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11 Commits
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0e843caad6 | |
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6fc795815f | |
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b46d2730cc | |
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34061d64d5 | |
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b47f28528a | |
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cb3f429e9e | |
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04d8dfbe68 | |
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24a6703ea6 | |
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0b8eadd54a | |
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7f48282f7d | |
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bcc5f6bcd4 |
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@ -0,0 +1,8 @@
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# Default ignored files
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/shelf/
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/workspace.xml
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# Editor-based HTTP Client requests
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/httpRequests/
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# Datasource local storage ignored files
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/dataSources/
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/dataSources.local.xml
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@ -0,0 +1 @@
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train
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@ -0,0 +1,2 @@
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<?xml version="1.0" encoding="UTF-8"?>
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<module classpath="CMake" type="CPP_MODULE" version="4" />
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@ -0,0 +1,7 @@
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<?xml version="1.0" encoding="UTF-8"?>
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<project version="4">
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<component name="CMakePythonSetting">
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<option name="pythonIntegrationState" value="YES" />
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</component>
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<component name="CMakeWorkspace" PROJECT_DIR="$PROJECT_DIR$" />
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</project>
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@ -0,0 +1,8 @@
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<?xml version="1.0" encoding="UTF-8"?>
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<project version="4">
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<component name="ProjectModuleManager">
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<modules>
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<module fileurl="file://$PROJECT_DIR$/.idea/VCarContainer_arm.iml" filepath="$PROJECT_DIR$/.idea/VCarContainer_arm.iml" />
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</modules>
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</component>
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</project>
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@ -0,0 +1,6 @@
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<?xml version="1.0" encoding="UTF-8"?>
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<project version="4">
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<component name="VcsDirectoryMappings">
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<mapping directory="$PROJECT_DIR$" vcs="Git" />
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</component>
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</project>
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@ -70,6 +70,8 @@ namespace ai_matrix
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this->identifyConfig_.iTargetMinWidth = config_["identify"]["target_min_width"].as<int>();
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this->identifyConfig_.iTargetMinY = config_["identify"]["target_min_y"].as<int>();
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this->identifyConfig_.iMaxIdentifyFrame = config_["identify"]["max_identify_frame"].as<int>();
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this->identifyConfig_.iMaxContainerSpaceX = config_["identify"]["max_container_space_x"].as<int>();
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this->identifyConfig_.iMaxContainerSpaceY = config_["identify"]["max_container_space_y"].as<int>();
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// websocket server 服务端参数
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this->wSocketConfig_.bIsUse = config_["wsocket_server"]["is_use"].as<bool>();
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@ -88,6 +88,10 @@ namespace ai_matrix
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int iTargetMinY;
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// 单次识别最大帧数
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int iMaxIdentifyFrame;
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// 两个箱子的箱角最大差值X
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int iMaxContainerSpaceX;
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// 两个箱子的箱角最大差值Y
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int iMaxContainerSpaceY;
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};
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// websocket_server 的服务端参数
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@ -1,101 +0,0 @@
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# 基础控制参数
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base:
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# 股道名称
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track_name: "1"
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# 测试模式
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test_model: false
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# Api 监听端口
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api_port: 7070
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# 日志文件目录
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log_path: "./logs"
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# 识别结果目录
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result_path: "./result"
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# 调试结果目录
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debug_result_path: "./debug_result"
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# 结果存储天数
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result_save_days: 10
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# 日志参数
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log:
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# 输出日志级别[DEBUG, INFO, WARN, ERROR, FATAL]
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out_level: "DEBUG"
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# 保存日志级别
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save_level: "DEBUG"
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# 数据源参数
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data_source:
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url: "./vedio/buertai2.mp4"
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# 跳帧数
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skip_interval: 3
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# 行驶方向 0-自动识别 1-向左 2-向右 (与“首位信息”成对存在,形成例如向左就编号在前,向右就属性在前的对应)
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direction: 0
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# 0-向左编号在前 1-向左属性在前 (向右行驶的情况:2-向右编号在前 3-向右属性在前)
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left_first: 0
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# (向左行驶的情况:0-向左编号在前 1-向左属性在前) 2-向右编号在前 3-向右属性在前
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right_first: 3
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# 识别区域
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identify_areas: [120, 0, 1800, 1080]
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# 识别参数
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identify:
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# 运行方式
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run_mode: "always" #[always; command]
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# 是否开启动态检测
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need_move_detect_flag: true
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# 识别方向 [LEFT,RIGHT,ALL]
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identify_direction: "LEFT"
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# 大框帧跨度(比一个大框从出现到消失的跨度稍大一点, 跟跳帧有关系)
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partition_frame_span: 20
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# 大框帧跨度的位置像素差异
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split_frame_span_px: 200
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# 每帧大框位置差异最小值 (持续小于此值,则可能停车)
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chkstop_px: 15
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# 持续X次续位置差异小于gc_chkstop_px,则判断为停车。
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chkstop_count: 10
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# 过滤最小大框高度(不需要的话就写个很小的值)
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num_frame_height: 150
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pro_frame_height: 120
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# 过滤最大框宽度(不需要的话就写个很大的值)
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space_frame_width: 500
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# 是否识别车头
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train_heard_detect: false
