[完善]文件转化

package.json

@@ -24,6 +24,7 @@
     "ngx-cookie-service": "^13.1.2",
     "rxjs": "~7.4.0",
     "tslib": "^2.3.0",
+    "yaml": "^2.2.1",
     "zone.js": "~0.11.4"
   },
   "devDependencies": {

src/app/system-management/host-config/host-config.component.ts

@@ -36,7 +36,7 @@ interface Camera {
 }
 
 import yaml from 'js-yaml';
-// declare var yaml: any;
+import * as YAML from 'yaml';
 
 @Component({
   selector: 'app-host-config',
@@ -592,7 +592,7 @@ sources:`;
     const instance = modal.getContentComponent();
   }
   //整理配置文件数据
-  disposalData() {
+  async disposalData() {
     let copyListOfData = JSON.parse(JSON.stringify(this.listOfData));
     copyListOfData = copyListOfData.filter((item, i) => {
       return item.isEnabled;
@@ -880,6 +880,7 @@ ${newstr}class-id=0
     console.log(this.hostData);
     //如果之前保存过文件
     if (this.hostData.configFiles && this.hostData.configFiles.length !== 0) {
+      console.log('走这里了吗')
       let config_arm = this.hostData.configFiles.find(
         (item) => item.name == 'config_arm.yaml'
       ).content;
@@ -891,6 +892,8 @@ ${newstr}class-id=0
       //修改config_arm.yaml文件
       //更改connet_oil
       let config_armObj = yaml.load(config_arm);
+      // let config_armObj = YAML.parse(config_arm);
+
       // for (const key in config_armObj.connet_oil.roi[0]) {
       //   delete config_armObj.connet_oil.roi[0][key];
       // }
@@ -910,10 +913,10 @@ ${newstr}class-id=0
       //   arr2.push(Number(99));
       // });
       // config_armObj.connet_grounder.roi[0][key2] = [arr2];
-      config2 = yaml.dump(config_armObj);
+      // let yyy = JSON.parse(JSON.stringify(config_armObj, null, 2))
-
+      config2 = yaml.dump(config_armObj, { lineWidth: -1, indent: 3, noArrayIndent: true });
-      console.log(555, config_armObj);
+      // config2 =JSON.parse(JSON.stringify(YAML.stringify(config_armObj)) ) 
-      console.log(6666, yaml.dump(config_armObj));
+      console.log(888, config2)
     } else {
       //使用模板
       config2 = `# The all in one config file.
@@ -1217,6 +1220,22 @@ ${newstr}class-id=0
     sessionStorage.setItem('config3', config3);
     sessionStorage.setItem('config4', config4);
   }
+  // 读取文本文件内容
+  async readFile(file) {
+    const reader = new FileReader()
+    const promise = new Promise((resolve, reject) => {
+      reader.onload = function () {
+        resolve(reader.result)
+      }
+      reader.onerror = function (e) {
+        reader.abort()
+        reject(e)
+      }
+    })
+    reader.readAsText(file, 'UTF-8') // 将文件读取为文本
+
+    return promise
+  }
 
