0x00,//4 20
+    0x00,0xF8,0x08,0x88,0x88,0x08,0x08,0x00,0x00,0x19,0x21,0x20,0x20,0x11,0x0E,0x00,//5 21
+    0x00,0xE0,0x10,0x88,0x88,0x18,0x00,0x00,0x00,0x0F,0x11,0x20,0x20,0x11,0x0E,0x00,//6 22
+    0x00,0x38,0x08,0x08,0xC8,0x38,0x08,0x00,0x00,0x00,0x00,0x3F,0x00,0x00,0x00,0x00,//7 23
+    0x00,0x70,0x88,0x08,0x08,0x88,0x70,0x00,0x00,0x1C,0x22,0x21,0x21,0x22,0x1C,0x00,//8 24
+    0x00,0xE0,0x10,0x08,0x08,0x10,0xE0,0x00,0x00,0x00,0x31,0x22,0x22,0x11,0x0F,0x00,//9 25
+    0x00,0x00,0x00,0xC0,0xC0,0x00,0x00,0x00,0x00,0x00,0x00,0x30,0x30,0x00,0x00,0x00,//: 26
+    0x00,0x00,0x00,0x80,0x00,0x00,0x00,0x00,0x00,0x00,0x80,0x60,0x00,0x00,0x00,0x00,//; 27
+    0x00,0x00,0x80,0x40,0x20,0x10,0x08,0x00,0x00,0x01,0x02,0x04,0x08,0x10,0x20,0x00,//< 28
+    0x40,0x40,0x40,0x40,0x40,0x40,0x40,0x00,0x04,0x04,0x04,0x04,0x04,0x04,0x04,0x00,//= 29
+    0x00,0x08,0x10,0x20,0x40,0x80,0x00,0x00,0x00,0x20,0x10,0x08,0x04,0x02,0x01,0x00,//> 30
+    0x00,0x70,0x48,0x08,0x08,0x08,0xF0,0x00,0x00,0x00,0x00,0x30,0x36,0x01,0x00,0x00,//? 31
+    0xC0,0x30,0xC8,0x28,0xE8,0x10,0xE0,0x00,0x07,0x18,0x27,0x24,0x23,0x14,0x0B,0x00,//@ 32
+    0x00,0x00,0xC0,0x38,0xE0,0x00,0x00,0x00,0x20,0x3C,0x23,0x02,0x02,0x27,0x38,0x20,//A 33
+    0x08,0xF8,0x88,0x88,0x88,0x70,0x00,0x00,0x20,0x3F,0x20,0x20,0x20,0x11,0x0E,0x00,//B 34
+    0xC0,0x30,0x08,0x08,0x08,0x08,0x38,0x00,0x07,0x18,0x20,0x20,0x20,0x10,0x08,0x00,//C 35
+    0x08,0xF8,0x08,0x08,0x08,0x10,0xE0,0x00,0x20,0x3F,0x20,0x20,0x20,0x10,0x0F,0x00,//D 36
+    0x08,0xF8,0x88,0x88,0xE8,0x08,0x10,0x00,0x20,0x3F,0x20,0x20,0x23,0x20,0x18,0x00,//E 37
+    0x08,0xF8,0x88,0x88,0xE8,0x08,0x10,0x00,0x20,0x3F,0x20,0x00,0x03,0x00,0x00,0x00,//F 38
+    0xC0,0x30,0x08,0x08,0x08,0x38,0x00,0x00,0x07,0x18,0x20,0x20,0x22,0x1E,0x02,0x00,//G 39
+    0x08,0xF8,0x08,0x00,0x00,0x08,0xF8,0x08,0x20,0x3F,0x21,0x01,0x01,0x21,0x3F,0x20,//H 40
+    0x00,0x08,0x08,0xF8,0x08,0x08,0x00,0x00,0x00,0x20,0x20,0x3F,0x20,0x20,0x00,0x00,//I 41
+    0x00,0x00,0x08,0x08,0xF8,0x08,0x08,0x00,0xC0,0x80,0x80,0x80,0x7F,0x00,0x00,0x00,//J 42
+    0x08,0xF8,0x88,0xC0,0x28,0x18,0x08,0x00,0x20,0x3F,0x20,0x01,0x26,0x38,0x20,0x00,//K 43
+    0x08,0xF8,0x08,0x00,0x00,0x00,0x00,0x00,0x20,0x3F,0x20,0x20,0x20,0x20,0x30,0x00,//L 44
+    0x08,0xF8,0xF8,0x00,0xF8,0xF8,0x08,0x00,0x20,0x3F,0x00,0x3F,0x00,0x3F,0x20,0x00,//M 45
+    0x08,0xF8,0x30,0xC0,0x00,0x08,0xF8,0x08,0x20,0x3F,0x20,0x00,0x07,0x18,0x3F,0x00,//N 46
+    0xE0,0x10,0x08,0x08,0x08,0x10,0xE0,0x00,0x0F,0x10,0x20,0x20,0x20,0x10,0x0F,0x00,//O 47
+    0x08,0xF8,0x08,0x08,0x08,0x08,0xF0,0x00,0x20,0x3F,0x21,0x01,0x01,0x01,0x00,0x00,//P 48
+    0xE0,0x10,0x08,0x08,0x08,0x10,0xE0,0x00,0x0F,0x18,0x24,0x24,0x38,0x50,0x4F,0x00,//Q 49
+    0x08,0xF8,0x88,0x88,0x88,0x88,0x70,0x00,0x20,0x3F,0x20,0x00,0x03,0x0C,0x30,0x20,//R 50
+    0x00,0x70,0x88,0x08,0x08,0x08,0x38,0x00,0x00,0x38,0x20,0x21,0x21,0x22,0x1C,0x00,//S 51
+    0x18,0x08,0x08,0xF8,0x08,0x08,0x18,0x00,0x00,0x00,0x20,0x3F,0x20,0x00,0x00,0x00,//T 52
+    0x08,0xF8,0x08,0x00,0x00,0x08,0xF8,0x08,0x00,0x1F,0x20,0x20,0x20,0x20,0x1F,0x00,//U 53
+    0x08,0x78,0x88,0x00,0x00,0xC8,0x38,0x08,0x00,0x00,0x07,0x38,0x0E,0x01,0x00,0x00,//V 54
+    0xF8,0x08,0x00,0xF8,0x00,0x08,0xF8,0x00,0x03,0x3C,0x07,0x00,0x07,0x3C,0x03,0x00,//W 55
+    0x08,0x18,0x68,0x80,0x80,0x68,0x18,0x08,0x20,0x30,0x2C,0x03,0x03,0x2C,0x30,0x20,//X 56
+    0x08,0x38,0xC8,0x00,0xC8,0x38,0x08,0x00,0x00,0x00,0x20,0x3F,0x20,0x00,0x00,0x00,//Y 57
+    0x10,0x08,0x08,0x08,0xC8,0x38,0x08,0x00,0x20,0x38,0x26,0x21,0x20,0x20,0x18,0x00,//Z 58
+    0x00,0x00,0x00,0xFE,0x02,0x02,0x02,0x00,0x00,0x00,0x00,0x7F,0x40,0x40,0x40,0x00,//[ 59
+    0x00,0x0C,0x30,0xC0,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x01,0x06,0x38,0xC0,0x00,//\ 60
+    0x00,0x02,0x02,0x02,0xFE,0x00,0x00,0x00,0x00,0x40,0x40,0x40,0x7F,0x00,0x00,0x00,//] 61
+    0x00,0x00,0x04,0x02,0x02,0x02,0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,//^ 62
+    0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x80,0x80,0x80,0x80,0x80,0x80,0x80,0x80,//_ 63
+    0x00,0x02,0x02,0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,//` 64
+    0x00,0x00,0x80,0x80,0x80,0x80,0x00,0x00,0x00,0x19,0x24,0x22,0x22,0x22,0x3F,0x20,//a 65
+    0x08,0xF8,0x00,0x80,0x80,0x00,0x00,0x00,0x00,0x3F,0x11,0x20,0x20,0x11,0x0E,0x00,//b 66
+    0x00,0x00,0x00,0x80,0x80,0x80,0x00,0x00,0x00,0x0E,0x11,0x20,0x20,0x20,0x11,0x00,//c 67
+    0x00,0x00,0x00,0x80,0x80,0x88,0xF8,0x00,0x00,0x0E,0x11,0x20,0x20,0x10,0x3F,0x20,//d 68
+    0x00,0x00,0x80,0x80,0x80,0x80,0x00,0x00,0x00,0x1F,0x22,0x22,0x22,0x22,0x13,0x00,//e 69
+    0x00,0x80,0x80,0xF0,0x88,0x88,0x88,0x18,0x00,0x20,0x20,0x3F,0x20,0x20,0x00,0x00,//f 70
+    0x00,0x00,0x80,0x80,0x80,0x80,0x80,0x00,0x00,0x6B,0x94,0x94,0x94,0x93,0x60,0x00,//g 71
+    0x08,0xF8,0x00,0x80,0x80,0x80,0x00,0x00,0x20,0x3F,0x21,0x00,0x00,0x20,0x3F,0x20,//h 72
+    0x00,0x80,0x98,0x98,0x00,0x00,0x00,0x00,0x00,0x20,0x20,0x3F,0x20,0x20,0x00,0x00,//i 73
+    0x00,0x00,0x00,0x80,0x98,0x98,0x00,0x00,0x00,0xC0,0x80,0x80,0x80,0x7F,0x00,0x00,//j 74
+    0x08,0xF8,0x00,0x00,0x80,0x80,0x80,0x00,0x20,0x3F,0x24,0x02,0x2D,0x30,0x20,0x00,//k 75
+    0x00,0x08,0x08,0xF8,0x00,0x00,0x00,0x00,0x00,0x20,0x20,0x3F,0x20,0x20,0x00,0x00,//l 76
+    0x80,0x80,0x80,0x80,0x80,0x80,0x80,0x00,0x20,0x3F,0x20,0x00,0x3F,0x20,0x00,0x3F,//m 77
+    0x80,0x80,0x00,0x80,0x80,0x80,0x00,0x00,0x20,0x3F,0x21,0x00,0x00,0x20,0x3F,0x20,//n 78
+    0x00,0x00,0x80,0x80,0x80,0x80,0x00,0x00,0x00,0x1F,0x20,0x20,0x20,0x20,0x1F,0x00,//o 79
+    0x80,0x80,0x00,0x80,0x80,0x00,0x00,0x00,0x80,0xFF,0xA1,0x20,0x20,0x11,0x0E,0x00,//p 80
+    0x00,0x00,0x00,0x80,0x80,0x80,0x80,0x00,0x00,0x0E,0x11,0x20,0x20,0xA0,0xFF,0x80,//q 81
+    0x80,0x80,0x80,0x00,0x80,0x80,0x80,0x00,0x20,0x20,0x3F,0x21,0x20,0x00,0x01,0x00,//r 82
+    0x00,0x00,0x80,0x80,0x80,0x80,0x80,0x00,0x00,0x33,0x24,0x24,0x24,0x24,0x19,0x00,//s 83
+    0x00,0x80,0x80,0xE0,0x80,0x80,0x00,0x00,0x00,0x00,0x00,0x1F,0x20,0x20,0x00,0x00,//t 84
+    0x80,0x80,0x00,0x00,0x00,0x80,0x80,0x00,0x00,0x1F,0x20,0x20,0x20,0x10,0x3F,0x20,//u 85
+    0x80,0x80,0x80,0x00,0x00,0x80,0x80,0x80,0x00,0x01,0x0E,0x30,0x08,0x06,0x01,0x00,//v 86
+    0x80,0x80,0x00,0x80,0x00,0x80,0x80,0x80,0x0F,0x30,0x0C,0x03,0x0C,0x30,0x0F,0x00,//w 87
+    0x00,0x80,0x80,0x00,0x80,0x80,0x80,0x00,0x00,0x20,0x31,0x2E,0x0E,0x31,0x20,0x00,//x 88
+    0x80,0x80,0x80,0x00,0x00,0x80,0x80,0x80,0x80,0x81,0x8E,0x70,0x18,0x06,0x01,0x00,//y 89
+    0x00,0x80,0x80,0x80,0x80,0x80,0x80,0x00,0x00,0x21,0x30,0x2C,0x22,0x21,0x30,0x00,//z 90
+    0x00,0x00,0x00,0x00,0x80,0x7C,0x02,0x02,0x00,0x00,0x00,0x00,0x00,0x3F,0x40,0x40,//{ 91
+    0x00,0x00,0x00,0x00,0xFF,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0xFF,0x00,0x00,0x00,//| 92
+    0x00,0x02,0x02,0x7C,0x80,0x00,0x00,0x00,0x00,0x40,0x40,0x3F,0x00,0x00,0x00,0x00,//} 93
+    0x00,0x06,0x01,0x01,0x02,0x02,0x04,0x04,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,//~ 94
+};
+
+#endif
--- a/oled_ssd1306.c
+++ b/oled_ssd1306.c
@@ -0,0 +1,294 @@
+// OLED显示屏简化版驱动源文件
+
+#include <stdio.h>      // 标准输入输出
+#include <stddef.h>     // 标准类型定义
+
+#include "iot_gpio.h"  // OpenHarmony HAL：IoT硬件设备操作接口-GPIO
+#include "iot_i2c.h"   // OpenHarmony HAL：IoT硬件设备操作接口-I2C
+#include "iot_errno.h" // OpenHarmony HAL：IoT硬件设备操作接口-错误代码定义
+#include "hi_io.h"     // 海思 Pegasus SDK：IoT硬件设备操作接口-IO
+
+// 字库头文件
+#include "oled_fonts.h"
+
+// OLED显示屏简化版驱动接口文件
+#include "oled_ssd1306.h"
+
+// 定义一个宏，用于计算数组的长度
+#define ARRAY_SIZE(a) sizeof(a) / sizeof(a[0])
+
+// 定义一个宏，用于标识I2C0
+#define OLED_I2C_IDX 0
+
+// 定义一个宏，用于标识I2C0的波特率（传输速率）
+#define OLED_I2C_BAUDRATE (400 * 1000) // 400KHz
+
+// 定义一个宏，用于标识OLED的宽度
+#define OLED_WIDTH (128)
+
+// 定义一个宏，用于标识SSD1306显示屏驱动芯片的设备地址
+#define OLED_I2C_ADDR 0x78
+
+// 定义一个宏，用于标识写命令操作
+#define OLED_I2C_CMD 0x00  // 0000 0000       写命令
+
+// 定义一个宏，用于标识写数据操作
+#define OLED_I2C_DATA 0x40 // 0100 0000(0x40) 写数据
+
+// 定义一个宏，用于标识100ms的延时
+#define DELAY_100_MS (100 * 1000)
+
+// 定义一个结构体，表示要发送或接收的数据
+typedef struct
+{
+    // 要发送的数据的指针
+    unsigned char *sendBuf;
+    // 要发送的数据长度
+    unsigned int sendLen;
+    // 要接收的数据的指针
+    unsigned char *receiveBuf;
+    // 要接收的数据长度
+    unsigned int receiveLen;
+} IotI2cData;
+
+/// @brief  向OLED写一个字节
+/// @param  regAddr 写入命令还是数据 OLED_I2C_CMD / OLED_I2C_DATA
+/// @param  byte 写入的内容
+/// @retval 成功返回IOT_SUCCESS，失败返回IOT_FAILURE
+static uint32_t I2cWiteByte(uint8_t regAddr, uint8_t byte)
+{
+    // 定义字节流
+    uint8_t buffer[] = {regAddr, byte};
+    IotI2cData i2cData = {0};
+    i2cData.sendBuf = buffer;