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# 是否识别集装箱
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container_detect: false
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# websocket_server 的服务端参数
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wsocket_server:
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is_use: false
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port: 7071
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max_queue_len: 10
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# http 接口
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http_server:
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# 使用状态
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is_use: false
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# 服务器IP
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http_ip: 192.168.2.108
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# 通讯端口
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http_port: 20004
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# 获取接口授权地址
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token_path: "/api/blade-auth/oauth/token"
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# 识别结果上传地址
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up_result_path: "/api/train-carriage/identification/rfid-save"
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# 设备状态上传地址
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device_status_url: ""
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# 接口用户名
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username: "guest_01"
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# 接口密码
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password: "d55b0f642e817eea24725d2f2a31dd08"
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# minio 服务配置
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minio:
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# 使用状态
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is_use: false
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# 服务地址
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url: "http://192.168.32.134:19000"
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# 通讯授权
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accesskey: "OpgVbHoeDLUBWjQkN3NS"
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# 密钥授权
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secretkey: "fc0sDwKTq2N7ZVl2iJk36WUZgL5EtNLTjRVtIzNM"
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# 容器名
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bucket: "train"
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@ -1,44 +0,0 @@
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#use_deviceid:
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# #engineid: deviceid
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# 0: 0
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#engine实例
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engines:
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ApiEngine: 0
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VideoEngine: 0
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VideoDecodeEngine: 0
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MoveEngine: 0
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SaveMoveImageEngine: 0
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SaveMoveInfoEngine: 0
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TrainStep1DataReadEngine: 0
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TrainStep1InferenceEngine: 0
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TrainStep1FilterEngine: 0
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TrainDivideEngine: 0
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TrainStep2DataReadEngine: 0
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TrainStep2InferenceEngine: 0
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TrainCharacterConversionEngine: 0
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SelectBestEngine: 0
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SaveResultCSVEngine: 0
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ToHttpSrvEngine: 0
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ToMinioSrvEngine: 0
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SaveDebugImageEngine: 0
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#engine连接
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connects:
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VideoEngine_0_0: "VideoDecodeEngine_0_0 1024"
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VideoDecodeEngine_0_0: "MoveEngine_0_0 1024"
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MoveEngine_0_0: "SaveMoveImageEngine_0_0 1024"
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MoveEngine_0_1: "SaveMoveInfoEngine_0_0 1024"
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SaveMoveImageEngine_0_0: "TrainStep1DataReadEngine_0_0 1024"
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TrainStep1DataReadEngine_0_0: "TrainStep1InferenceEngine_0_0 1024"
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TrainStep1InferenceEngine_0_0: "TrainStep1FilterEngine_0_0 1024"
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TrainStep1FilterEngine_0_0: "TrainDivideEngine_0_0 1024"
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TrainDivideEngine_0_0: "TrainStep2DataReadEngine_0_0 1024"
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TrainStep2DataReadEngine_0_0: "TrainStep2InferenceEngine_0_0 1024"
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TrainStep2InferenceEngine_0_0: "TrainCharacterConversionEngine_0_0 1024"
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TrainCharacterConversionEngine_0_0: "SelectBestEngine_0_0 1024"
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TrainCharacterConversionEngine_0_1: "SaveDebugImageEngine_0_0 1024"
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SelectBestEngine_0_0: "SaveResultCSVEngine_0_0 1024"
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SaveResultCSVEngine_0_0: "ToHttpSrvEngine_0_0 1024"
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SaveResultCSVEngine_0_1: "ToMinioSrvEngine_0_0 1024"
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@ -1,47 +0,0 @@
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# 动态检测
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move_model:
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model_path: "./model/step0/step0.engine"
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score_threshold: 0
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class: []
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# 关键区域识别
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train_step1_model:
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model_path: "./model/step1/step1.engine"
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score_threshold: 0.6
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class: [ "HEADNUM",
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"PROPERTY",
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"TYPENUM_K",
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"TYPENUM_C",
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"TYPENUM_P",
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"TYPENUM_G",
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"TYPENUM_N",
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"MAINTENFLAG",
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"TYPENUM_J",
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"SPACE",
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"SPACELK",
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"SPACENX",
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"SPACEG",
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"SPACEP",
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"SPACEJ",
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"TYPENUM_W",
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"SPACEW",
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"SPACEM",
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"SPACEU"
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]
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# 字符识别
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train_step2_model:
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model_path: "./model/step2/step2.engine"
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score_threshold: 0.7
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class: ["0","1","2","3","4","5","6","7","8","9",
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"A","B","C","D","E","F","G","H","I","J","K","L", "M", "N", "O", "P", "Q", "R", "S", "T", "U", "V","W", "X", "Y", "Z",
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"change", "load", "m", "self", "t", "volume", "meter",")", "(", "?", "-"
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]
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# 集装箱关键区域识别
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container_step1_model:
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model_path: "./model/container_step1/con1.engine"
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score_threshold: 0.6
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class: []
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# 集装箱字符识别
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container_step2_model:
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model_path: "./model/container_step2/con2.engine"
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score_threshold: 0.7
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class: []
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