   //黄海配置文件
   config() {

src/assets/file/config_arm.yaml

@@ -0,0 +1,148 @@
+# The all in one config file.
+
+debug: false #when the debug is on, osd.
+video_record: 10 #time to record into the .ts video
+
+sources:
+  config: 'config/source.yaml'
+
+tracker:
+  config: 'config/dstest_tracker_config.txt'
+
+analytics:
+  config: 'config/config_nvdsanalytics.txt'
+
+## 通用模型 ##
+
+# 1：人物检测
+peoplenet:
+  enable: true
+  apply_on: -1
+  interval: 1
+  batch_size: 16
+  topk: 5
+  roi-top-offset: 0
+  roi-bottom-offset: 0
+  detected-min-w: 20 
+  detected-min-h: 200
+  model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/peoplenet/weights/resnet34_peoplenet_int8.etlt_b16_gpu0_int8.engine'
+  threshold: 0.3
+
+# 2：车辆检测
+trafficcam:
+  enable: true
+  apply_on: 0
+  interval: 1
+  batch_size: 16
+  topk: 5
+  roi-top-offset: 0
+  roi-bottom-offset: 0
+  detected-min-w: 100 
+  detected-min-h: 100
+  model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/trafficcam/weights/resnet18_trafficcamnet_pruned.etlt_b16_gpu0_int8.engine'
+
+# 3：人物倚靠行为
+actionnet:
+  enable: false
+  apply_on: 1
+  # roi:
+  #   - 'fuel_island-4':
+  #     - [200, 0, 450, 500]
+  #   - 'fuel_island-5':
+  #     - [930, 93, 940, 987]
+  #   - 'fuel_island-6':
+  #     - [1174, 151, 746, 929]
+  #   - 'fuel_island-7':
+  #     - [1450, 300, 460, 650]
+  interval: 1
+  batch_size: 32
+
+# 4：烟火检测
+fire_smoke_net:
+  enable: true
+  apply_on: -1
+  interval: 1
+  batch_size: 16
+  model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/fire_smoke_net/weights/yolov4_cspdarknet_tiny_fp16.etlt_b16_gpu0_fp16.engine'
+  threshold: 0.95
+
+# 5：抽烟打电话检测
+smoking_calling_net:
+  enable: true
+  apply_on: -1
+  interval: 1
+  batch_size: 2
+  model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/smoking_calling_net/weights/resnet50_smoking_calling_net_fp16.etlt_b2_gpu0_fp16.engine'
+
+## 油站专用模型 ##
+
+# 1：身份判别：工装、反光衣、便衣
+idnet:
+  enable: true
+  apply_on: -1
+  interval: 1
+  batch_size: 2
+  model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/idnet/weights/resnet50_idnet_fp16.etlt_b2_gpu0_fp16.engine'
+
+# 2：卸油区物体识别：油罐车、灭火器、手推车、三角木、取样桶、隔离锥、卸油管
+oilnet:
+  enable: false
+  apply_on: 2
+  interval: 1
+  batch_size: 2 
+  roi-top-offset: 0
+  roi-bottom-offset: 0
+  detected-min-w: 20 
+  detected-min-h: 20
+  model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/oilnet/weights/yolov4_cspdarknet_tiny_fp16.etlt_b2_gpu0_fp16.engine'
+  threshold: 0.5
+
+# 3：卸油管是否连接判定
+connet_oil:
+  enable: true
+  apply_on: 2
+  roi:
+    - 'oil_tube-0':
+      # - [719,509,136,206]   
+      - [719,509,436,286]   
+  interval: 1
+  batch_size: 2
+  model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/connet_oil/weights/resnet50_connet_oil_fp16.etlt_b2_gpu0_fp16.engine'
+
+# 4：静电接地仪器是否连接判定
+connet_grounder:
+  enable: true
+  apply_on: 2
+  roi:
+    - 'grounder-0':
+      - [782,378,271,149]
+  interval: 1
+  batch_size: 2
+  model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/connet_grounder/weights/resnet50_connet_grounder_fp16.etlt_b2_gpu0_fp16.engine'
+
+# 5：散装桶加油
+bulk_oil_net:
+  enable: False
+  apply_on: 2
+  interval: 1
+  batch_size: 2
+  model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/bulk_oil_net/weights/yolov4_cspdarknet_tiny_fp16.etlt_b2_gpu0_fp16.engine'
+  threshold: 0.2
+
+# 模型阈值通用设定
+rule_threshold:
+  object_occurence_interval_second: 3
+  object_disappear_interval_second: 10
+  on_car_parking_interval_second: 1800
+  on_fire_smoke_interval_second: 5
+  on_helmet_interval_second: 5
+  threshold_relying_sitting: 0.4 #rolling mean confidence
+  threshold_smoking_calling: 0.3 #rolling mean confidence
+  threshold_connecting: 0.667 #rolling mean confidence
+  threshold_identity: 0.1 #only to filter out people net error
+  threshold_helmet: 0 #num of helmet detected on a person
+  enable_seconday_model: False      # secondary model (双模型)
+  threshold_secondary_model: 0.5    
+  secondary_model_window: 50
+  secondary_model_path: '/opt/app/xgboost'
+