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@ -289,12 +289,12 @@ export class HostConfigComponent implements OnInit { |
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return item.isEnabled; |
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return item.isEnabled; |
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}) |
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}) |
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let config4 = `video_rate: 5
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let config4 = `video_rate: 5
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inference_buffer_second: 6 |
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inference_buffer_second: 10 |
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sources:` |
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sources:` |
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copyListOfData.forEach((item: any, index) => { |
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copyListOfData.forEach((item: any, index) => { |
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if (item.type == 3 && item.dimensionedPointsObj && item.dimensionedPointsObj.arrow.length != 0) { |
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if (item.type == 3 && item.dimensionedPointsObj && item.dimensionedPointsObj.arrow.length != 0) { |
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let arrowArr = item.dimensionedPointsObj.arrow |
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let arrowArr = item.dimensionedPointsObj.arrow |
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let str = arrowArr[1].startX + ';' + arrowArr[1].startY + ';' + arrowArr[1].endX + ';' + arrowArr[1].endY + ';' + arrowArr[0].startX + ';' + arrowArr[0].startY + ';' + arrowArr[0].endX + ';' + arrowArr[0].endY |
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let str = arrowArr[1].startX + ',' + arrowArr[1].startY + ',' + arrowArr[1].endX + ',' + arrowArr[1].endY + ',' + arrowArr[0].startX + ',' + arrowArr[0].startY + ',' + arrowArr[0].endX + ',' + arrowArr[0].endY |
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config4 += ` |
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config4 += ` |
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- name: '${item.name}' |
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- name: '${item.name}' |
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user: '${item.user}' |
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user: '${item.user}' |
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@ -305,7 +305,7 @@ sources:` |
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` |
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` |
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} else if (item.type == 2 && item.dimensionedPointsObj && item.dimensionedPointsObj.arrow.length != 0 && item.dimensionedPointsObj.arrowOfWest && item.dimensionedPointsObj.arrowOfWest.length == 0) { |
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} else if (item.type == 2 && item.dimensionedPointsObj && item.dimensionedPointsObj.arrow.length != 0 && item.dimensionedPointsObj.arrowOfWest && item.dimensionedPointsObj.arrowOfWest.length == 0) { |
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let arrowArr = item.dimensionedPointsObj.arrow |
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let arrowArr = item.dimensionedPointsObj.arrow |
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let str = arrowArr[1].startX + ';' + arrowArr[1].startY + ';' + arrowArr[1].endX + ';' + arrowArr[1].endY + ';' + arrowArr[0].startX + ';' + arrowArr[0].startY + ';' + arrowArr[0].endX + ';' + arrowArr[0].endY |
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let str = arrowArr[1].startX + ',' + arrowArr[1].startY + ',' + arrowArr[1].endX + ',' + arrowArr[1].endY + ',' + arrowArr[0].startX + ',' + arrowArr[0].startY + ',' + arrowArr[0].endX + ',' + arrowArr[0].endY |
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config4 += ` |
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config4 += ` |
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- name: '${item.name}' |
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- name: '${item.name}' |
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user: '${item.user}' |
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user: '${item.user}' |
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@ -316,10 +316,10 @@ sources:` |
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` |
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` |
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} else if (item.type == 2 && item.dimensionedPointsObj && item.dimensionedPointsObj.arrow.length != 0 && item.dimensionedPointsObj.arrowOfWest && item.dimensionedPointsObj.arrowOfWest.length != 0) { |
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} else if (item.type == 2 && item.dimensionedPointsObj && item.dimensionedPointsObj.arrow.length != 0 && item.dimensionedPointsObj.arrowOfWest && item.dimensionedPointsObj.arrowOfWest.length != 0) { |
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let arrowArr = item.dimensionedPointsObj.arrow |
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let arrowArr = item.dimensionedPointsObj.arrow |
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let str = arrowArr[1].startX + ';' + arrowArr[1].startY + ';' + arrowArr[1].endX + ';' + arrowArr[1].endY + ';' + arrowArr[0].startX + ';' + arrowArr[0].startY + ';' + arrowArr[0].endX + ';' + arrowArr[0].endY |
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let str = arrowArr[1].startX + ',' + arrowArr[1].startY + ',' + arrowArr[1].endX + ',' + arrowArr[1].endY + ',' + arrowArr[0].startX + ',' + arrowArr[0].startY + ',' + arrowArr[0].endX + ',' + arrowArr[0].endY |
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let arrowArr2 = item.dimensionedPointsObj.arrowOfWest |
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let arrowArr2 = item.dimensionedPointsObj.arrowOfWest |
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let str2 = arrowArr2[1].startX + ';' + arrowArr2[1].startY + ';' + arrowArr2[1].endX + ';' + arrowArr2[1].endY + ';' + arrowArr2[0].startX + ';' + arrowArr2[0].startY + ';' + arrowArr2[0].endX + ';' + arrowArr2[0].endY |
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let str2 = arrowArr2[1].startX + ',' + arrowArr2[1].startY + ',' + arrowArr2[1].endX + ',' + arrowArr2[1].endY + ',' + arrowArr2[0].startX + ',' + arrowArr2[0].startY + ',' + arrowArr2[0].endX + ',' + arrowArr2[0].endY |
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let str3 = '[' + str + ']' + ',' + '[' + str2 + ']' |
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let str3 = '[' + str + ',' + str2 + ']' |
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config4 += ` |
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config4 += ` |
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- name: '${item.name}' |
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- name: '${item.name}' |
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user: '${item.user}' |
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user: '${item.user}' |
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@ -552,16 +552,9 @@ ${newstr}class-id=0 |
