Train_Identify_arm/config.yaml

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gc_init_deviceid: "ALL" #例: 0; 0,1; 2,3; ALL
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#识别数据来源参数配置
gc_data_source: "camera" #[camera, images]
camera:
#url: "rtsp://admin:sgt12345@10.27.119.13:554/h264/ch1/main/av_stream"
# url: "./videos/km70.mp4"
url: "./videos/06-29_96.mp4"
skipInterval: 3
target: "NUM"
use: true
direction: 0 #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)
left_first: 0 # 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)
right_first: 3 # (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
identify_areas: "120, 0, 1800, 1080" #(ltx,lty,rbx,rby)
classid_minheight: "1:90, 2:120, 3:120, 9:240, 10:240, 18:120" #大框的最小高度(为屏蔽远股道识别到的信息)
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images:
images_0:
url: "./images"
skipInterval: 5
target: "NUM,PRO,CONTAINER_T"
use: true
direction: 0 #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)
left_first: 0 # 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)
right_first: 3 # (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
identify_areas: "50, 10, 1850, 1080" #(ltx,lty,rbx,rby)
#是否采集数据
gc_collect_data_flag: false
gc_collect_data_savepath: "./collectdata/"
#运行式
gc_run_mode: "always" #[always; command]
#是否开启动态检测
gc_need_move_detect_flag: true
#是否实时推流-用于直播
gc_push_actual_flag: false
gc_log_level: "DEBUG" #[DEBUG, INFO, WARN, ERROR, FATAL]
gc_log_logfile: "./logs/log.txt"
gc_log_logfile_bakpath: "./logs"
#微服务地址
gc_service_address: 0.0.0.0:9002
#授权参数
gc_bind_hardware: false #是否绑定小站true-绑定false-不绑定
gc_check_register: false #是否检查授权true-检查false-不检查
atlas_poundno: "5" #工作站编号
gc_username: "admin"
gc_password: "matrixai@1234"
#选优 0-频率优先 1-长度优先
gc_select_best_mode: 0
#识别结果存储目录
gc_result_path: "./result"
gc_result_path_for_test: "./pic"
gc_best_path: "./result/best"
#模型参数,只考虑敞车
model:
MoveEngine: #动态检测
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# om_path: "./model/step0/step0.FP16.engine"
om_path: "./model/step0/step0.engine"
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modelinfo_path: "./model/step0/retina_move_modelinfo.txt"
model_type: "retina" #(retina, yolov5)
score_threshold: 0.9
nms_threshold: 0.3
TrainStepOneEngine: #关键区域识别
om_path: "./model/step1/step1.engine"
modelinfo_path: "./model/step1/yolov5_train_step1_modelinfo.txt"
model_type: "yolov5" #(retina, yolov5)
score_threshold: 0.6
nms_threshold: 0.3
TrainStepTwoEngine: #字符识别
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# om_path: "./model/step2/step2.engine"
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om_path: "./model/step2/step2.engine"
modelinfo_path: "./model/step2/yolov5_train_step2_modelinfo.txt"
model_type: "yolov5" #(retina, yolov5)
score_threshold: 0.7
nms_threshold: 0.3
ChkDateStepOneEngine: #定检期关键区域识别
om_path: "./model/chkDate_step1/step1.engine"
modelinfo_path: "./model/chkDate_step1/yolov5_chkdate_step1_modelinfo.txt"
model_type: "yolov5" #(retina, yolov5)
score_threshold: 0.6
nms_threshold: 0.3
ChkDateStepTwoEngine: #定检期字符识别
om_path: "./model/chkDate_step2/step2.engine"
modelinfo_path: "./model/chkDate_step2/yolov5_chkdate_step2_modelinfo.txt"
model_type: "yolov5" #(retina, yolov5)
score_threshold: 0.7
nms_threshold: 0.3
StepOneContainerEngine: #集装箱关键区域识别
om_path: "./model/container_step1/con1.engine"
modelinfo_path: "./model/container_step1/yolov5_container_step1_modelinfo.txt"
model_type: "yolov5" #(retina, yolov5)
score_threshold: 0.6
nms_threshold: 0.3
StepTwoContainerEngine: #顶部集装箱字符识别
om_path: "./model/container_step2/con2.engine"
modelinfo_path: "./model/container_step2/yolov5_container_step2_modelinfo.txt"
model_type: "yolov5" #(retina, yolov5)
score_threshold: 0.7
nms_threshold: 0.3
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gc_http_open: 0
# gc_http_url: "http://192.168.2.211:20004/api/train-carriage/identification/video-save"
# gc_gettoken_url: "http://192.168.2.211:20004/api/blade-auth/oauth/token"
# gc_image_srv: "http://192.168.2.211:9010/"
username: ""
password: ""
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gc_http_url: "http://192.168.2.121:8081"
gc_gettoken_url: "http://192.168.0.121:20004/api/blade-auth/oauth/token"
gc_image_srv: "http://192.168.0.121:9010/"
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gc_device_status_open: 0
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gc_device_status_url: "http://192.168.2.211:20004/api/blade-train/deviceInfo/save"
rfid_ip: "10.27.200.39"
#socket_server 的服务端参数
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socket_server_open: 0
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socket_server_port: 7000
socket_server_queue_len: 10
#sftp用户名、密码、地址
gc_ftp_open: 0
gc_ftp_type: "ftp" #可选 ftp 或 sftp
gc_ftp_ip: "192.168.2.138"
gc_ftp_port: 21 # ftp默认21 sftp默认22
gc_ftp_username: "nvidia"
gc_ftp_password: "nvidia"
gc_ftp_image_path: ""
gc_ftp_quit_time: 10 #无上传任务延迟XXX秒断开FTP连接
gc_minio_open: 0
gc_minio_url: "http://192.168.2.115:9000"
gc_minio_accesskey: "J4SiNTqzt5Ur8ukC"
gc_minio_secretkey: "zILttfdSpgylhATgV8K3cSqyLlflY60X"
gc_minio_path: "nzz/"
# mysql 相关
gc_mysql_open: 0
gc_mysql_table: "train_income_intf"
gc_mysql_charset: "gbk"
gc_mysql_host: "192.168.2.137"
gc_mysql_user: "root"
gc_mysql_passwd: "123456"
gc_mysql_db: "test1"
gc_mysql_port: "http://192.168.2.115:9000"
gc_push_direction: 2 #(1:识别向左行驶的列车2:识别向右行驶的列车0:识别双方向。 注如果方向不对服务器会正常识别只是不推送给web)
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gc_space_minrbx_imgpercent: 0 #间隔框最低点不应小于画面某个高度值(该值为画面百分比) [主要为屏蔽远股道间隔框若不需要屏蔽则配置为0]
#车厢划分相关
partition_frame_span: 20 #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)
gc_split_frame_span_px: 200 #大框帧跨度的位置像素差异
#停车判断相关
gc_chkstop_px: 15 #连续三帧位置差异小于15px则可能停车
gc_chkstop_count: 10 #持续10次续三帧位置差异小于15px则判断为停车。
#远股道
gc_save_pic_quality: 50
gc_load_delay: 10
gc_hardware_decode: true
# 过滤最小大框高度(不需要的话就写个很小的值)
gc_num_frame_height: 150
gc_pro_frame_height: 120
# 过滤最大框宽度(不需要的话就写个很大的值)
gc_c_space_frame_width: 500
# 是否识别车头
gc_train_heard_detect: true
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# 识别结果保存天数
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gc_days_for_result_expire_folder: 3