291 lines
16 KiB
YAML
291 lines
16 KiB
YAML
#本地存储方法和pt文件的对应关系，避免走数据库
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# 包括func_description 在内的前面三个参数是方法级别的，只跟方法相关；后面的参数才跟模型相关
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local_func:
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- model_func_id: 100000 #对应到postgres 表的model_func_Id字段
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filter_cls: [ 0,1,5 ] # 增加过滤字段，仅识别模型中的哪几个字段
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func_description: "当前方法主要用作xxxxxxxx"
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yolo_version: "11"
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path: "pt/best.pt"
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cls_index: [ 0,1,2,3,4,5,6,7,8,9 ]
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cls: [ "pedestrian","people","bicycle","car","van","truck","tricycle","awning-tricycle","bus","motor" ]
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cls_en: [ "人","人","自行车","汽车","厢型车","卡车","三轮车","三轮车","公交","摩托" ]
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cls_description: "人、车识别的模型"
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- model_func_id: 100008 #对应到postgres 表的model_func_Id字段
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filter_cls: [ 0,1,2,3,4 ] # 增加过滤字段，仅识别模型中的哪几个字段
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func_description: "人员配置统计,基于安全帽的颜色，做人员配置统计"
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yolo_version: "11"
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path: "pt/gdaq.pt"
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cls_index: [ 0,1,2,3,4,5,6,7,8,9 ]
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cls: [ "RedHat","WhiteHat","BlueHat","YellowHat","NoHat","Harness","NoHarness","Rail","BrokenRail","TrashPile" ]
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cls_en: [ "红帽","白帽","蓝帽","黄帽","未带安全帽","安全带","没系安全带","围栏","破损围栏","乱堆放" ]
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cls_description: "人员配置统计,基于安全帽的颜色，做人员配置统计"
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- model_func_id: 100052 #对应到postgres 表的model_func_Id字段
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filter_cls: [ 0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16 ] # 增加过滤字段，仅识别模型中的哪几个字段
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func_description: "挖掘机,自卸卡车,压路机,移动式起重机,固定式起重机,轮式装载机,混凝土搅拌车,反铲式装载机,推土机,平地机"
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yolo_version: "11"
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path: "pt/GDCL.pt"
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cls_index: [ 0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16 ]
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cls: [ "Excavator","Flatbed","Truck","DumpTruck","Roller","CraneMobile","CraneTruck","CraneTower","CraneFixed","LoaderWheel","CementTanker","ConcreteMixer","MixerTruck","BackhoeLoader","LoaderWheel","Grader","PileDriver" ]
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cls_en: [ "挖掘机", "卡车", "卡车", "卡车", " 压路机", "起重机","起重机", "塔吊", "塔吊", "塔吊", "水泥罐车", "水泥罐车",
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"水泥罐车", "挖土机", "推土机", "地坪机", "打桩机" ]
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cls_description: "挖掘机,自卸卡车,压路机,移动式起重机,固定式起重机,轮式装载机,混凝土搅拌车,反铲式装载机,推土机,平地机"
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- model_func_id: 100091 #对应到postgres 表的model_func_Id字段
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filter_cls: [ 4 ] # 增加过滤字段，仅识别模型中的哪几个字段
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func_description: "统计未佩戴安全帽"
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yolo_version: "11"
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path: "pt/gdaq.pt"
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cls_index: [ 0,1,2,3,4,5,6,7,8,9 ]
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cls: [ "RedHat","WhiteHat","BlueHat","YellowHat","NoHat","Harness","NoHarness","Rail","BrokenRail","TrashPile" ]
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cls_en: [ "红帽","白帽","蓝帽","黄帽","未带安全帽","安全带","没系安全带","围栏","破损围栏","乱堆放" ]
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cls_description: "人员配置统计,基于安全帽的颜色，做人员配置统计"
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#当前是临时用法，后续还是查库查表
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- model_func_id: 101901 #对应到postgres 表的model_func_Id字段
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filter_cls: [ 0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16 ] # 增加过滤字段，仅识别模型中的哪几个字段
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func_description: "挖掘机,自卸卡车,压路机,移动式起重机,固定式起重机,轮式装载机,混凝土搅拌车,反铲式装载机,推土机,平地机"
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yolo_version: "11"
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path: "pt/GDCL.pt"
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cls_index: [ 0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16 ]
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cls: [ "Excavator","Flatbed","Truck","DumpTruck","Roller","CraneMobile","CraneTruck","CraneTower","CraneFixed","LoaderWheel","CementTanker","ConcreteMixer","MixerTruck","BackhoeLoader","LoaderWheel","Grader","PileDriver" ]
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cls_en: [ "挖掘机", "卡车", "卡车", "卡车", " 压路机", "起重机","起重机", "塔吊", "塔吊", "塔吊", "水泥罐车", "水泥罐车",
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"水泥罐车", "挖土机", "推土机", "地坪机", "打桩机" ]
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cls_description: "挖掘机,自卸卡车,压路机,移动式起重机,固定式起重机,轮式装载机,混凝土搅拌车,反铲式装载机,推土机,平地机"