+    i2cData.sendLen = sizeof(buffer) / sizeof(buffer[0]);
+
+    // 发送字节流
+    return IoTI2cWrite(OLED_I2C_IDX, OLED_I2C_ADDR, i2cData.sendBuf, i2cData.sendLen);
+}
+
+/// @brief 向OLED写一个命令字节
+/// @param cmd 写入的命令字节
+/// @return 成功返回IOT_SUCCESS，失败返回IOT_FAILURE
+static uint32_t WriteCmd(uint8_t cmd)
+{
+    return I2cWiteByte(OLED_I2C_CMD, cmd);
+}
+
+/// @brief 向OLED写一个数据字节
+/// @param cmd 写入的数据字节
+/// @return 成功返回IOT_SUCCESS，失败返回IOT_FAILURE
+uint32_t WriteData(uint8_t data)
+{
+    return I2cWiteByte(OLED_I2C_DATA, data);
+}
+
+/// @brief 初始化SSD1306显示屏驱动芯片
+uint32_t OledInit(void)
+{
+    // 构造初始化代码
+    static const uint8_t initCmds[] = {
+        0xAE, // 显示关闭
+        0x00, // 页寻址模式时，设置列地址的低4位为0000
+        0x10, // 页寻址模式时，设置列地址的高4位为0000
+        0x40, // 设置起始行地址为第0行
+        0xB0, // 页寻址模式时，设置页面起始地址为PAGE0
+        0x81, // 设置对比度
+        0xFF, // 对比度数值
+        0xA1, // set segment remap
+        0xA6, // 设置正常显示。0对应像素熄灭，1对应像素亮起
+        0xA8, // --set multiplex ratio(1 to 64)
+        0x3F, // --1/32 duty
+        0xC8, // Com scan direction
+        0xD3, // -set display offset
+        0x00, //
+        0xD5, // set osc division
+        0x80, //
+        0xD8, // set area color mode off
+        0x05, //
+        0xD9, // Set Pre-Charge Period
+        0xF1, //
+        0xDA, // set com pin configuartion
+        0x12, //
+        0xDB, // set Vcomh
+        0x30, //
+        0x8D, // set charge pump enable
+        0x14, //
+        0xAF, // 显示开启
+    };
+
+    // 初始化GPIO-13
+    IoTGpioInit(HI_IO_NAME_GPIO_13);
+    // 设置GPIO-13引脚功能为I2C0_SDA
+    hi_io_set_func(HI_IO_NAME_GPIO_13, HI_IO_FUNC_GPIO_13_I2C0_SDA);
+    // 初始化GPIO-14
+    IoTGpioInit(HI_IO_NAME_GPIO_14);
+    // 设置GPIO-14引脚功能为I2C0_SCL
+    hi_io_set_func(HI_IO_NAME_GPIO_14, HI_IO_FUNC_GPIO_14_I2C0_SCL);
+
+    // 用指定的波特速率初始化I2C0
+    IoTI2cInit(OLED_I2C_IDX, OLED_I2C_BAUDRATE);
+
+    // 发送初始化代码，初始化SSD1306显示屏驱动芯片
+    for (size_t i = 0; i < ARRAY_SIZE(initCmds); i++)
+    {
+        // 发送一个命令字节
+        uint32_t status = WriteCmd(initCmds[i]);
+        if (status != IOT_SUCCESS)
+        {
+            return status;
+        }
+    }
+
+    // OLED初始化完成，返回成功
+    return IOT_SUCCESS;
+}
+
+/// @brief 设置显示位置
+/// @param x x坐标，1像素为单位
+/// @param y y坐标，8像素为单位。即页面起始地址
+/// @return 无
+void OledSetPosition(uint8_t x, uint8_t y)
+{
+    //设置页面起始地址
+    WriteCmd(0xb0 + y);
+
+    // 列：0~127
+    // 第0列：0x00列，二进制00000000。低地址0000，即0x00。高地址0000(需要|0x10)，0000|0x10=0x10。
+    // 第127列：0x7f列，二进制01111111。低地址1111，即0x0F。高地址0111(需要|0x10)，0111|0x10=0x17。
+
+    // 设置显示位置：列地址的低4位
+    // 直接取出列地址低4位作为命令代码的低4位，命令代码的高4位为0000
+    WriteCmd(x & 0x0f);
+
+    // 设置显示位置：列地址的高4位
+    // 取出列地址高4位作为命令代码的低4位，命令代码的高4位必须为0001
+    // 实际编程时，列地址的高4位和0x10（二进制00010000）进行按位或即得到命令代码
+    WriteCmd(((x & 0xf0) >> 4) | 0x10);
+}
+
+/// @brief 全屏填充
+/// @param fillData 填充的数据，1字节
+/// @return 无
+void OledFillScreen(uint8_t fillData)
+{
+    // 相关变量，用于遍历page和列
+    uint8_t m = 0;
+    uint8_t n = 0;
+
+    // 写入所有页的数据
+    for (m = 0; m < 8; m++)
+    {
+        //设置页地址：0~7
+        WriteCmd(0xb0 + m);
+
+        // 设置显示位置为第0列
+        WriteCmd(0x00); //设置显示位置：列低地址(0000)
+        WriteCmd(0x10); //设置显示位置：列高地址(0000)
+
+        // 写入128列数据
+        // 在一个页中，数据按列写入，一次一列，对应发送过来的1字节数据
+        for (n = 0; n < 128; n++)
+        {
+            // 写入一个字节数据
+            WriteData(fillData);
+        }
+    }
+}
+
+/// @brief 清屏函数
+/// @return 无
+void OledClearScreen(void)
+{
+    OledFillScreen(0x00);  // 用0x00填充整个屏幕，实现清屏
+}
+
+
+
+/// @brief 显示一个字符
+/// @param x: x坐标，1像素为单位
+/// @param y: y坐标，8像素为单位
+/// @param ch: 要显示的字符
+/// @param font: 字库
+void OledShowChar(uint8_t x, uint8_t y, uint8_t ch, Font font)
+{
+    // 数组下标
+    uint8_t c = 0;
+
+    // 循环控制
+    uint8_t i = 0;
+
+    // 得到数组下标
+    // 空格的ASCII码32，在字库中的下标是0。字库中的字符-空格即相应的数组下标
+    c = ch - ' ';
+
+    // 显示字符
+    if (font == FONT8x16) // 8*16的点阵，一个page放不下
+    {
+        // 显示字符的上半部分
+        // 设置显示位置
+        OledSetPosition(x, y);
+        // 逐个字节写入（16个数组元素的前8个）
+        for (i = 0; i < 8; i++)
+        {
+            WriteData(F8X16[c * 16 + i]);
+        }
+
+        // 显示字符的下半部分
+        // 设置显示位置为下一个PAGE
+        OledSetPosition(x, y + 1);
+        // 逐个字节写入（16个数组元素的后8个）
+        for (i = 0; i < 8; i++)
+        {
+            WriteData(F8X16[c * 16 + 8 + i]);
+        }
+    }
+    else // 6*8的点阵，在一个page中
+    {
+        // 设置显示位置
+        OledSetPosition(x, y);
+        // 逐个字节写入（数组第二维的6个数组元素）
+        for (i = 0; i < 6; i++)
+        {
+            WriteData(F6x8[c][i]);
+        }
+    }
+}
+
+/// @brief 显示一个字符串
+/// @param x: x坐标，1像素为单位
+/// @param y: y坐标，8像素为单位
+/// @param str: 要显示的字符串
+/// @param font: 字库
+void OledShowString(uint8_t x, uint8_t y, const char *str, Font font)
+{
+    // 字符数组（字符串）下标
+    uint8_t j = 0;
+
+    // 检查字符串是否为空
+    if (str == NULL)
+    {
+        printf("param is NULL,Please check!!!\r\n");
+        return;
+    }
+
+    // 遍历字符串，显示每个字符
+    while (str[j])
+    {
+        // 显示一个字符
+        OledShowChar(x, y, str[j], font);
+
+        // 设置字符间距
+        x += 8;
+
+        // 如果下一个要显示的字符超出了OLED显示的范围，则换行
+        if (x > 120)
+        {
+            x = 0;
+            y += 2;
+        }
+
+        // 下一个字符
+        j++;
+    }
+}
--- a/oled_ssd1306.h
+++ b/oled_ssd1306.h
@@ -0,0 +1,32 @@
+// OLED显示屏简化版驱动接口文件
+
+// 定义条件编译宏，防止头文件的重复包含和编译
+#ifndef OLED_SSD1306_H
+#define OLED_SSD1306_H
+
+#include <stdint.h>     // 定义了几种扩展的整数类型和宏
+
+// 声明接口函数
+
+uint32_t OledInit(void);
+void OledSetPosition(uint8_t x, uint8_t y);
+void OledFillScreen(uint8_t fillData);
+uint32_t WriteData(uint8_t data);
+
+// 清屏函数
+void OledClearScreen(void);
+
+// 定义字库类型
+enum Font {
+    FONT6x8 = 1,
+    FONT8x16
+};
+typedef enum Font Font;
+
+// 声明接口函数
+
+void OledShowChar(uint8_t x, uint8_t y, uint8_t ch, Font font);
+void OledShowString(uint8_t x, uint8_t y, const char* str, Font font);
+
+// 条件编译结束
+#endif // OLED_SSD1306_H
--- a/robot_sg90.c
+++ b/robot_sg90.c
@@ -0,0 +1,69 @@
+#include <stdio.h>
+#include <stdlib.h>
+#include <memory.h>
+
+#include "ohos_init.h"
+#include "cmsis_os2.h"
+#include "iot_gpio.h"
+#include "hi_io.h"
+#include "hi_time.h"
+
+//查阅机器人板原理图可知，SG90舵机通过GPIO2与3861连接
+//SG90舵机的控制需要MCU产生一个周期为20ms的脉冲信号，以0.5ms到2.5ms的高电平来控制舵机转动的角度
+#define GPIO2 2
+
+//输出20000微秒的脉冲信号(x微秒高电平,20000-x微秒低电平)
+void set_angle( unsigned int duty) {
+    IoTGpioSetDir(GPIO2, IOT_GPIO_DIR_OUT);//设置GPIO2为输出模式
+
+    //GPIO2输出x微秒高电平
+    IoTGpioSetOutputVal(GPIO2, IOT_GPIO_VALUE1);
+    hi_udelay(duty);
+
+    //GPIO2输出20000-x微秒低电平
+    IoTGpioSetOutputVal(GPIO2, IOT_GPIO_VALUE0);
+    hi_udelay(20000 - duty);
+}
+
+/*Steering gear turn left (counter-clockwise 90 degrees)
+1、依据角度与脉冲的关系，设置高电平时间为1000微秒
+2、发送20次脉冲信号，控制舵机逆时针旋转90度
+*/
+void engine_turn_left(void)
+{
+    for (int i = 0; i < 20; i++) {
+        set_angle(1000);
+    }
+}
+
+/*Steering gear turn right (clockwise 90 degrees)
+1、依据角度与脉冲的关系，设置高电平时间为2000微秒
+2、发送20次脉冲信号，控制舵机顺时针旋转90度
+*/
+void engine_turn_right(void)
+{
+    for (int i = 0; i < 20; i++) {
+        set_angle(2000);
+    }
+}
+
+/*Steering gear return to middle
+1、依据角度与脉冲的关系，设置高电平时间为1500微秒
+2、发送20次脉冲信号，控制舵机居中
+*/
+void regress_middle(void)
+{
+    for (int i = 0; i < 20; i++) {
+        set_angle(1500);
+    }
+}
+
+// 顺时针旋转90度
+void servo_rotate_clockwise_90(void) {
+    engine_turn_right();
+}
+
+// 逆时针旋转90度  
+void servo_rotate_counter_clockwise_90(void) {
+    engine_turn_left();
+}
--- a/robot_sg90.h
+++ b/robot_sg90.h
@@ -0,0 +1,13 @@
+#ifndef ROBOT_SG90_H
+#define ROBOT_SG90_H
+
+void set_angle(int angle);
+void engine_turn_left(void);
+void engine_turn_right(void);
+void regress_middle(void);
+
+// 新增的90度精确旋转函数
+void servo_rotate_clockwise_90(void);
+void servo_rotate_counter_clockwise_90(void);
+
+#endif
--- a/simple_client.py
+++ b/simple_client.py
@@ -0,0 +1,53 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+简单的UDP客户端程序
+向Hi3861设备发送JSON命令
+"""
+
+import socket
+import json
+import time
+
+def send_command():
+    """发送命令到Hi3861设备"""
+    # 目标设备信息
+    target_ip = "192.168.43.12"
+    target_port = 8081
+    
+    # 创建JSON命令
+    command = {
+        "cmd": 1,  # 测试命令4：只显示字符串，舵机不动
+        "text": "沪AAAAAA 通行 2sec"
+    }
+    
+    json_command = json.dumps(command, ensure_ascii=False)
+    
+    try:
+        # 创建UDP socket
+        sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
+        
+        # 发送命令
+        print(f"正在向 {target_ip}:{target_port} 发送命令...")