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console.log('泄油管区域', xieyouguan) |
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console.log('泄油管区域', xieyouguan) |
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console.log('静电接地', jingdian) |
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console.log('静电接地', jingdian) |
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config2 = `# The all in one config file.
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config2 = `# The all in one config file.
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# RTSP sources |
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# type |
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# 0 ViolateArea.ENTRANCE, |
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# 1 ViolateArea.GAS_AREA, |
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# 2 ViolateArea.FUEL_AREA, |
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# 3 ViolateArea.MART, |
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# don't change the key name. |
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debug: false #when the debug is on, osd. |
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debug: false #when the debug is on, osd. |
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video_record: 3 #time to record into the .ts video |
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video_record: 15 #time to record into the .ts video |
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sources: |
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sources: |
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config: 'config/source.yaml' |
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config: 'config/source.yaml' |
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@ -572,6 +565,9 @@ tracker: |
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analytics: |
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analytics: |
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config: 'config/config_nvdsanalytics.txt' |
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config: 'config/config_nvdsanalytics.txt' |
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## 通用模型 ## |
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# 1:人物检测 |
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peoplenet: |
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peoplenet: |
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enable: true |
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enable: true |
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apply_on: -1 |
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apply_on: -1 |
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@ -583,8 +579,9 @@ peoplenet: |
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detected-min-w: 20
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detected-min-w: 20
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detected-min-h: 200 |
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detected-min-h: 200 |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/peoplenet/weights/resnet34_peoplenet_int8.etlt_b16_gpu0_int8.engine' |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/peoplenet/weights/resnet34_peoplenet_int8.etlt_b16_gpu0_int8.engine' |
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threshold: 0.8 |
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threshold: 0.3 |
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# 2:车辆检测 |
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trafficcam: |
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trafficcam: |
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enable: true |
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enable: true |
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apply_on: 0 |
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apply_on: 0 |
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@ -597,6 +594,7 @@ trafficcam: |
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detected-min-h: 100 |
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detected-min-h: 100 |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/trafficcam/weights/resnet18_trafficcamnet_pruned.etlt_b16_gpu0_int8.engine' |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/trafficcam/weights/resnet18_trafficcamnet_pruned.etlt_b16_gpu0_int8.engine' |
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# 3:人物倚靠行为 |
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actionnet: |
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actionnet: |
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enable: false |
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enable: false |
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apply_on: 1 |
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apply_on: 1 |
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@ -612,6 +610,26 @@ actionnet: |
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interval: 1 |
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interval: 1 |
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batch_size: 32 |
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batch_size: 32 |
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# 4:烟火检测 |
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fire_smoke_net: |
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enable: true |
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apply_on: -1 |
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interval: 1 |
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batch_size: 16 |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/fire_smoke_net/weights/yolov4_cspdarknet_tiny_fp16.etlt_b2_gpu0_fp16.engine' |
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threshold: 0.95 |
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# 5:抽烟打电话检测 |
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smoking_calling_net: |
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enable: true |
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apply_on: -1 |
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interval: 1 |
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batch_size: 2 |
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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' |
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## 油站专用模型 ## |
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# 1:身份判别:工装、反光衣、便衣 |
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idnet: |
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idnet: |
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enable: true |
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enable: true |
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apply_on: -1 |
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apply_on: -1 |
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@ -619,8 +637,9 @@ idnet: |
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batch_size: 2 |
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batch_size: 2 |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/idnet/weights/resnet50_idnet_fp16.etlt_b2_gpu0_fp16.engine' |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/idnet/weights/resnet50_idnet_fp16.etlt_b2_gpu0_fp16.engine' |