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#当前是临时用法，后续还是查库查表
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- model_func_id: 101101 #对应到postgres 表的model_func_Id字段
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filter_cls: [ 0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16 ] # 增加过滤字段，仅识别模型中的哪几个字段
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func_description: "挖掘机,自卸卡车,压路机,移动式起重机,固定式起重机,轮式装载机,混凝土搅拌车,反铲式装载机,推土机,平地机"
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yolo_version: "11"
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path: "pt/GDCL.pt"
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cls_index: [ 0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16 ]
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cls: [ "Excavator","Flatbed","Truck","DumpTruck","Roller","CraneMobile","CraneTruck","CraneTower","CraneFixed","LoaderWheel","CementTanker","ConcreteMixer","MixerTruck","BackhoeLoader","LoaderWheel","Grader","PileDriver" ]
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cls_en: [ "挖掘机", "卡车", "卡车", "卡车", " 压路机", "起重机","起重机", "塔吊", "塔吊", "塔吊", "水泥罐车", "水泥罐车",
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"水泥罐车", "挖土机", "推土机", "地坪机", "打桩机" ]
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cls_description: "挖掘机,自卸卡车,压路机,移动式起重机,固定式起重机,轮式装载机,混凝土搅拌车,反铲式装载机,推土机,平地机"
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- model_func_id: 101102 #对应到postgres 表的model_func_Id字段
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filter_cls: [ 0,1,2,3,4,5,6,7,8,9 ] # 增加过滤字段，仅识别模型中的哪几个字段
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func_description: "当前方法主要用作xxxxxxxx"
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yolo_version: "11"
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path: "pt/best.pt"
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cls_index: [ 0,1,2,3,4,5,6,7,8,9 ]
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cls: [ "pedestrian","people","bicycle","car","van"," truck","tricycle","awning-tricycle","bus","motor" ]
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cls_en: [ "人","人","自行车","汽车","厢型车","卡车","三轮车","三轮车","公交","摩托" ]
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cls_description: "人、车识别的模型"
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- model_func_id: 101201 #对应到postgres 表的model_func_Id字段
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filter_cls: [ 0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16 ] # 增加过滤字段，仅识别模型中的哪几个字段
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func_description: "挖掘机,自卸卡车,压路机,移动式起重机,固定式起重机,轮式装载机,混凝土搅拌车,反铲式装载机,推土机,平地机"
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yolo_version: "11"
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path: "pt/GDCL.pt"
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cls_index: [ 0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16 ]
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cls: [ "Excavator","Flatbed","Truck","DumpTruck","Roller","CraneMobile","CraneTruck","CraneTower","CraneFixed","LoaderWheel","CementTanker","ConcreteMixer","MixerTruck","BackhoeLoader","LoaderWheel","Grader","PileDriver" ]
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cls_en: [ "挖掘机", "卡车", "卡车", "卡车", " 压路机", "起重机","起重机", "塔吊", "塔吊", "塔吊", "水泥罐车", "水泥罐车",
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"水泥罐车", "挖土机", "推土机", "地坪机", "打桩机" ]
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cls_description: "挖掘机,自卸卡车,压路机,移动式起重机,固定式起重机,轮式装载机,混凝土搅拌车,反铲式装载机,推土机,平地机"
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#当前是临时用法，后续还是查库查表
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- model_func_id: 101202 #对应到postgres 表的model_func_Id字段
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filter_cls: [ 0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16 ] # 增加过滤字段，仅识别模型中的哪几个字段
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func_description: "挖掘机,自卸卡车,压路机,移动式起重机,固定式起重机,轮式装载机,混凝土搅拌车,反铲式装载机,推土机,平地机"
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yolo_version: "11"
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path: "pt/GDCL.pt"
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cls_index: [ 0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16 ]
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cls: [ "Excavator","Flatbed","Truck","DumpTruck","Roller","CraneMobile","CraneTruck","CraneTower","CraneFixed","LoaderWheel","CementTanker","ConcreteMixer","MixerTruck","BackhoeLoader","LoaderWheel","Grader","PileDriver" ]
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cls_en: [ "挖掘机", "卡车", "卡车", "卡车", " 压路机", "起重机","起重机", "塔吊", "塔吊", "塔吊", "水泥罐车", "水泥罐车",
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"水泥罐车", "挖土机", "推土机", "地坪机", "打桩机" ]
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cls_description: "挖掘机,自卸卡车,压路机,移动式起重机,固定式起重机,轮式装载机,混凝土搅拌车,反铲式装载机,推土机,平地机"
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- model_func_id: 101203 #对应到postgres 表的model_func_Id字段
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filter_cls: [ 0,1,2,3,4,5,6,7,8,9 ] # 增加过滤字段，仅识别模型中的哪几个字段
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func_description: "当前方法主要用作xxxxxxxx"
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yolo_version: "11"
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path: "pt/best.pt"
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cls_index: [ 0,1,2,3,4,5,6,7,8,9 ]
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cls: [ "pedestrian","people","bicycle","car","van"," truck","tricycle","awning-tricycle","bus","motor" ]