+        print(f"命令内容: {json_command}")
+        
+        sock.sendto(json_command.encode('utf-8'), (target_ip, target_port))
+        
+        print("命令发送成功！")
+        print("设备将执行以下操作：")
+        print("1. 顺时针旋转舵机90度")
+        print("2. 在OLED屏幕上显示：沪AAAAAA")
+        print("3. 等待10秒")
+        print("4. 逆时针旋转舵机90度")
+        print("5. 清空OLED屏幕")
+        
+    except Exception as e:
+        print(f"发送命令失败: {e}")
+    finally:
+        sock.close()
+
+if __name__ == "__main__":
+    print("Hi3861 简单客户端程序")
+    print("=" * 30)
+    send_command()
+    print("程序结束")
--- a/test_json.c
+++ b/test_json.c
@@ -0,0 +1,56 @@
+#include <stdio.h>
+#include <string.h>
+#include "json_parser.h"
+
+// 测试JSON解析功能
+void test_json_parsing() {
+    printf("=== JSON解析测试 ===\n");
+    
+    // 测试命令1：旋转+显示+清屏
+    char test1[] = "{\"cmd\":1,\"text\":\"Hello World\"}";
+    JsonCommand cmd1;
+    if (ParseJsonCommand(test1, &cmd1) == 0) {
+        printf("测试1成功: cmd=%d, text=%s\n", cmd1.cmd, cmd1.text);
+    } else {
+        printf("测试1失败\n");
+    }
+    
+    // 测试命令2：顺时针旋转
+    char test2[] = "{\"cmd\":2,\"text\":\"\"}";
+    JsonCommand cmd2;
+    if (ParseJsonCommand(test2, &cmd2) == 0) {
+        printf("测试2成功: cmd=%d, text=%s\n", cmd2.cmd, cmd2.text);
+    } else {
+        printf("测试2失败\n");
+    }
+    
+    // 测试命令3：逆时针旋转
+    char test3[] = "{\"cmd\":3,\"text\":\"ignored\"}";
+    JsonCommand cmd3;
+    if (ParseJsonCommand(test3, &cmd3) == 0) {
+        printf("测试3成功: cmd=%d, text=%s\n", cmd3.cmd, cmd3.text);
+    } else {
+        printf("测试3失败\n");
+    }
+    
+    // 测试IP消息创建
+    printf("\n=== IP消息创建测试 ===\n");
+    char ip_msg[128];
+    CreateIpMessage("192.168.1.100", ip_msg, sizeof(ip_msg));
+    printf("IP消息: %s\n", ip_msg);
+}
+
+// 测试舵机控制逻辑
+void test_servo_commands() {
+    printf("\n=== 舵机命令测试 ===\n");
+    
+    printf("命令1: 顺时针90°+显示+10秒后逆时针90°+清屏\n");
+    printf("命令2: 顺时针90°\n");
+    printf("命令3: 逆时针90°\n");
+}
+
+int main() {
+    test_json_parsing();
+    test_servo_commands();
+    return 0;
+}
--- a/udp_client_test.c
+++ b/udp_client_test.c
@@ -0,0 +1,242 @@
+#include <stdio.h>          // 标准输入输出
+#include <unistd.h>         // POSIX标准接口
+#include <errno.h>          // 错误码
+#include <string.h>         // 字符串处理(操作字符数组)
+
+#include "lwip/sockets.h"   // lwIP TCP/IP协议栈：Socket API
+#include "ohos_init.h"      // 用于初始化服务(services)和功能(features)
+#include "cmsis_os2.h"      // CMSIS-RTOS API V2
+#include "oled_ssd1306.h" 
+#include "json_parser.h"    // JSON解析器
+#include "wifi_connecter.h" // WiFi连接器
+
+
+
+extern int control_flag ;
+
+// 要发送的数据
+static char request[] = "connecting";
+
+// 要接收的数据
+char response[128] = "";
+
+// 全局变量存储解析后的命令
+JsonCommand g_current_command = {0};
+
+// 发送IP地址到服务器
+void SendIpToServer(const char *host, unsigned short port) {
+    char ip_buffer[32] = {0};
+    char message_buffer[128] = {0};
+    
+    // 获取本机IP地址
+    if (GetLocalIpAddress(ip_buffer, sizeof(ip_buffer)) != 0) {
+        printf("Failed to get local IP address\r\n");
+        return;
+    }
+    
+    // 创建IP消息
+    if (CreateIpMessage(message_buffer, sizeof(message_buffer), ip_buffer) != 0) {
+        printf("Failed to create IP message\r\n");
+        return;
+    }
+    
+    // 创建UDP socket
+    int sockfd = socket(AF_INET, SOCK_DGRAM, 0);
+    if (sockfd < 0) {
+        printf("Failed to create socket\r\n");
+        return;
+    }
+    
+    struct sockaddr_in toAddr = {0};
+    toAddr.sin_family = AF_INET;
+    toAddr.sin_port = htons(port);
+    
+    if (inet_pton(AF_INET, host, &toAddr.sin_addr) <= 0) {
+        printf("inet_pton failed!\r\n");
+        lwip_close(sockfd);
+        return;
+    }
+    
+    // 发送IP地址消息
+    ssize_t retval = sendto(sockfd, message_buffer, strlen(message_buffer), 0, 
+                           (struct sockaddr *)&toAddr, sizeof(toAddr));
+    
+    if (retval < 0) {
+        printf("Failed to send IP message!\r\n");
+    } else {
+        printf("IP message sent: %s\r\n", message_buffer);
+    }
+    
+    lwip_close(sockfd);
+}
+
+/// @brief UDP客户端测试函数
+/// @param host UDP服务端IP地址
+/// @param port UDP服务端端口
+void UdpClientTest(const char *host, unsigned short port)
+{
+    // 用于接收Socket API接口返回值
+    ssize_t retval = 0;
+    // 创建一个UDP Socket，返回值为文件描述符
+    int sockfd = socket(AF_INET, SOCK_DGRAM, 0);
+    if (sockfd < 0) {
+        printf("创建socket失败！\r\n");
+        return;
+    }
+    
+    // 用于设置服务端的地址信息
+    struct sockaddr_in toAddr = {0};
+    // 用于设置本地绑定的地址信息
+    struct sockaddr_in localAddr = {0};
+
+    // 使用IPv4协议
+    toAddr.sin_family = AF_INET;
+    localAddr.sin_family = AF_INET;
+
+    // 端口号，从主机字节序转为网络字节序
+    toAddr.sin_port = htons(port);
+    localAddr.sin_port = htons(port);  // 绑定到相同端口接收数据
+    localAddr.sin_addr.s_addr = INADDR_ANY;  // 绑定到所有可用的网络接口
+
+    // 将服务端IP地址从"点分十进制"字符串，转化为标准格式（32位整数）
+    if (inet_pton(AF_INET, host, &toAddr.sin_addr) <= 0)
+    {
+        // 转化失败
+        printf("inet_pton failed!\r\n");    // 输出日志
+        lwip_close(sockfd);
+        return;    
+    }
+
+    // 绑定本地端口，这样才能接收数据
+    printf("绑定本地端口 %d...\r\n", port);
+    if (bind(sockfd, (struct sockaddr *)&localAddr, sizeof(localAddr)) < 0) {
+        printf("绑定端口失败！错误: %d\r\n", errno);
+        lwip_close(sockfd);
+        return;
+    }
+    printf("端口绑定成功！\r\n");
+
+    // 发送设备IP地址到服务器
+    SendIpToServer(sockfd, &toAddr);
+
+    // 发送数据
+    // UDP socket是 "无连接的"，因此每次发送都必须先指定目标主机和端口，主机可以是多播地址
+    // 发送数据的时候，使用本地随机端口N
+    // 
+    // 参数：
+    // s：socket文件描述符
+    // dataptr：要发送的数据
+    // size：要发送的数据的长度，最大65332字节
+    // flags：消息传输标志位
+    // to：目标的地址信息
+    // tolen：目标的地址信息长度
+    // 
+    // 返回值：
+    // 发送的字节数，如果出错，返回-1
+    printf("发送连接消息到服务器...\r\n");
+    retval = sendto(sockfd, request, sizeof(request), 0, (struct sockaddr *)&toAddr, sizeof(toAddr));
+
+    // 检查接口返回值，小于0表示发送失败
+    if (retval < 0)
+    {
+        // 发送失败
+        printf("发送消息失败！错误: %d\r\n", errno);   // 输出日志
+        lwip_close(sockfd);
+        return;                
+    }
+
+    // 发送成功
+    // 输出日志
+    printf("发送UDP消息成功: {%s} %ld 字节\r\n", request, retval);
+    
+    // 显示等待接收状态
+    printf("开始监听UDP消息，等待来自 %s 的数据...\r\n", host);
+    
+    // 用于记录发送方的地址信息(IP地址和端口号)
+    struct sockaddr_in fromAddr = {0};
+
+    // 用于记录发送方的地址信息长度
+    socklen_t fromLen = sizeof(fromAddr);
+
+    // 在本地随机端口N上面接收数据
+    // UDP socket是 “无连接的”，因此每次接收时并不知道消息来自何处，通过fromAddr参数可以得到发送方的信息（主机、端口号）
+    // device\hisilicon\hispark_pegasus\sdk_liteos\third_party\lwip_sack\include\lwip\sockets.h -> lwip_recvfrom
+    //
+    // 参数：
+    // s：socket文件描述符
+    // buffer：接收数据的缓冲区的地址
+    // length：接收数据的缓冲区的长度
+    // flags：消息接收标志位
+    // address：发送方的地址信息
+    // address_len：发送方的地址信息长度
+    //
+    // 返回值：
+    // 接收的字节数，如果出错，返回-1
+    while (1)
+    {
+        // 清空接收缓冲区
+        memset(response, 0, sizeof(response));
+        
+        retval = lwip_recvfrom(sockfd, response, sizeof(response) - 1, 0, (struct sockaddr *)&fromAddr, &fromLen);
+
+        // 检查接口返回值，小于0表示接收失败
+        if (retval <= 0)
+        {
+            // 接收失败，或者收到0长度的数据(忽略掉)
+            printf("recvfrom failed or abort, %ld, %d!\r\n", retval, errno);    // 输出日志
+            continue;  // 继续接收，不要关闭socket                                                
+        }
+
+        // 接收成功
+        // 末尾添加字符串结束符'\0'，以便后续的字符串操作
+        response[retval] = '\0';
+
+        // 输出日志 - 显示所有收到的消息
+        printf("=== 收到UDP消息 ===\r\n");
+        printf("消息内容: {%s}\r\n", response);
+        printf("消息长度: %ld 字节\r\n", retval);
+        printf("发送方IP: %s\r\n", inet_ntoa(fromAddr.sin_addr));
+        printf("发送方端口: %d\r\n", ntohs(fromAddr.sin_port));
+        printf("==================\r\n");
+        
+        // 尝试解析JSON命令
+        JsonCommand temp_cmd = {0};
+        if (ParseJsonCommand(response, &temp_cmd) == 0) {
+            printf("JSON解析成功: cmd=%d, text=%s\r\n", temp_cmd.cmd, temp_cmd.text);
+            
+            // 保存解析的命令
+            g_current_command = temp_cmd;
+            
+            // 根据命令类型设置控制标志
+            if (temp_cmd.cmd >= 1 && temp_cmd.cmd <= 4) {
+                control_flag = temp_cmd.cmd;
+                printf("设置控制标志为: %d\r\n", control_flag);
+            } else {
+                printf("无效的命令类型: %d\r\n", temp_cmd.cmd);
+            }
+        } else {
+            printf("JSON解析失败，尝试旧格式命令\r\n");
+            
+            // 兼容旧的字符串命令格式
+            if(strlen(response) > 10) {
+                control_flag = 2;
+                g_current_command.cmd = 0;  // 标记为旧命令
+                printf("设置为复杂字符串命令，控制标志: %d\r\n", control_flag);
+            } else if(strcmp(response,"T:on") == 0) {
+                control_flag = 1;
+                g_current_command.cmd = 0;  // 标记为旧命令
+                printf("设置为开启命令，控制标志: %d\r\n", control_flag);
+            } else if(strcmp(response,"T:off") == 0) {
+                control_flag = 0;
+                g_current_command.cmd = 0;  // 标记为旧命令
+                printf("设置为关闭命令，控制标志: %d\r\n", control_flag);
+            } else {
+                printf("未识别的命令格式: %s\r\n", response);
+            }
+        }
+        
+        sleep(1);
+    }
+    // 关闭socket
+    lwip_close(sockfd);
+}
--- a/wifi_connecter.c
+++ b/wifi_connecter.c
@@ -0,0 +1,146 @@
+#include "cmsis_os2.h"      // CMSIS-RTOS API V2
+#include "wifi_device.h"    // Wi-Fi设备接口：station模式
+
+#include "lwip/netifapi.h"  // lwIP TCP/IP协议栈：网络接口API
+#include "lwip/api_shell.h" // lwIP TCP/IP协议栈：SHELL命令API
+
+static void PrintLinkedInfo(WifiLinkedInfo* info)
+{
+    if (!info) return;
+
+    static char macAddress[32] = {0};
+    unsigned char* mac = info->bssid;
+    snprintf(macAddress, sizeof(macAddress), "%02X:%02X:%02X:%02X:%02X:%02X",
+        mac[0], mac[1], mac[2], mac[3], mac[4], mac[5]);
+    printf("bssid: %s, rssi: %d, connState: %d, reason: %d, ssid: %s\r\n",
+        macAddress, info->rssi, info->connState, info->disconnectedReason, info->ssid);
+}
+
+static volatile int g_connected = 0;
+
+static void OnWifiConnectionChanged(int state, WifiLinkedInfo* info)
+{
+    if (!info) return;
+
+    printf("%s %d, state = %d, info = \r\n", __FUNCTION__, __LINE__, state);
+    PrintLinkedInfo(info);
+
+    if (state == WIFI_STATE_AVALIABLE) {
+        g_connected = 1;
+    } else {
+        g_connected = 0;
+    }
+}
+
+static void OnWifiScanStateChanged(int state, int size)
+{
+    printf("%s %d, state = %X, size = %d\r\n", __FUNCTION__, __LINE__, state, size);
+}
+
+static WifiEvent g_defaultWifiEventListener = {
+    .OnWifiConnectionChanged = OnWifiConnectionChanged,
+    .OnWifiScanStateChanged = OnWifiScanStateChanged
+};
+
+static struct netif* g_iface = NULL;
+
+err_t netifapi_set_hostname(struct netif *netif, char *hostname, u8_t namelen);
+
+int ConnectToHotspot(WifiDeviceConfig* apConfig)
+{
+    WifiErrorCode errCode;
+    int netId = -1;
+
+    errCode = RegisterWifiEvent(&g_defaultWifiEventListener);
+    printf("RegisterWifiEvent: %d\r\n", errCode);
+
+    errCode = EnableWifi();
+    printf("EnableWifi: %d\r\n", errCode);
+
+    errCode = AddDeviceConfig(apConfig, &netId);
+    printf("AddDeviceConfig: %d\r\n", errCode);
+    
+    g_connected = 0;
+    errCode = ConnectTo(netId);
+    printf("ConnectTo(%d): %d\r\n", netId, errCode);
+
+    while (!g_connected) { // wait until connect to AP
+        // printf("connecting\n");
+        osDelay(10);
+    }
+    printf("g_connected: %d\r\n", g_connected);
+
+    g_iface = netifapi_netif_find("wlan0");
+    if (g_iface) {
+        err_t ret = 0;
+        char* hostname = "hispark";
+        ret = netifapi_set_hostname(g_iface, hostname, strlen(hostname));
+        printf("netifapi_set_hostname: %d\r\n", ret);
+
+        ret = netifapi_dhcp_start(g_iface);
+        printf("netifapi_dhcp_start: %d\r\n", ret);
+
+        osDelay(100); // wait DHCP server give me IP 
+#if 0
+        ret = netifapi_netif_common(g_iface, dhcp_clients_info_show, NULL);
+        printf("netifapi_netif_common: %d\r\n", ret);
+#else
+        // 下面这种方式也可以打印 IP、网关、子网掩码信息
+        ip4_addr_t ip = {0};
+        ip4_addr_t netmask = {0};
+        ip4_addr_t gw = {0};
+        ret = netifapi_netif_get_addr(g_iface, &ip, &netmask, &gw);
+        if (ret == ERR_OK) {
+            printf("ip = %s\r\n", ip4addr_ntoa(&ip));
+            printf("netmask = %s\r\n", ip4addr_ntoa(&netmask));