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# 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 |
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oilnet: |
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oilnet: |
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enable: true |
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enable: false |
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apply_on: 2 |
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apply_on: 2 |
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interval: 1 |
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interval: 1 |
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batch_size: 2
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batch_size: 2
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@ -631,21 +650,7 @@ oilnet: |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/oilnet/weights/yolov4_cspdarknet_tiny_fp16.etlt_b2_gpu0_fp16.engine' |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/oilnet/weights/yolov4_cspdarknet_tiny_fp16.etlt_b2_gpu0_fp16.engine' |
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threshold: 0.5 |
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threshold: 0.5 |
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fire_smoke_net: |
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# 3:卸油管是否连接判定 |
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enable: true |
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apply_on: -1 |
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interval: 1 |
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batch_size: 2 |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/fire_smoke_net/weights/yolov4_cspdarknet_tiny_fp16.etlt_b2_gpu0_fp16.engine' |
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threshold: 0.95 |
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smoking_calling_net: |
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enable: true |
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apply_on: -1 |
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interval: 1 |
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batch_size: 2 |
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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' |
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connet_oil: |
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connet_oil: |
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enable: true |
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enable: true |
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apply_on: 2 |
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apply_on: 2 |
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@ -656,6 +661,7 @@ connet_oil: |
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batch_size: 2 |
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batch_size: 2 |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/connet_oil/weights/resnet50_connet_oil_fp16.etlt_b2_gpu0_fp16.engine' |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/connet_oil/weights/resnet50_connet_oil_fp16.etlt_b2_gpu0_fp16.engine' |
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# 4:静电接地仪器是否连接判定 |
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connet_grounder: |
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connet_grounder: |
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enable: true |
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enable: true |
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apply_on: 2 |
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apply_on: 2 |
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@ -666,28 +672,36 @@ connet_grounder: |
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batch_size: 2 |
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batch_size: 2 |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/connet_grounder/weights/resnet50_connet_grounder_fp16.etlt_b2_gpu0_fp16.engine' |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/connet_grounder/weights/resnet50_connet_grounder_fp16.etlt_b2_gpu0_fp16.engine' |
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#new field for rule threshold |
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# 5:散装桶加油 |
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bulk_oil_net: |
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enable: true |
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apply_on: 2 |
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interval: 1 |
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batch_size: 2 |
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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' |
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threshold: 0.3 |
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# 模型阈值通用设定 |
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rule_threshold: |
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rule_threshold: |
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object_occurence_interval_second: 3 |
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object_occurence_interval_second: 3 |
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object_disappear_interval_second: 10 |
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object_disappear_interval_second: 10 |
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on_car_parking_interval_second: 1800 |
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on_car_parking_interval_second: 1800 |
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on_fire_smoke_interval_second: 5 |
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on_fire_smoke_interval_second: 5 |
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on_helmet_interval_second: 5 |
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threshold_relying_sitting: 0.4 #rolling mean confidence |
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threshold_relying_sitting: 0.4 #rolling mean confidence |
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threshold_smoking_calling: 0.3 #rolling mean confidence |
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threshold_smoking_calling: 0.3 #rolling mean confidence |
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threshold_connecting: 0.667 #rolling mean confidence |
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threshold_connecting: 0.667 #rolling mean confidence |
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threshold_identity: 0.5 #only to filter out people net error |
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threshold_identity: 0.1 #only to filter out people net error |
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threshold_helmet: 0 #num of helmet detected on a person |
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enable_seconday_model: False # secondary model (双模型) |
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threshold_secondary_model: 0.5
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secondary_model_window: 50 |
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secondary_model_path: '/opt/app/xgboost' |
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` |
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` |
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config3 = `# The all in one config file.