+            printf("gw = %s\r\n", ip4addr_ntoa(&gw));
+        }
+        printf("netifapi_netif_get_addr: %d\r\n", ret);
+#endif
+    }
+    return netId;
+}
+
+void DisconnectWithHotspot(int netId)
+{
+    if (g_iface) {
+        err_t ret = netifapi_dhcp_stop(g_iface);
+        printf("netifapi_dhcp_stop: %d\r\n", ret);
+    }
+
+    WifiErrorCode errCode = Disconnect(); // disconnect with your AP
+    printf("Disconnect: %d\r\n", errCode);
+
+    errCode = UnRegisterWifiEvent(&g_defaultWifiEventListener);
+    printf("UnRegisterWifiEvent: %d\r\n", errCode);
+
+    RemoveDevice(netId); // remove AP config
+    printf("RemoveDevice: %d\r\n", errCode);
+
+    errCode = DisableWifi();
+    printf("DisableWifi: %d\r\n", errCode);
+}
+
+// 获取本机IP地址
+int GetLocalIpAddress(char* ip_buffer, int buffer_size)
+{
+    if (!ip_buffer || buffer_size < 16 || !g_iface) {
+        return -1;
+    }
+    
+    ip4_addr_t ip = {0};
+    ip4_addr_t netmask = {0};
+    ip4_addr_t gw = {0};
+    
+    err_t ret = netifapi_netif_get_addr(g_iface, &ip, &netmask, &gw);
+    if (ret == ERR_OK) {
+        const char* ip_str = ip4addr_ntoa(&ip);
+        if (ip_str && strlen(ip_str) < buffer_size) {
+            strcpy(ip_buffer, ip_str);
+            return 0;
+        }
+    }
+    
+    return -1;
+}
+
--- a/wifi_connecter.h
+++ b/wifi_connecter.h
@@ -0,0 +1,13 @@
+#ifndef WIFI_CONNECTER_H
+#define WIFI_CONNECTER_H
+
+#include "wifi_device.h"   // Wi-Fi设备接口：station模式
+
+int ConnectToHotspot(WifiDeviceConfig* apConfig);
+
+void DisconnectWithHotspot(int netId);
+
+// 获取本机IP地址
+int GetLocalIpAddress(char* ip_buffer, int buffer_size);
+
+#endif  // WIFI_CONNECTER_H
--- a/yolopart/.idea/.gitignore
+++ b/yolopart/.idea/.gitignore
@@ -1,8 +0,0 @@
-# 默认忽略的文件
-/shelf/
-/workspace.xml
-# 基于编辑器的 HTTP 客户端请求
-/httpRequests/
-# Datasource local storage ignored files
-/dataSources/
-/dataSources.local.xml
--- a/yolopart/.idea/inspectionProfiles/profiles_settings.xml
+++ b/yolopart/.idea/inspectionProfiles/profiles_settings.xml
@@ -1,6 +0,0 @@
-<component name="InspectionProjectProfileManager">
-  <settings>
-    <option name="USE_PROJECT_PROFILE" value="false" />
-    <version value="1.0" />
-  </settings>
-</component>
--- a/yolopart/.idea/misc.xml
+++ b/yolopart/.idea/misc.xml
@@ -1,7 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="Black">
-    <option name="sdkName" value="pytorh" />
-  </component>
-  <component name="ProjectRootManager" version="2" project-jdk-name="pytorh" project-jdk-type="Python SDK" />
-</project>
--- a/yolopart/.idea/modules.xml
+++ b/yolopart/.idea/modules.xml
@@ -1,8 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="ProjectModuleManager">
-    <modules>
-      <module fileurl="file://$PROJECT_DIR$/.idea/yolopart.iml" filepath="$PROJECT_DIR$/.idea/yolopart.iml" />
-    </modules>
-  </component>
-</project>
--- a/yolopart/.idea/vcs.xml
+++ b/yolopart/.idea/vcs.xml
@@ -1,6 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="VcsDirectoryMappings">
-    <mapping directory="$PROJECT_DIR$/.." vcs="Git" />
-  </component>
-</project>
--- a/yolopart/.idea/yolopart.iml
+++ b/yolopart/.idea/yolopart.iml
@@ -1,12 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<module type="PYTHON_MODULE" version="4">
-  <component name="NewModuleRootManager">
-    <content url="file://$MODULE_DIR$" />
-    <orderEntry type="jdk" jdkName="pytorh" jdkType="Python SDK" />
-    <orderEntry type="sourceFolder" forTests="false" />
-  </component>
-  <component name="PyDocumentationSettings">
-    <option name="format" value="PLAIN" />
-    <option name="myDocStringFormat" value="Plain" />
-  </component>
-</module>
--- a/yolopart/README.md
+++ b/yolopart/README.md
@@ -1,177 +0,0 @@
-# 车牌检测系统
-
-基于YOLO11s模型的实时车牌检测应用，支持摄像头和视频文件输入，具备GPU加速和车牌识别接口。
-
-## 功能特性
-
- ✅ **实时车牌检测**: 基于YOLO11s ONNX模型
- ✅ **GPU加速**: 支持CUDA GPU推理加速
- ✅ **多视频源**: 支持摄像头和视频文件切换
- ✅ **实时显示**: 显示检测框、置信度和实时FPS
- ✅ **图像切割**: 自动切割检测到的车牌区域
- ✅ **识别接口**: 预留车牌号识别接口，可接入OCR模型
- ✅ **友好界面**: 基于PyQt5的现代化用户界面
-
-## 系统要求
-
- Python 3.7+
- Windows/Linux/macOS
- 摄像头（可选）
- NVIDIA GPU（可选，用于加速）
-
-## 安装依赖
-
-```bash
-# 安装基础依赖
-pip install -r requirements.txt
-
-# 如果需要CPU版本的onnxruntime
-pip uninstall onnxruntime-gpu
-pip install onnxruntime
-
-# 可选：安装车牌识别依赖
-# PaddleOCR
-pip install paddlepaddle paddleocr
-
-# 或者 Tesseract
-pip install pytesseract
-```
-
-## 使用方法
-
-### 1. 准备模型文件
-
-确保项目根目录下有以下文件：
- `last.onnx`: YOLO11s车牌检测模型
- `video.mp4`: 测试视频文件（可选）
-
-### 2. 运行应用
-
-```bash
-python main.py
-```
-
-### 3. 界面操作
-
- **开始检测**: 点击"开始检测"按钮启动实时检测
- **切换视频源**: 勾选/取消"使用摄像头"切换视频源
- **启用检测**: 勾选/取消"启用检测"开关检测功能
- **查看结果**: 右侧面板显示检测信息和车牌识别结果
-
-## 项目结构
-
-```
-yolopart/
-├── main.py                 # 主程序入口
-├── requirements.txt        # 依赖包列表
-├── README.md              # 项目说明
-├── last.onnx              # YOLO11s模型文件
-├── video.mp4              # 测试视频文件
-├── ui/                    # 用户界面模块
-│   ├── __init__.py
-│   ├── main_window.py     # 主窗口
-│   └── video_widget.py    # 视频显示组件
-├── models/                # 模型模块
-│   ├── __init__.py
-│   ├── yolo_detector.py   # YOLO检测器
-│   └── plate_recognizer.py # 车牌识别接口
-└── utils/                 # 工具模块
-    ├── __init__.py
-    └── video_capture.py   # 视频捕获管理
-```
-
-## 核心功能说明
-
-### YOLO检测器 (`models/yolo_detector.py`)
-
- 支持ONNX格式的YOLO11s模型
- 自动GPU/CPU推理选择
- 640x640输入尺寸
- NMS后处理
- 检测框绘制和车牌切割
-
-### 视频捕获 (`utils/video_capture.py`)
-
- 摄像头自动检测和配置
- 视频文件循环播放
- 实时FPS计算和显示
- 线程安全的帧获取
-
-### 车牌识别接口 (`models/plate_recognizer.py`)
-
-提供了多种识别器实现：
- `MockPlateRecognizer`: 模拟识别器（用于测试）
- `PaddleOCRRecognizer`: PaddleOCR识别器
- `TesseractRecognizer`: Tesseract识别器
-
-可通过`PlateRecognizerManager`轻松切换不同的识别引擎。
-
-## 配置说明
-
-### 检测参数调整
-
-在`models/yolo_detector.py`中可以调整：
- `conf_threshold`: 置信度阈值（默认0.5）
- `nms_threshold`: NMS阈值（默认0.4）
- `input_size`: 输入尺寸（默认640x640）
-
-### 视频参数调整
-
-在`utils/video_capture.py`中可以调整：
- 摄像头分辨率和帧率
- FPS计算窗口大小
- 视频文件路径
-
-## 扩展开发
-
-### 添加新的车牌识别器
-
-1. 继承`PlateRecognizerInterface`基类
-2. 实现`recognize`和`batch_recognize`方法
-3. 在`PlateRecognizerManager`中注册新识别器
-
-### 添加新功能
-
- 检测结果保存
- 车牌数据库管理
- 网络接口API
- 多摄像头支持
-
-## 故障排除
-
-### 常见问题
-
-1. **模型加载失败**
-   - 检查`last.onnx`文件是否存在
-   - 确认onnxruntime版本兼容性
-
-2. **摄像头无法打开**
-   - 检查摄像头是否被其他程序占用
-   - 尝试不同的摄像头索引
-
-3. **GPU加速不生效**
-   - 确认安装了`onnxruntime-gpu`
-   - 检查CUDA环境配置
-
-4. **车牌识别失败**
-   - 检查OCR依赖是否正确安装
-   - 尝试切换不同的识别器
-
-### 性能优化
-
- 使用GPU加速推理
- 调整检测阈值减少误检
- 优化图像预处理流程
- 使用多线程处理
-
-## 许可证
-
-本项目仅供学习和研究使用。
-
-## 更新日志
-
-### v1.0.0
- 初始版本发布
- 支持YOLO11s车牌检测
- 实现基础UI界面
- 预留车牌识别接口
--- a/yolopart/main.py
+++ b/yolopart/main.py
@@ -1,34 +0,0 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-"""
-车牌检测系统主程序
-基于YOLO11s模型的实时车牌检测应用
-"""
-
-import sys
-import os
-from PyQt5.QtWidgets import QApplication
-from PyQt5.QtCore import Qt
-from ui.main_window import MainWindow
-
-def main():
-    """主函数"""
-    # 创建QApplication实例
-    app = QApplication(sys.argv)
-    app.setAttribute(Qt.AA_EnableHighDpiScaling, True)
-    app.setAttribute(Qt.AA_UseHighDpiPixmaps, True)
-    
-    # 设置应用信息
-    app.setApplicationName("车牌检测系统")
-    app.setApplicationVersion("1.0.0")
-    app.setOrganizationName("License Plate Detection")
-    
-    # 创建主窗口
-    main_window = MainWindow()
-    main_window.show()
-    
-    # 运行应用
-    sys.exit(app.exec_())
-
-if __name__ == "__main__":
-    main()
--- a/yolopart/models/init.py
+++ b/yolopart/models/init.py
@@ -1 +0,0 @@
-# 模型模块初始化文件
--- a/yolopart/models/pycache/init.cpython-38.pyc
+++ b/yolopart/models/pycache/init.cpython-38.pyc
--- a/yolopart/models/pycache/plate_recognizer.cpython-38.pyc
+++ b/yolopart/models/pycache/plate_recognizer.cpython-38.pyc
--- a/yolopart/models/pycache/yolo_detector.cpython-38.pyc
+++ b/yolopart/models/pycache/yolo_detector.cpython-38.pyc
--- a/yolopart/models/plate_recognizer.py
+++ b/yolopart/models/plate_recognizer.py
@@ -1,490 +0,0 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-"""
-车牌识别接口模块
-预留接口，可接入各种OCR模型进行车牌号识别
-"""
-
-import cv2
-import numpy as np
-from typing import List, Optional, Dict, Any
-from abc import ABC, abstractmethod
-
-class PlateRecognizerInterface(ABC):
-    """车牌识别接口基类"""
-    
-    @abstractmethod
-    def recognize(self, plate_image: np.ndarray) -> Dict[str, Any]:
-        """
-        识别车牌号
-        
-        Args:
-            plate_image: 车牌图像 (BGR格式)
-            
-        Returns:
-            识别结果字典，包含:
-            {
-                'text': str,           # 识别的车牌号
-                'confidence': float,   # 置信度 (0-1)
-                'success': bool        # 是否识别成功
-            }
-        """
-        pass
-        
-    @abstractmethod
-    def batch_recognize(self, plate_images: List[np.ndarray]) -> List[Dict[str, Any]]:
-        """
-        批量识别车牌号
-        
-        Args:
-            plate_images: 车牌图像列表
-            
-        Returns:
-            识别结果列表
-        """
-        pass
-
-class MockPlateRecognizer(PlateRecognizerInterface):
-    """模拟车牌识别器（用于测试）"""
-    
-    def __init__(self):
-        self.mock_plates = [
-            "京A12345", "沪B67890", "粤C11111", "川D22222", 
-            "鲁E33333", "苏F44444", "浙G55555", "闽H66666"
-        ]
-        self.call_count = 0
-        
-    def recognize(self, plate_image: np.ndarray) -> Dict[str, Any]:
-        """
-        模拟识别单个车牌
-        
-        Args:
-            plate_image: 车牌图像
-            
-        Returns:
-            模拟识别结果
-        """
-        # 模拟处理时间
-        import time
-        time.sleep(0.01)  # 10ms模拟处理时间
-        
-        # 简单的图像质量检查
-        if plate_image is None or plate_image.size == 0:
-            return {
-                'text': '',
-                'confidence': 0.0,
-                'success': False
-            }
-            
-        # 检查图像尺寸
-        height, width = plate_image.shape[:2]
-        if width < 50 or height < 20:
-            return {
-                'text': '',
-                'confidence': 0.3,
-                'success': False
-            }
-            
-        # 模拟识别结果
-        plate_text = self.mock_plates[self.call_count % len(self.mock_plates)]
-        confidence = 0.85 + (self.call_count % 10) * 0.01  # 0.85-0.94
-        
-        self.call_count += 1
-        
-        return {
-            'text': plate_text,
-            'confidence': confidence,
-            'success': True
-        }
-        
-    def batch_recognize(self, plate_images: List[np.ndarray]) -> List[Dict[str, Any]]:
-        """
-        批量识别车牌
-        
-        Args:
-            plate_images: 车牌图像列表
-            
-        Returns:
-            识别结果列表
-        """
-        results = []
-        for plate_image in plate_images:
-            result = self.recognize(plate_image)
-            results.append(result)
-        return results
-
-class PaddleOCRRecognizer(PlateRecognizerInterface):
-    """PaddleOCR车牌识别器（示例实现）"""
-    
-    def __init__(self, use_gpu: bool = True):
-        """
-        初始化PaddleOCR识别器
-        
-        Args:
-            use_gpu: 是否使用GPU
-        """
-        self.use_gpu = use_gpu
-        self.ocr = None
-        self._init_ocr()
-        
-    def _init_ocr(self):
-        """初始化OCR模型"""
-        try:
-            # 这里可以接入PaddleOCR
-            # from paddleocr import PaddleOCR
-            # self.ocr = PaddleOCR(use_angle_cls=True, lang='ch', use_gpu=self.use_gpu)
-            print("PaddleOCR初始化完成（示例代码，需要安装PaddleOCR）")
-        except ImportError:
-            print("PaddleOCR未安装，使用模拟识别器")
-            self.ocr = None
-            
-    def recognize(self, plate_image: np.ndarray) -> Dict[str, Any]:
-        """
-        使用PaddleOCR识别车牌
-        
-        Args:
-            plate_image: 车牌图像
-            
-        Returns:
-            识别结果
-        """
-        if self.ocr is None:
-            # 回退到模拟识别
-            mock_recognizer = MockPlateRecognizer()
-            return mock_recognizer.recognize(plate_image)
-            
-        try:
-            # 使用PaddleOCR进行识别
-            results = self.ocr.ocr(plate_image, cls=True)
-            
-            if results and len(results) > 0 and results[0]:
-                # 提取文本和置信度
-                text_results = []
-                for line in results[0]:
-                    text = line[1][0]
-                    confidence = line[1][1]
-                    text_results.append((text, confidence))
-                    
-                # 选择置信度最高的结果
-                if text_results:
-                    best_result = max(text_results, key=lambda x: x[1])
-                    return {
-                        'text': best_result[0],
-                        'confidence': best_result[1],
-                        'success': True
-                    }
-                    
-        except Exception as e:
-            print(f"PaddleOCR识别失败: {e}")
-            
-        return {
-            'text': '',
-            'confidence': 0.0,
-            'success': False
-        }
-        
-    def batch_recognize(self, plate_images: List[np.ndarray]) -> List[Dict[str, Any]]:
-        """
-        批量识别
-        
-        Args:
-            plate_images: 车牌图像列表
-            
-        Returns:
-            识别结果列表
-        """
-        results = []
-        for plate_image in plate_images:
-            result = self.recognize(plate_image)
-            results.append(result)
-        return results
-
-class TesseractRecognizer(PlateRecognizerInterface):
-    """Tesseract车牌识别器（示例实现）"""
-    
-    def __init__(self, lang: str = 'chi_sim+eng'):
-        """
-        初始化Tesseract识别器
-        
-        Args:
-            lang: 识别语言
-        """
-        self.lang = lang
-        self.tesseract_available = self._check_tesseract()
-        
-    def _check_tesseract(self) -> bool:
-        """检查Tesseract是否可用"""
-        try:
-            import pytesseract
-            return True
-        except ImportError:
-            print("pytesseract未安装，使用模拟识别器")
-            return False
-            
-    def recognize(self, plate_image: np.ndarray) -> Dict[str, Any]:
-        """
-        使用Tesseract识别车牌
-        
-        Args:
-            plate_image: 车牌图像
-            
-        Returns:
-            识别结果
-        """
-        if not self.tesseract_available:
-            # 回退到模拟识别
-            mock_recognizer = MockPlateRecognizer()
-            return mock_recognizer.recognize(plate_image)
-            
-        try:
-            import pytesseract
-            
-            # 图像预处理
-            processed_image = self._preprocess_image(plate_image)
-            
-            # 使用Tesseract识别
-            text = pytesseract.image_to_string(
-                processed_image, 
-                lang=self.lang,
-                config='--psm 8 --oem 3 -c tessedit_char_whitelist=0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ京沪粤川鲁苏浙闽'
-            )
-            
-            # 清理识别结果
-            text = text.strip().replace(' ', '').replace('\n', '')
-            
-            if text and len(text) >= 5:  # 车牌号至少5位
-                return {
-                    'text': text,
-                    'confidence': 0.8,  # Tesseract不直接提供置信度
-                    'success': True
-                }
-                
-        except Exception as e:
-            print(f"Tesseract识别失败: {e}")
-            
-        return {
-            'text': '',
-            'confidence': 0.0,
-            'success': False
-        }
-        
-    def _preprocess_image(self, image: np.ndarray) -> np.ndarray:
-        """图像预处理"""
-        # 转换为灰度图
-        if len(image.shape) == 3:
-            gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
-        else:
-            gray = image
-            
-        # 调整尺寸
-        height, width = gray.shape
-        if width < 200:
-            scale = 200 / width
-            new_width = int(width * scale)
-            new_height = int(height * scale)
-            gray = cv2.resize(gray, (new_width, new_height))
-            
-        # 二值化
-        _, binary = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
-        
-        return binary
-        
-    def batch_recognize(self, plate_images: List[np.ndarray]) -> List[Dict[str, Any]]:
-        """
-        批量识别
-        
-        Args:
-            plate_images: 车牌图像列表
-            
-        Returns:
-            识别结果列表
-        """
-        results = []
-        for plate_image in plate_images:
-            result = self.recognize(plate_image)
-            results.append(result)
-        return results
-
-class PlateRecognizerManager:
-    """车牌识别管理器"""
-    
-    def __init__(self, recognizer_type: str = 'mock'):
-        """
-        初始化识别管理器
-        
-        Args:
-            recognizer_type: 识别器类型 ('mock', 'paddleocr', 'tesseract')
-        """
-        self.recognizer_type = recognizer_type
-        self.recognizer = self._create_recognizer(recognizer_type)
-        
-    def _create_recognizer(self, recognizer_type: str) -> PlateRecognizerInterface:
-        """创建识别器"""
-        if recognizer_type == 'mock':
-            return MockPlateRecognizer()
-        elif recognizer_type == 'paddleocr':
-            return PaddleOCRRecognizer()
-        elif recognizer_type == 'tesseract':
-            return TesseractRecognizer()
-        else:
-            print(f"未知的识别器类型: {recognizer_type}，使用模拟识别器")
-            return MockPlateRecognizer()
-            
-    def recognize_plates(self, plate_images: List[np.ndarray]) -> List[Dict[str, Any]]:
-        """
-        识别车牌列表
-        
-        Args:
-            plate_images: 车牌图像列表
-            
-        Returns:
-            识别结果列表
-        """
-        if not plate_images:
-            return []
-            
-        return self.recognizer.batch_recognize(plate_images)
-        
-    def switch_recognizer(self, recognizer_type: str):
-        """
-        切换识别器
-        
-        Args:
-            recognizer_type: 新的识别器类型
-        """
-        self.recognizer_type = recognizer_type
-        self.recognizer = self._create_recognizer(recognizer_type)
-        print(f"已切换到识别器: {recognizer_type}")
-        
-    def get_recognizer_info(self) -> Dict[str, Any]:
-        """
-        获取识别器信息
-        
-        Returns:
-            识别器信息
-        """
-        return {
-            'type': self.recognizer_type,
-            'class': self.recognizer.__class__.__name__
-        }
-    
-    def preprocess_blue_plate(self, plate_image: np.ndarray, original_image: np.ndarray, bbox: List[int]) -> np.ndarray:
-        """
-        蓝色车牌预处理：倾斜矫正
-        
-        Args:
-            plate_image: 切割后的车牌图像
-            original_image: 原始图像
-            bbox: 边界框坐标 [x1, y1, x2, y2]
-            
-        Returns:
-            矫正后的车牌图像
-        """
-        try:
-            # 从原图中提取车牌区域
-            x1, y1, x2, y2 = bbox
-            roi = original_image[y1:y2, x1:x2]
-            
-            # 获取蓝色车牌的二值图像
-            bin_img = self._get_blue_img_bin(roi)
-            
-            # 倾斜矫正
-            corrected_img = self._deskew_plate(bin_img, roi)
-            
-            return corrected_img
-        except Exception as e:
-            print(f"蓝色车牌预处理失败: {e}")
-            return plate_image
-    
-    def _get_blue_img_bin(self, img: np.ndarray) -> np.ndarray:
-        """
-        获取蓝色车牌的二值图像
-        """
-        # 掩膜：BGR通道，若像素B分量在 100~255 且 G分量在 0~190 且 R分量在 0~140 置255（白色），否则置0（黑色）
-        mask_bgr = cv2.inRange(img, (100, 0, 0), (255, 190, 140))
-        
-        # 转换成 HSV 颜色空间
-        img_hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
-        h, s, v = cv2.split(img_hsv)  # 分离通道 色调(H)，饱和度(S)，明度(V)
-        mask_s = cv2.inRange(s, 80, 255)  # 取饱和度通道进行掩膜得到二值图像
-        
-        # 与操作，两个二值图像都为白色才保留，否则置黑
-        rgbs = mask_bgr & mask_s
-        
-        # 核的横向分量大，使车牌数字尽量连在一起
-        kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (15, 3))
-        img_rgbs_dilate = cv2.dilate(rgbs, kernel, 3)  # 膨胀，减小车牌空洞
-        
-        return img_rgbs_dilate
-    
-    def _order_points(self, pts: np.ndarray) -> np.ndarray:
-        """
-        将四点按 左上、右上、右下、左下 排序
-        """
-        rect = np.zeros((4, 2), dtype="float32")
-        s = pts.sum(axis=1)
-        rect[0] = pts[np.argmin(s)]  # 左上
-        rect[2] = pts[np.argmax(s)]  # 右下
-        
-        diff = np.diff(pts, axis=1)
-        rect[1] = pts[np.argmin(diff)]  # 右上
-        rect[3] = pts[np.argmax(diff)]  # 左下
-        
-        return rect
-    
-    def _deskew_plate(self, bin_img: np.ndarray, original_roi: np.ndarray) -> np.ndarray:
-        """
-        车牌倾斜矫正
-        
-        Args:
-            bin_img: 二值图像
-            original_roi: 原始ROI区域
-            
-        Returns:
-            矫正后的原始图像（未被掩模，但经过旋转和切割）
-        """
-        try:
-            # 找最大轮廓
-            cnts, _ = cv2.findContours(bin_img, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
-            if not cnts:
-                return original_roi
-                
-            c = max(cnts, key=cv2.contourArea)
-            
-            # 最小外接矩形
-            rect = cv2.minAreaRect(c)
-            box = cv2.boxPoints(rect)
-            box = np.array(box, dtype="float32")
-            
-            # 排序四个点
-            pts_src = self._order_points(box)
-            
-            # 计算目标矩形宽高
-            (tl, tr, br, bl) = pts_src
-            widthA = np.linalg.norm(br - bl)
-            widthB = np.linalg.norm(tr - tl)
-            maxWidth = int(max(widthA, widthB))
-            
-            heightA = np.linalg.norm(tr - br)
-            heightB = np.linalg.norm(tl - bl)
-            maxHeight = int(max(heightA, heightB))
-            
-            # 确保尺寸合理
-            if maxWidth < 10 or maxHeight < 10:
-                return original_roi
-            
-            # 目标点集合
-            pts_dst = np.array([
-                [0, 0],
-                [maxWidth - 1, 0],
-                [maxWidth - 1, maxHeight - 1],
-                [0, maxHeight - 1]], dtype="float32")
-            
-            # 透视变换
-            M = cv2.getPerspectiveTransform(pts_src, pts_dst)
-            warped = cv2.warpPerspective(original_roi, M, (maxWidth, maxHeight))
-            
-            return warped
-        except Exception as e:
-            print(f"车牌矫正失败: {e}")
-            return original_roi
--- a/yolopart/models/yolo_detector.py
+++ b/yolopart/models/yolo_detector.py
@@ -1,368 +0,0 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-"""
-YOLO车牌检测器
-基于ONNX Runtime的YOLO11s模型推理
-"""
-
-import cv2
-import numpy as np
-import onnxruntime as ort
-import time
-from typing import List, Tuple, Optional
-
-class YOLODetector:
-    """YOLO车牌检测器"""
-    
-    def __init__(self, model_path: str, conf_threshold: float = 0.25, nms_threshold: float = 0.4):
-        """
-        初始化YOLO检测器
-        
-        Args:
-            model_path: ONNX模型文件路径
-            conf_threshold: 置信度阈值
-            nms_threshold: NMS阈值
-        """
-        self.model_path = model_path
-        self.conf_threshold = conf_threshold
-        self.nms_threshold = nms_threshold
-        self.input_size = (640, 640)  # YOLO11s输入尺寸
-        self.use_gpu = False
-        
-        # 初始化ONNX Runtime会话
-        self._init_session()
-        
-        # 获取模型输入输出信息
-        self.input_name = self.session.get_inputs()[0].name
-        self.output_names = [output.name for output in self.session.get_outputs()]
-        
-        print(f"YOLO检测器初始化完成")
-        print(f"模型路径: {model_path}")
-        print(f"输入尺寸: {self.input_size}")
-        print(f"GPU加速: {self.use_gpu}")
-        
-    def _init_session(self):
-        """初始化ONNX Runtime会话"""
-        # 获取可用的providers
-        available_providers = ort.get_available_providers()
-        print(f"可用的执行提供者: {available_providers}")
-        
-        # 优先使用GPU，如果可用的话
-        providers = []
-        if 'CUDAExecutionProvider' in available_providers:
-            providers.append('CUDAExecutionProvider')
-            self.use_gpu = True
-            print("检测到CUDA支持，将使用GPU加速")
-        elif 'TensorrtExecutionProvider' in available_providers:
-            providers.append('TensorrtExecutionProvider')
-            self.use_gpu = True
-            print("检测到TensorRT支持，将使用GPU加速")
-        else:
-            self.use_gpu = False
-            print("未检测到GPU支持，将使用CPU")
-            
-        # 添加CPU作为备选
-        providers.append('CPUExecutionProvider')
-        
-        print(f"使用的执行提供者: {providers}")
-            
-        # 创建会话
-        session_options = ort.SessionOptions()
-        session_options.graph_optimization_level = ort.GraphOptimizationLevel.ORT_ENABLE_ALL
-        
-        try:
-            self.session = ort.InferenceSession(
-                self.model_path, 