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config3 = `# The all in one config file.
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# RTSP sources |
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# type |
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# 0 ViolateArea.ENTRANCE, |
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# 1 ViolateArea.GAS_AREA, |
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# 2 ViolateArea.FUEL_AREA, |
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# 3 ViolateArea.MART, |
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# don't change the key name. |
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debug: false #when the debug is on, osd. |
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debug: false #when the debug is on, osd. |
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video_record: 3 #time to record into the .ts video |
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video_record: 15 #time to record into the .ts video |
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sources: |
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sources: |
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config: 'config/source.yaml' |
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config: 'config/source.yaml' |
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@ -698,6 +712,9 @@ tracker: |
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analytics: |
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analytics: |
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config: 'config/config_nvdsanalytics.txt' |
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config: 'config/config_nvdsanalytics.txt' |
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## 通用模型 ## |
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# 1:人物检测 |
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peoplenet: |
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peoplenet: |
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enable: true |
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enable: true |
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apply_on: -1 |
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apply_on: -1 |
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@ -711,6 +728,7 @@ peoplenet: |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/peoplenet/weights/resnet34_peoplenet_int8.etlt_b16_gpu0_int8.engine' |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/peoplenet/weights/resnet34_peoplenet_int8.etlt_b16_gpu0_int8.engine' |
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threshold: 0.8 |
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threshold: 0.8 |
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# 2:车辆检测 |
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trafficcam: |
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trafficcam: |
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enable: true |
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enable: true |
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apply_on: 0 |
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apply_on: 0 |
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@ -723,6 +741,7 @@ trafficcam: |
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detected-min-h: 100 |
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detected-min-h: 100 |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/trafficcam/weights/resnet18_trafficcamnet_pruned.etlt_b16_gpu0_int8.engine' |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/trafficcam/weights/resnet18_trafficcamnet_pruned.etlt_b16_gpu0_int8.engine' |
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# 3:人物倚靠行为 |
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actionnet: |
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actionnet: |
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enable: false |
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enable: false |
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apply_on: 1 |
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apply_on: 1 |
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@ -738,6 +757,26 @@ actionnet: |
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interval: 1 |
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interval: 1 |
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batch_size: 32 |
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batch_size: 32 |
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# 4:烟火检测 |
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fire_smoke_net: |
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enable: true |
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apply_on: -1 |
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interval: 1 |
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batch_size: 16 |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/fire_smoke_net/weights/yolov4_cspdarknet_tiny_fp16.etlt_b2_gpu0_fp32.engine' |
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threshold: 0.95 |
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# 5:抽烟打电话检测 |
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smoking_calling_net: |
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enable: true |
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apply_on: -1 |
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interval: 1 |
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batch_size: 2 |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/smoking_calling_net/weights/resnet50_smoking_calling_net_fp16.etlt_b2_gpu0_fp32.engine' |
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## 油站专用模型 ## |
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# 1:身份判别:工装、反光衣、便衣 |
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idnet: |
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idnet: |
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enable: true |
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enable: true |
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apply_on: -1 |
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apply_on: -1 |
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@ -745,8 +784,9 @@ idnet: |
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batch_size: 2 |
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batch_size: 2 |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/idnet/weights/resnet50_idnet_fp16.etlt_b2_gpu0_fp32.engine' |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/idnet/weights/resnet50_idnet_fp16.etlt_b2_gpu0_fp32.engine' |
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# 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 |
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oilnet: |
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oilnet: |
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enable: true |
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enable: false |
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apply_on: 2 |
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apply_on: 2 |