-                sess_options=session_options,
-                providers=providers
-            )
-            
-            # 检查实际使用的provider
-            actual_providers = self.session.get_providers()
-            print(f"实际使用的执行提供者: {actual_providers}")
-            
-            if 'CUDAExecutionProvider' in actual_providers or 'TensorrtExecutionProvider' in actual_providers:
-                self.use_gpu = True
-                print("✅ GPU加速已启用")
-            else:
-                self.use_gpu = False
-                print("⚠️ 使用CPU执行")
-                
-        except Exception as e:
-            print(f"模型加载失败: {e}")
-            raise
-            
-    def preprocess(self, image: np.ndarray) -> Tuple[np.ndarray, float, float]:
-        """
-        图像预处理
-        
-        Args:
-            image: 输入图像 (BGR格式)
-            
-        Returns:
-            preprocessed_image: 预处理后的图像
-            scale_x: X轴缩放比例
-            scale_y: Y轴缩放比例
-        """
-        original_height, original_width = image.shape[:2]
-        target_width, target_height = self.input_size
-        
-        # 计算缩放比例
-        scale_x = target_width / original_width
-        scale_y = target_height / original_height
-        
-        # 等比例缩放
-        scale = min(scale_x, scale_y)
-        new_width = int(original_width * scale)
-        new_height = int(original_height * scale)
-        
-        # 缩放图像
-        resized_image = cv2.resize(image, (new_width, new_height))
-        
-        # 创建目标尺寸的图像并居中放置
-        padded_image = np.full((target_height, target_width, 3), 114, dtype=np.uint8)
-        
-        # 计算填充位置
-        start_x = (target_width - new_width) // 2
-        start_y = (target_height - new_height) // 2
-        
-        padded_image[start_y:start_y + new_height, start_x:start_x + new_width] = resized_image
-        
-        # 转换为RGB并归一化
-        rgb_image = cv2.cvtColor(padded_image, cv2.COLOR_BGR2RGB)
-        normalized_image = rgb_image.astype(np.float32) / 255.0
-        
-        # 转换为NCHW格式
-        input_tensor = np.transpose(normalized_image, (2, 0, 1))
-        input_tensor = np.expand_dims(input_tensor, axis=0)
-        
-        return input_tensor, scale, scale
-        
-    def postprocess(self, outputs: List[np.ndarray], scale_x: float, scale_y: float, 
-                   original_shape: Tuple[int, int]) -> List[dict]:
-        """
-        后处理检测结果
-        
-        Args:
-            outputs: 模型输出
-            scale_x: X轴缩放比例
-            scale_y: Y轴缩放比例
-            original_shape: 原始图像尺寸 (height, width)
-            
-        Returns:
-            检测结果列表
-        """
-        detections = []
-        
-        if len(outputs) == 0:
-            return detections
-            
-        # 获取输出张量
-        output = outputs[0]
-        
-        # YOLO11输出格式: [batch, 6, 8400] -> [batch, 8400, 6]
-        if len(output.shape) == 3:
-            output = output.transpose(0, 2, 1)
-            
-        # 处理每个检测结果
-        for detection in output[0]:  # 取第一个batch
-            # 前4个值是边界框坐标，后2个是类别概率
-            x_center, y_center, width, height = detection[:4]
-            class_scores = detection[4:]  # 类别概率 [蓝牌概率, 绿牌概率]
-            
-            # 获取最高概率的类别
-            class_id = np.argmax(class_scores)
-            confidence = class_scores[class_id]  # 使用类别概率作为置信度
-            
-            # 过滤低置信度检测
-            if confidence < self.conf_threshold:
-                continue
-                
-            # 转换坐标到原始图像尺寸
-            original_height, original_width = original_shape
-            
-            # 计算实际缩放比例和偏移
-            scale = min(self.input_size[0] / original_width, self.input_size[1] / original_height)
-            pad_x = (self.input_size[0] - original_width * scale) / 2
-            pad_y = (self.input_size[1] - original_height * scale) / 2
-            
-            # 转换坐标
-            x_center = (x_center - pad_x) / scale
-            y_center = (y_center - pad_y) / scale
-            width = width / scale
-            height = height / scale
-            
-            # 计算边界框
-            x1 = int(x_center - width / 2)
-            y1 = int(y_center - height / 2)
-            x2 = int(x_center + width / 2)
-            y2 = int(y_center + height / 2)
-            
-            # 确保坐标在图像范围内
-            x1 = max(0, min(x1, original_width - 1))
-            y1 = max(0, min(y1, original_height - 1))
-            x2 = max(0, min(x2, original_width - 1))
-            y2 = max(0, min(y2, original_height - 1))
-            
-            # 定义类别名称
-            class_names = ['blue_plate', 'green_plate']  # 0: 蓝牌, 1: 绿牌
-            class_name = class_names[class_id] if class_id < len(class_names) else 'unknown'
-            
-            detections.append({
-                'bbox': [x1, y1, x2, y2],
-                'confidence': float(confidence),
-                'class_id': int(class_id),
-                'class_name': class_name
-            })
-            
-        # 应用NMS
-        if detections:
-            detections = self._apply_nms(detections)
-            
-        return detections
-        
-    def _apply_nms(self, detections: List[dict]) -> List[dict]:
-        """
-        应用非极大值抑制
-        
-        Args:
-            detections: 检测结果列表
-            
-        Returns:
-            NMS后的检测结果
-        """
-        if len(detections) == 0:
-            return detections
-            
-        # 提取边界框和置信度
-        boxes = np.array([det['bbox'] for det in detections])
-        scores = np.array([det['confidence'] for det in detections])
-        
-        # 应用NMS
-        indices = cv2.dnn.NMSBoxes(
-            boxes.tolist(), 
-            scores.tolist(), 
-            self.conf_threshold, 
-            self.nms_threshold
-        )
-        
-        # 返回保留的检测结果
-        if len(indices) > 0:
-            indices = indices.flatten()
-            return [detections[i] for i in indices]
-        else:
-            return []
-            
-    def detect(self, image: np.ndarray) -> List[dict]:
-        """
-        检测车牌
-        
-        Args:
-            image: 输入图像 (BGR格式)
-            
-        Returns:
-            检测结果列表
-        """
-        try:
-            # 预处理
-            input_tensor, scale_x, scale_y = self.preprocess(image)
-            
-            # 推理
-            outputs = self.session.run(self.output_names, {self.input_name: input_tensor})
-            
-            # 调试输出
-            print(f"模型输出数量: {len(outputs)}")
-            for i, output in enumerate(outputs):
-                print(f"输出 {i} 形状: {output.shape}")
-                print(f"输出 {i} 数据范围: [{output.min():.4f}, {output.max():.4f}]")
-            
-            # 后处理
-            detections = self.postprocess(outputs, scale_x, scale_y, image.shape[:2])
-            print(f"检测到的目标数量: {len(detections)}")
-            for i, det in enumerate(detections):
-                print(f"检测 {i}: 类别={det['class_name']}, 置信度={det['confidence']:.3f}")
-            
-            return detections
-            
-        except Exception as e:
-            print(f"检测过程出错: {e}")
-            return []
-            
-    def draw_detections(self, image: np.ndarray, detections: List[dict]) -> np.ndarray:
-        """
-        在图像上绘制检测结果
-        
-        Args:
-            image: 输入图像
-            detections: 检测结果列表
-            
-        Returns:
-            绘制了检测框的图像
-        """
-        result_image = image.copy()
-        
-        for detection in detections:
-            bbox = detection['bbox']
-            confidence = detection['confidence']
-            class_id = detection['class_id']
-            class_name = detection['class_name']
-            
-            x1, y1, x2, y2 = bbox
-            
-            # 根据车牌类型选择颜色
-            if class_id == 0:  # 蓝牌
-                color = (255, 0, 0)  # 蓝色 (BGR格式)
-                plate_type = "Blue Plate"
-            elif class_id == 1:  # 绿牌
-                color = (0, 255, 0)  # 绿色 (BGR格式)
-                plate_type = "Green Plate"
-            else:
-                color = (0, 255, 255)  # 黄色 (BGR格式)
-                plate_type = "Unknown"
-            
-            # 绘制边界框
-            cv2.rectangle(result_image, (x1, y1), (x2, y2), color, 2)
-            
-            # 绘制置信度标签
-            label = f"{plate_type}: {confidence:.2f}"
-            label_size = cv2.getTextSize(label, cv2.FONT_HERSHEY_SIMPLEX, 0.6, 2)[0]
-            
-            # 绘制标签背景
-            cv2.rectangle(result_image, 
-                         (x1, y1 - label_size[1] - 10), 
-                         (x1 + label_size[0], y1), 
-                         color, -1)
-            
-            # 绘制标签文字
-            cv2.putText(result_image, label, 
-                       (x1, y1 - 5), 
-                       cv2.FONT_HERSHEY_SIMPLEX, 0.6, 
-                       (255, 255, 255), 2)
-                       
-        return result_image
-        
-    def crop_plates(self, image: np.ndarray, detections: List[dict]) -> List[np.ndarray]:
-        """
-        切割车牌图像
-        
-        Args:
-            image: 原始图像
-            detections: 检测结果列表
-            
-        Returns:
-            切割后的车牌图像列表
-        """
-        plate_images = []
-        
-        for detection in detections:
-            bbox = detection['bbox']
-            x1, y1, x2, y2 = bbox
-            
-            # 确保坐标有效
-            if x2 > x1 and y2 > y1:
-                # 切割车牌区域
-                plate_image = image[y1:y2, x1:x2]
-                if plate_image.size > 0:
-                    plate_images.append(plate_image)
-                    
-        return plate_images
--- a/yolopart/requirements.txt
+++ b/yolopart/requirements.txt
@@ -1,17 +0,0 @@
-# 车牌检测系统依赖包
-
-# 核心依赖
-PyQt5>=5.15.0
-opencv-python>=4.5.0
-onnxruntime-gpu>=1.12.0
-numpy>=1.21.0
-
-# 可选依赖（车牌识别）
-# paddlepaddle>=2.4.0
-# paddleocr>=2.6.0
-# pytesseract>=0.3.10
-
-# 开发依赖
-# pytest>=7.0.0
-# black>=22.0.0
-# flake8>=4.0.0
--- a/yolopart/ui/init.py
+++ b/yolopart/ui/init.py
@@ -1 +0,0 @@
-# UI模块初始化文件
--- a/yolopart/ui/pycache/init.cpython-38.pyc
+++ b/yolopart/ui/pycache/init.cpython-38.pyc
--- a/yolopart/ui/pycache/main_window.cpython-38.pyc
+++ b/yolopart/ui/pycache/main_window.cpython-38.pyc
--- a/yolopart/ui/pycache/video_widget.cpython-38.pyc
+++ b/yolopart/ui/pycache/video_widget.cpython-38.pyc
--- a/yolopart/ui/main_window.py
+++ b/yolopart/ui/main_window.py
@@ -1,348 +0,0 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-"""
-主界面窗口
-包含视频显示区域、控制按钮和车牌号显示区域
-"""
-
-import sys
-import os
-from PyQt5.QtWidgets import (
-    QMainWindow, QWidget, QVBoxLayout, QHBoxLayout, 
-    QLabel, QPushButton, QFrame, QTextEdit, QGroupBox,
-    QCheckBox, QSpinBox, QSlider, QGridLayout
-)
-from PyQt5.QtCore import Qt, QTimer, pyqtSignal
-from PyQt5.QtGui import QFont, QPixmap, QPalette, QImage
-
-from .video_widget import VideoWidget
-from utils.video_capture import VideoCapture
-from models.yolo_detector import YOLODetector
-from models.plate_recognizer import PlateRecognizerManager
-
-class MainWindow(QMainWindow):
-    """主窗口类"""
-    
-    def __init__(self):
-        super().__init__()
-        self.video_capture = None
-        self.yolo_detector = None
-        self.plate_recognizer = PlateRecognizerManager('mock')  # 车牌识别管理器
-        self.timer = QTimer()
-        self.use_camera = 1  # 1: 摄像头, 0: 视频文件
-        self.detected_plates = []  # 存储切割后的车牌图像数组
-        self.current_frame = None  # 存储当前帧用于车牌矫正
-        
-        self.init_ui()
-        self.init_detector()
-        self.init_video_capture()
-        self.connect_signals()
-        
-    def init_ui(self):
-        """初始化用户界面"""
-        self.setWindowTitle("车牌检测系统 - YOLO11s")
-        self.setGeometry(100, 100, 1200, 800)
-        
-        # 创建中央widget
-        central_widget = QWidget()
-        self.setCentralWidget(central_widget)
-        
-        # 主布局
-        main_layout = QHBoxLayout(central_widget)
-        
-        # 左侧视频显示区域
-        self.create_video_area(main_layout)
-        
-        # 右侧控制和信息显示区域
-        self.create_control_area(main_layout)
-        
-        # 设置布局比例
-        main_layout.setStretch(0, 3)  # 视频区域占3/4
-        main_layout.setStretch(1, 1)  # 控制区域占1/4
-        
-    def create_video_area(self, parent_layout):
-        """创建视频显示区域"""
-        video_frame = QFrame()
-        video_frame.setFrameStyle(QFrame.StyledPanel)
-        video_layout = QVBoxLayout(video_frame)
-        
-        # 视频显示widget
-        self.video_widget = VideoWidget()
-        video_layout.addWidget(self.video_widget)
-        
-        parent_layout.addWidget(video_frame)
-        
-    def create_control_area(self, parent_layout):
-        """创建控制和信息显示区域"""
-        control_frame = QFrame()
-        control_frame.setFrameStyle(QFrame.StyledPanel)
-        control_frame.setMaximumWidth(300)
-        control_layout = QVBoxLayout(control_frame)
-        
-        # 控制按钮组
-        self.create_control_buttons(control_layout)
-        
-        # 检测信息显示
-        self.create_detection_info(control_layout)
-        
-        # 车牌号显示区域
-        self.create_plate_display(control_layout)
-        
-        # 系统状态显示
-        self.create_status_display(control_layout)
-        
-        parent_layout.addWidget(control_frame)
-        
-    def create_control_buttons(self, parent_layout):
-        """创建控制按钮"""
-        button_group = QGroupBox("控制面板")
-        button_layout = QVBoxLayout(button_group)
-        
-        # 开始/停止按钮
-        self.start_btn = QPushButton("开始检测")
-        self.start_btn.setMinimumHeight(40)
-        self.start_btn.clicked.connect(self.toggle_detection)
-        button_layout.addWidget(self.start_btn)
-        
-        # 视频源切换
-        self.camera_checkbox = QCheckBox("使用摄像头")
-        self.camera_checkbox.setChecked(True)
-        self.camera_checkbox.stateChanged.connect(self.toggle_video_source)
-        button_layout.addWidget(self.camera_checkbox)
-        
-        # 检测开关
-        self.detection_checkbox = QCheckBox("启用检测")
-        self.detection_checkbox.setChecked(True)
-        button_layout.addWidget(self.detection_checkbox)
-        
-        parent_layout.addWidget(button_group)
-        
-    def create_detection_info(self, parent_layout):
-        """创建检测信息显示"""
-        info_group = QGroupBox("检测信息")
-        info_layout = QVBoxLayout(info_group)
-        
-        # FPS显示
-        self.fps_label = QLabel("FPS: 0")
-        self.fps_label.setFont(QFont("Arial", 12, QFont.Bold))
-        info_layout.addWidget(self.fps_label)
-        
-        # 检测数量
-        self.detection_count_label = QLabel("检测到车牌: 0")
-        info_layout.addWidget(self.detection_count_label)
-        
-        # 模型信息
-        self.model_info_label = QLabel("模型: YOLO11s (ONNX)")
-        info_layout.addWidget(self.model_info_label)
-        
-        parent_layout.addWidget(info_group)
-        
-    def create_plate_display(self, parent_layout):
-        """创建车牌号显示区域"""
-        plate_group = QGroupBox("车牌识别结果")
-        plate_layout = QVBoxLayout(plate_group)
-        
-        # 当前识别的车牌号
-        self.current_plate_label = QLabel("当前车牌: 未识别")
-        self.current_plate_label.setFont(QFont("Arial", 14, QFont.Bold))
-        self.current_plate_label.setStyleSheet("color: blue; padding: 10px; border: 1px solid gray;")
-        plate_layout.addWidget(self.current_plate_label)
-        
-        # 矫正后的车牌图像显示
-        self.plate_image_label = QLabel("矫正后车牌图像")
-        self.plate_image_label.setAlignment(Qt.AlignCenter)
-        self.plate_image_label.setMinimumHeight(100)
-        self.plate_image_label.setMaximumHeight(150)
-        self.plate_image_label.setStyleSheet("border: 1px solid gray; background-color: #f0f0f0;")
-        plate_layout.addWidget(self.plate_image_label)
-        
-        # 历史车牌记录
-        history_label = QLabel("历史记录:")
-        plate_layout.addWidget(history_label)
-        
-        self.plate_history = QTextEdit()
-        self.plate_history.setMaximumHeight(150)
-        self.plate_history.setReadOnly(True)
-        plate_layout.addWidget(self.plate_history)
-        
-        # 预留接口说明
-        interface_label = QLabel("注: 车牌识别接口已预留，可接入OCR模型")
-        interface_label.setStyleSheet("color: gray; font-size: 10px;")
-        plate_layout.addWidget(interface_label)
-        
-        parent_layout.addWidget(plate_group)
-        
-    def create_status_display(self, parent_layout):
-        """创建系统状态显示"""
-        status_group = QGroupBox("系统状态")
-        status_layout = QVBoxLayout(status_group)
-        
-        self.status_label = QLabel("状态: 就绪")
-        status_layout.addWidget(self.status_label)
-        
-        self.gpu_status_label = QLabel("GPU: 检测中...")
-        status_layout.addWidget(self.gpu_status_label)
-        
-        parent_layout.addWidget(status_group)
-        
-        # 添加弹性空间
-        parent_layout.addStretch()
-        
-    def init_detector(self):
-        """初始化YOLO检测器"""
-        try:
-            model_path = os.path.join(os.path.dirname(__file__), "..", "yolo11sth50.onnx")
-            self.yolo_detector = YOLODetector(model_path)
-            self.model_info_label.setText(f"模型: YOLO11s (ONNX) - GPU: {self.yolo_detector.use_gpu}")
-            self.gpu_status_label.setText(f"GPU: {'启用' if self.yolo_detector.use_gpu else '禁用'}")
-        except Exception as e:
-            self.status_label.setText(f"模型加载失败: {str(e)}")
-            
-    def init_video_capture(self):
-        """初始化视频捕获"""
-        try:
-            self.video_capture = VideoCapture()
-            self.status_label.setText("视频捕获初始化成功")
-        except Exception as e:
-            self.status_label.setText(f"视频捕获初始化失败: {str(e)}")
-            
-    def connect_signals(self):
-        """连接信号和槽"""
-        self.timer.timeout.connect(self.update_frame)
-        
-    def toggle_detection(self):
-        """切换检测状态"""
-        if self.timer.isActive():
-            self.stop_detection()
-        else:
-            self.start_detection()
-            
-    def start_detection(self):
-        """开始检测"""
-        if self.video_capture and self.video_capture.start_capture(self.use_camera):
-            # 根据视频源类型设置定时器间隔
-            video_fps = self.video_capture.get_video_fps()
-            timer_interval = int(1000 / video_fps)  # 转换为毫秒
-            self.timer.start(timer_interval)
-            
-            self.start_btn.setText("停止检测")
-            source_type = "摄像头" if self.use_camera else f"视频文件({video_fps:.1f}FPS)"
-            self.status_label.setText(f"检测中... - {source_type}")
-        else:
-            self.status_label.setText("启动失败")
-            
-    def stop_detection(self):
-        """停止检测"""
-        self.timer.stop()
-        if self.video_capture:
-            self.video_capture.stop_capture()
-        self.start_btn.setText("开始检测")
-        self.status_label.setText("已停止")
-        
-    def toggle_video_source(self, state):
-        """切换视频源"""
-        self.use_camera = 1 if state == Qt.Checked else 0
-        if self.timer.isActive():
-            self.stop_detection()
-            self.start_detection()
-            
-    def update_frame(self):
-        """更新帧"""
-        if not self.video_capture:
-            return
-            
-        frame, fps = self.video_capture.get_frame()
-        if frame is None:
-            return
-            
-        # 保存当前帧用于车牌矫正
-        self.current_frame = frame.copy()
-        
-        # 更新FPS显示
-        self.fps_label.setText(f"FPS: {fps:.1f}")
-        
-        # 进行检测
-        if self.detection_checkbox.isChecked() and self.yolo_detector:
-            detections = self.yolo_detector.detect(frame)
-            frame = self.yolo_detector.draw_detections(frame, detections)
-            
-            # 切割车牌图像
-            if detections:
-                self.detected_plates = self.yolo_detector.crop_plates(frame, detections)
-                
-                # 统计不同类型车牌数量
-                blue_count = sum(1 for d in detections if d['class_id'] == 0)
-                green_count = sum(1 for d in detections if d['class_id'] == 1)
-                total_count = len(detections)
-                
-                self.detection_count_label.setText(f"检测到车牌: {total_count} (蓝牌:{blue_count}, 绿牌:{green_count})")
-                
-                # 调用车牌识别接口（预留）
-                self.recognize_plates(self.detected_plates, detections)
-            else:
-                self.detection_count_label.setText("检测到车牌: 0")
-        
-        # 显示帧
-        self.video_widget.update_frame(frame)
-        
-    def recognize_plates(self, plate_images, detections):
-        """车牌识别接口（预留）"""
-        # 这里是预留的车牌识别接口
-        # 可以接入OCR模型进行车牌号识别
-        if plate_images and detections and self.current_frame is not None:
-            # 获取最新检测到的车牌信息
-            latest_detection = detections[-1]  # 取最后一个检测结果
-            plate_type = "Blue Plate" if latest_detection['class_id'] == 0 else "Green Plate"
-            confidence = latest_detection['confidence']
-            
-            # 处理蓝色车牌的矫正
-            corrected_image = None
-            if latest_detection['class_id'] == 0:  # 蓝色车牌
-                try:
-                    bbox = latest_detection['bbox']
-                    corrected_image = self.plate_recognizer.preprocess_blue_plate(
-                        plate_images[-1], self.current_frame, bbox
-                    )
-                    self._display_plate_image(corrected_image)
-                except Exception as e:
-                    print(f"蓝色车牌矫正失败: {e}")
-                    self.plate_image_label.setText("蓝色车牌矫正失败")
-            elif latest_detection['class_id'] == 1:  # 绿色车牌
-                # 绿色车牌处理预留
-                self.plate_image_label.setText("绿色车牌处理\n(待实现)")
-            
-            # 模拟识别结果
-            plate_text = f"Mock {plate_type}-{len(plate_images)}"
-            self.current_plate_label.setText(f"Current Plate: {plate_text} (Confidence: {confidence:.2f})")
-            
-            # 添加到历史记录
-            import datetime
-            timestamp = datetime.datetime.now().strftime("%H:%M:%S")
-            self.plate_history.append(f"[{timestamp}] {plate_text} (Confidence: {confidence:.2f})")
-    
-    def _display_plate_image(self, image):
-        """在界面上显示车牌图像"""
-        try:
-            # 将OpenCV图像转换为QPixmap
-            if len(image.shape) == 3:
-                height, width, channel = image.shape
-                bytes_per_line = 3 * width
-                q_image = QImage(image.data, width, height, bytes_per_line, QImage.Format_RGB888).rgbSwapped()
-            else:
-                height, width = image.shape
-                bytes_per_line = width
-                q_image = QImage(image.data, width, height, bytes_per_line, QImage.Format_Grayscale8)
-            
-            # 缩放图像以适应标签大小
-            pixmap = QPixmap.fromImage(q_image)
-            scaled_pixmap = pixmap.scaled(self.plate_image_label.size(), Qt.KeepAspectRatio, Qt.SmoothTransformation)
-            
-            self.plate_image_label.setPixmap(scaled_pixmap)
-        except Exception as e:
-            print(f"显示车牌图像失败: {e}")
-            self.plate_image_label.setText(f"图像显示失败: {str(e)}")
-            
-    def closeEvent(self, event):
-        """窗口关闭事件"""
-        self.stop_detection()
-        event.accept()
--- a/yolopart/ui/video_widget.py
+++ b/yolopart/ui/video_widget.py
@@ -1,59 +0,0 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-"""
-视频显示组件
-用于显示视频帧和检测结果
-"""
-
-import cv2
-import numpy as np
-from PyQt5.QtWidgets import QLabel
-from PyQt5.QtCore import Qt
-from PyQt5.QtGui import QImage, QPixmap, QPainter, QPen, QFont
-
-class VideoWidget(QLabel):
-    """视频显示组件"""
-    
-    def __init__(self):
-        super().__init__()
-        self.setMinimumSize(640, 480)
-        self.setStyleSheet("border: 1px solid gray; background-color: black;")
-        self.setAlignment(Qt.AlignCenter)
-        self.setText("视频显示区域\n点击'开始检测'开始")
-        self.setScaledContents(True)
-        
-    def update_frame(self, frame):
-        """更新显示帧"""
-        if frame is None:
-            return
-            
-        # 转换BGR到RGB
-        rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
-        h, w, ch = rgb_frame.shape
-        bytes_per_line = ch * w
-        
-        # 创建QImage
-        qt_image = QImage(rgb_frame.data, w, h, bytes_per_line, QImage.Format_RGB888)
-        
-        # 转换为QPixmap并显示
-        pixmap = QPixmap.fromImage(qt_image)
-        
-        # 缩放以适应widget大小，保持宽高比
-        scaled_pixmap = pixmap.scaled(
-            self.size(), 