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interval: 1 |
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interval: 1 |
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batch_size: 2
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batch_size: 2
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@ -757,21 +797,7 @@ oilnet: |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/oilnet/weights/yolov4_cspdarknet_tiny_fp16.etlt_b2_gpu0_fp32.engine' |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/oilnet/weights/yolov4_cspdarknet_tiny_fp16.etlt_b2_gpu0_fp32.engine' |
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threshold: 0.5 |
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threshold: 0.5 |
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fire_smoke_net: |
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# 3:卸油管是否连接判定 |
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enable: true |
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apply_on: -1 |
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interval: 1 |
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batch_size: 2 |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/fire_smoke_net/weights/yolov4_cspdarknet_tiny_fp16.etlt_b2_gpu0_fp32.engine' |
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threshold: 0.95 |
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smoking_calling_net: |
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enable: true |
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apply_on: -1 |
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interval: 1 |
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batch_size: 2 |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/smoking_calling_net/weights/resnet50_smoking_calling_net_fp16.etlt_b2_gpu0_fp32.engine' |
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connet_oil: |
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connet_oil: |
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enable: true |
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enable: true |
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apply_on: 2 |
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apply_on: 2 |
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@ -782,6 +808,7 @@ connet_oil: |
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batch_size: 2 |
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batch_size: 2 |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/connet_oil/weights/resnet50_connet_oil_fp16.etlt_b2_gpu0_fp32.engine' |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/connet_oil/weights/resnet50_connet_oil_fp16.etlt_b2_gpu0_fp32.engine' |
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# 4:静电接地仪器是否连接判定 |
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connet_grounder: |
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connet_grounder: |
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enable: true |
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enable: true |
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apply_on: 2 |
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apply_on: 2 |
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@ -792,16 +819,31 @@ connet_grounder: |
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batch_size: 2 |
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batch_size: 2 |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/connet_grounder/weights/resnet50_connet_grounder_fp16.etlt_b2_gpu0_fp32.engine' |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/connet_grounder/weights/resnet50_connet_grounder_fp16.etlt_b2_gpu0_fp32.engine' |
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#new field for rule threshold |
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# 5:散装桶加油 |
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bulk_oil_net: |
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enable: true |
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apply_on: 2 |
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interval: 1 |
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batch_size: 2 |
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model_engine_file: '/opt/nvidia/deepstream/deepstream-6.0/sources/project/models/bulk_oil_net/weights/yolov4_cspdarknet_tiny_fp16.etlt_b2_gpu0_fp32.engine' |
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threshold: 0.3 |
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#模型阈值通用设定 |
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rule_threshold: |
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rule_threshold: |
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object_occurence_interval_second: 3 |
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object_occurence_interval_second: 3 |
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object_disappear_interval_second: 10 |
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object_disappear_interval_second: 10 |
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on_car_parking_interval_second: 1800 |
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on_car_parking_interval_second: 1800 |
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on_fire_smoke_interval_second: 5 |
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on_fire_smoke_interval_second: 5 |
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on_helmet_interval_second: 5 |
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threshold_relying_sitting: 0.4 #rolling mean confidence |
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threshold_relying_sitting: 0.4 #rolling mean confidence |
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threshold_smoking_calling: 0.3 #rolling mean confidence |
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threshold_smoking_calling: 0.3 #rolling mean confidence |
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threshold_connecting: 0.667 #rolling mean confidence |
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threshold_connecting: 0.667 #rolling mean confidence |
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threshold_identity: 0.5 #only to filter out people net error |
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threshold_identity: 0.1 #only to filter out people net error |
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threshold_helmet: 0 #num of helmet detected on a person |
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enable_seconday_model: False # secondary model (双模型) |
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threshold_secondary_model: 0.5
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secondary_model_window: 50 |
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secondary_model_path: '/opt/app/xgboost' |
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` |
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` |
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sessionStorage.setItem('config1', config1) |
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sessionStorage.setItem('config1', config1) |
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