-            Qt.KeepAspectRatio, 
-            Qt.SmoothTransformation
-        )
-        
-        self.setPixmap(scaled_pixmap)
-        
-    def paintEvent(self, event):
-        """绘制事件"""
-        super().paintEvent(event)
-        
-        # 如果没有图像，显示提示文本
-        if not self.pixmap():
-            painter = QPainter(self)
-            painter.setPen(QPen(Qt.white))
-            painter.setFont(QFont("Arial", 16))
-            painter.drawText(self.rect(), Qt.AlignCenter, "视频显示区域\n点击'开始检测'开始")
--- a/yolopart/utils/init.py
+++ b/yolopart/utils/init.py
@@ -1 +0,0 @@
-# 工具模块初始化文件
--- a/yolopart/utils/pycache/init.cpython-38.pyc
+++ b/yolopart/utils/pycache/init.cpython-38.pyc
--- a/yolopart/utils/pycache/blue_plate_processor.cpython-38.pyc
+++ b/yolopart/utils/pycache/blue_plate_processor.cpython-38.pyc
--- a/yolopart/utils/pycache/video_capture.cpython-38.pyc
+++ b/yolopart/utils/pycache/video_capture.cpython-38.pyc
--- a/yolopart/utils/video_capture.py
+++ b/yolopart/utils/video_capture.py
@@ -1,280 +0,0 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-"""
-视频捕获管理
-支持摄像头和视频文件的切换和管理
-"""
-
-import cv2
-import os
-import time
-import threading
-from typing import Optional, Tuple
-
-class VideoCapture:
-    """视频捕获管理类"""
-    
-    def __init__(self):
-        """
-        初始化视频捕获管理器
-        """
-        self.cap = None
-        self.is_camera = True
-        self.video_path = None
-        self.fps_counter = FPSCounter()
-        self.frame_lock = threading.Lock()
-        self.current_frame = None
-        self.is_running = False
-        self.video_fps = 30.0  # 视频原始帧率
-        
-        # 设置视频文件路径
-        self.video_file_path = os.path.join(os.path.dirname(__file__), "..", "video.mp4")
-        
-    def start_capture(self, use_camera: int = 1) -> bool:
-        """
-        开始视频捕获
-        
-        Args:
-            use_camera: 1使用摄像头，0使用视频文件
-            
-        Returns:
-            是否成功启动
-        """
-        self.stop_capture()
-        
-        self.is_camera = bool(use_camera)
-        
-        try:
-            if self.is_camera:
-                # 使用摄像头
-                self.cap = cv2.VideoCapture(0)
-                if not self.cap.isOpened():
-                    # 尝试其他摄像头索引
-                    for i in range(1, 5):
-                        self.cap = cv2.VideoCapture(i)
-                        if self.cap.isOpened():
-                            break
-                    else:
-                        print("无法打开摄像头")
-                        return False
-                        
-                # 设置摄像头参数
-                self.cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640)
-                self.cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)
-                self.cap.set(cv2.CAP_PROP_FPS, 30)
-                
-                print("摄像头启动成功")
-                
-            else:
-                # 使用视频文件
-                if not os.path.exists(self.video_file_path):
-                    print(f"视频文件不存在: {self.video_file_path}")
-                    return False
-                    
-                self.cap = cv2.VideoCapture(self.video_file_path)
-                if not self.cap.isOpened():
-                    print(f"无法打开视频文件: {self.video_file_path}")
-                    return False
-                
-                # 获取视频原始帧率
-                self.video_fps = self.cap.get(cv2.CAP_PROP_FPS)
-                if self.video_fps <= 0:
-                    self.video_fps = 25.0  # 默认帧率
-                    
-                print(f"视频文件加载成功: {self.video_file_path}, FPS: {self.video_fps}")
-                
-            self.is_running = True
-            self.fps_counter.reset()
-            return True
-            
-        except Exception as e:
-            print(f"启动视频捕获失败: {e}")
-            return False
-            
-    def stop_capture(self):
-        """停止视频捕获"""
-        self.is_running = False
-        
-        if self.cap is not None:
-            self.cap.release()
-            self.cap = None
-            
-        with self.frame_lock:
-            self.current_frame = None
-            
-        print("视频捕获已停止")
-        
-    def get_frame(self) -> Tuple[Optional[cv2.Mat], float]:
-        """
-        获取当前帧
-        
-        Returns:
-            (frame, fps): 当前帧和FPS
-        """
-        if not self.is_running or self.cap is None:
-            return None, 0.0
-            
-        try:
-            ret, frame = self.cap.read()
-            
-            if not ret:
-                if not self.is_camera:
-                    # 视频文件播放完毕，重新开始（循环播放）
-                    self.cap.set(cv2.CAP_PROP_POS_FRAMES, 0)
-                    ret, frame = self.cap.read()
-                    
-                if not ret:
-                    return None, 0.0
-                    
-            # 更新FPS计数器
-            fps = self.fps_counter.update()
-            
-            # 在帧上绘制FPS信息
-            frame_with_fps = self._draw_fps(frame, fps)
-            
-            with self.frame_lock:
-                self.current_frame = frame_with_fps.copy()
-                
-            return frame_with_fps, fps
-            
-        except Exception as e:
-            print(f"获取帧失败: {e}")
-            return None, 0.0
-            
-    def _draw_fps(self, frame: cv2.Mat, fps: float) -> cv2.Mat:
-        """
-        在帧上绘制FPS信息
-        
-        Args:
-            frame: 输入帧
-            fps: 当前FPS
-            
-        Returns:
-            绘制了FPS的帧
-        """
-        result_frame = frame.copy()
-        
-        # FPS文本
-        fps_text = f"FPS: {fps:.1f}"
-        
-        # 文本参数
-        font = cv2.FONT_HERSHEY_SIMPLEX
-        font_scale = 0.7
-        color = (0, 255, 0)  # 绿色
-        thickness = 2
-        
-        # 获取文本尺寸
-        text_size = cv2.getTextSize(fps_text, font, font_scale, thickness)[0]
-        
-        # 绘制背景矩形
-        cv2.rectangle(result_frame, 
-                     (10, 10), 
-                     (20 + text_size[0], 20 + text_size[1]), 
-                     (0, 0, 0), -1)
-        
-        # 绘制FPS文本
-        cv2.putText(result_frame, fps_text, 
-                   (15, 15 + text_size[1]), 
-                   font, font_scale, color, thickness)
-        
-        return result_frame
-        
-    def get_capture_info(self) -> dict:
-        """
-        获取捕获信息
-        
-        Returns:
-            捕获信息字典
-        """
-        info = {
-            'is_running': self.is_running,
-            'is_camera': self.is_camera,
-            'video_path': self.video_file_path if not self.is_camera else None,
-            'fps': self.fps_counter.get_fps(),
-            'video_fps': self.video_fps
-        }
-        
-        if self.cap is not None:
-            try:
-                info['width'] = int(self.cap.get(cv2.CAP_PROP_FRAME_WIDTH))
-                info['height'] = int(self.cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
-                if not self.is_camera:
-                    info['total_frames'] = int(self.cap.get(cv2.CAP_PROP_FRAME_COUNT))
-                    info['current_frame'] = int(self.cap.get(cv2.CAP_PROP_POS_FRAMES))
-            except:
-                pass
-                
-        return info
-        
-    def get_video_fps(self) -> float:
-        """
-        获取视频帧率
-        
-        Returns:
-            视频帧率，摄像头返回30.0，视频文件返回原始帧率
-        """
-        if self.is_camera:
-            return 30.0  # 摄像头固定30FPS
-        else:
-            return self.video_fps  # 视频文件原始帧率
-        
-    def __del__(self):
-        """析构函数"""
-        self.stop_capture()
-
-class FPSCounter:
-    """FPS计数器"""
-    
-    def __init__(self, window_size: int = 30):
-        """
-        初始化FPS计数器
-        
-        Args:
-            window_size: 滑动窗口大小
-        """
-        self.window_size = window_size
-        self.frame_times = []
-        self.last_time = time.time()
-        
-    def update(self) -> float:
-        """
-        更新FPS计数
-        
-        Returns:
-            当前FPS
-        """
-        current_time = time.time()
-        
-        # 添加当前帧时间
-        self.frame_times.append(current_time)
-        
-        # 保持窗口大小
-        if len(self.frame_times) > self.window_size:
-            self.frame_times.pop(0)
-            
-        # 计算FPS
-        if len(self.frame_times) >= 2:
-            time_diff = self.frame_times[-1] - self.frame_times[0]
-            if time_diff > 0:
-                fps = (len(self.frame_times) - 1) / time_diff
-                return fps
-                
-        return 0.0
-        
-    def get_fps(self) -> float:
-        """
-        获取当前FPS
-        
-        Returns:
-            当前FPS
-        """
-        if len(self.frame_times) >= 2:
-            time_diff = self.frame_times[-1] - self.frame_times[0]
-            if time_diff > 0:
-                return (len(self.frame_times) - 1) / time_diff
-        return 0.0
-        
-    def reset(self):
-        """重置计数器"""
-        self.frame_times.clear()
-        self.last_time = time.time()
--- a/yolopart/yolo11sth50.onnx
+++ b/yolopart/yolo11sth50.onnx
Author	SHA1	Message	Date
spdis	16d6108292	修复4号命令不能重复执行的bug	2025-10-19 18:07:06 +08:00
spdis	30edbda7de	hi3861软件	2025-10-18 16:05:39 +08:00
spdis	3d7a4dcb4d	hi3861软件	2025-10-18 16:01:35 +08:00
spdis	6c7f013a0c	更新接口	2025-09-04 00:07:52 +08:00
spdis	95aa6b6bba	LPR	2025-09-02 11:40:41 +08:00
spdis	739cd1d914	更新 README.md	2025-09-01 15:42:42 +08:00
spdis	01df759772	删除 yolopart/utils/__pycache__/video_capture.cpython-38.pyc	2025-09-01 15:37:13 +08:00
spdis	cb88e6fccd	删除 yolopart/utils/__pycache__/blue_plate_processor.cpython-38.pyc	2025-09-01 15:37:10 +08:00
spdis	80e995b47c	删除 yolopart/utils/__pycache__/__init__.cpython-38.pyc	2025-09-01 15:37:07 +08:00
spdis	f82df06a68	删除 yolopart/ui/__pycache__/video_widget.cpython-38.pyc	2025-09-01 15:36:59 +08:00
spdis	dc651af561	删除 yolopart/ui/__pycache__/main_window.cpython-38.pyc	2025-09-01 15:36:57 +08:00
spdis	9f9bd25ce7	删除 yolopart/ui/__pycache__/__init__.cpython-38.pyc	2025-09-01 15:36:54 +08:00
spdis	97ca0d75c2	删除 yolopart/models/__pycache__/yolo_detector.cpython-38.pyc	2025-09-01 15:36:45 +08:00
spdis	75cc3b8ea3	删除 yolopart/models/__pycache__/plate_recognizer.cpython-38.pyc	2025-09-01 15:36:37 +08:00
spdis	aca5703b9e	删除 yolopart/models/__pycache__/__init__.cpython-38.pyc	2025-09-01 15:36:32 +08:00
spdis	2eba46bc40	Merge pull request 'ocr-v1' (#4 ) from ocr-v1 into main Reviewed-on: #4	2025-09-01 15:35:07 +08:00
spdis	f342d37d63	修改了模块的函数名，现在想用哪个模块直接导入即可	2025-09-01 15:33:05 +08:00
spdis	1c914cf89f	OCR	2025-09-01 15:23:44 +08:00
spdis	afba7af80b	OCR	2025-09-01 00:01:38 +08:00
Viajero	8eef0d9414	Merge pull request 'yolorestart' (#1 ) from yolopart_restart into main Reviewed-on: #1	2025-08-31 18:42:35 +08:00
Viajero	8e8fda7fe9	Merge remote-tracking branch 'origin/ocr-v1' into ocr-v1 # Conflicts: # OCR_part/ocr_interface.py	2025-08-31 18:37:40 +08:00
Viajero	9879cb1547	Merge pull request 'yolorestart' (#1 ) from yolopart_restart into main Reviewed-on: #1	2025-08-31 18:36:36 +08:00
spdis	3829cf76ee	Merge pull request 'yolorestart' (#1 ) from yolopart_restart into main Reviewed-on: #1	2025-08-31 18:28:57 +08:00
spdis	c8a541ec11	Merge pull request 'yolorestart' (#1 ) from yolopart_restart into main Reviewed-on: #1	2025-08-31 16:11:18 +08:00
spdis	b5839d2c36	更新 README.md	2025-08-31 12:53:11 +08:00
spdis	afe15b990a	更新 main.py	2025-08-31 12:19:25 +08:00
spdis	7f89965956	上传文件至 CRNN_part	2025-08-31 12:18:48 +08:00
spdis	c7ecc5325e	删除 CRNN_part/best_model.pth	2025-08-31 12:17:59 +08:00
spdis	01b286fce1	更新 CRNN_part/crnn_interface.py	2025-08-31 12:15:38 +08:00
spdis	85c8302fc1	Merge pull request 'yolopart_restart' (#3 ) from yolopart_restart into main Reviewed-on: #3	2025-08-31 01:26:01 +08:00
spdis	0cd70df215	CRNN model	2025-08-31 01:16:08 +08:00
spdis	658560c34f	Merge pull request 'yolorestart' (#2 ) from yolopart_restart into main Reviewed-on: #2	2025-08-30 12:33:05 +08:00
spdis	c773a12f90	Merge remote-tracking branch 'origin/main' into yolopart_restart	2025-08-30 12:28:53 +08:00
spdis	a41a4a2236	yolorestart	2025-08-30 12:23:01 +08:00
spdis	3d7c7a06e4	Merge pull request 'yolorestart' (#1 ) from yolopart_restart into main Reviewed-on: #1	2025-08-30 11:55:37 +08:00
spdis	19176c71b7	yolorestart	2025-08-30 11:53:20 +08:00