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cls_en: [ "人","人","自行车","汽车","厢型车","卡车","三轮车","三轮车","公交","摩托" ]
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cls_description: "人、车识别的模型"
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#
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- model_func_id: 100001 #对应到postgres 表的model_func_Id字段
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filter_cls: [0,1,2,3,4,5,6,7,8,9] # 增加过滤字段，仅识别模型中的哪几个字段
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func_description: "当前方法主要用作xxxxxxxx"
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yolo_version: "11"
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path: "pt/best.pt"
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cls_index: [ 0,1,2,3,4,5,6,7,8,9 ]
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cls: [ "pedestrian","people","bicycle","car","van"," truck","tricycle","awning-tricycle","bus","motor" ]
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cls_en: [ "人","人","自行车","汽车","厢型车","卡车","三轮车","三轮车","公交","摩托" ]
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cls_description: "人、车识别的模型"
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- model_func_id: 100002 #对应到postgres 表的model_func_Id字段
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filter_cls: [ 0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16 ] # 增加过滤字段，仅识别模型中的哪几个字段
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func_description: "挖掘机,自卸卡车,压路机,移动式起重机,固定式起重机,轮式装载机,混凝土搅拌车,反铲式装载机,推土机,平地机"
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yolo_version: "11"
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path: "pt/GDCL.pt"
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cls_index: [ 0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16 ]
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cls: [ "Excavator","Flatbed","Truck","DumpTruck","Roller","CraneMobile","CraneTruck","CraneTower","CraneFixed","LoaderWheel","CementTanker","ConcreteMixer","MixerTruck","BackhoeLoader","LoaderWheel","Grader","PileDriver" ]
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cls_en: [ "挖掘机", "卡车", "卡车", "卡车", " 压路机", "起重机","起重机", "塔吊", "塔吊", "塔吊", "水泥罐车", "水泥罐车",
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"水泥罐车", "挖土机", "推土机", "地坪机", "打桩机" ]
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cls_description: "挖掘机,自卸卡车,压路机,移动式起重机,固定式起重机,轮式装载机,混凝土搅拌车,反铲式装载机,推土机,平地机"
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- model_func_id: 100003 #对应到postgres 表的model_func_Id字段
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filter_cls: [ 4 ] # 增加过滤字段，仅识别模型中的哪几个字段
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func_description: "统计未佩戴安全帽"
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yolo_version: "11"
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path: "pt/gdaq.pt"
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cls_index: [ 0,1,2,3,4,5,6,7,8,9 ]
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cls: [ "RedHat","WhiteHat","BlueHat","YellowHat","NoHat","Harness","NoHarness","Rail","BrokenRail","TrashPile" ]
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cls_en: [ "红帽","白帽","蓝帽","黄帽","未带安全帽","安全带","没系安全带","围栏","破损围栏","乱堆放" ]
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cls_description: "判断安全帽"
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- model_func_id: 100004 #对应到postgres 表的model_func_Id字段
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filter_cls: [ 0,1,2,3,4,5 ] # 增加过滤字段，仅识别模型中的哪几个字段
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func_description: "当前方法主要用作xxxxxxxx"
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yolo_version: "11"
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path: "pt/build.pt"
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cls: [ "honeycomb&rough_surface","peeling&chipping","cavity&hole","rust on rebar","damage&exposed rebar","creck"]
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cls_index: [ 0,1,2,3,4,5 ]
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cls_en: [ "蜂窝","剥落","空洞","钢筋锈蚀","破损","裂缝"]
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cls_description: "之前的模型，判断桥梁损害"
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- model_func_id: 100005 #对应到postgres 表的model_func_Id字段
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filter_cls: [ 0 ] # 增加过滤字段，仅识别模型中的哪几个字段
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func_description: "当前方法主要用作xxxxxxxx"
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yolo_version: "11"
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path: "pt/fire.pt"
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cls: [ "smoke"]
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cls_index: [ 0 ]
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cls_en: [ "烟雾"]
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cls_description: "之前的模型，判断烟火"
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- model_func_id: 100006 #对应到postgres 表的model_func_Id字段
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filter_cls: [ 0,1,2,3,4,5,6,7,8,9 ] # 增加过滤字段，仅识别模型中的哪几个字段
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func_description: "当前方法主要用作xxxxxxxx"
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yolo_version: "11"
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path: "pt/hwgf.pt"
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cls: [ "dyrb","dmjrb","dyrb_ycdw","dmjrb_ycdw","ycdw","dyrb_zd","zd_hw","dmjrb_zd","ycdw_zd","ejgdl","ygfs_hw","ejgdl_ycdw"]
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cls_index: [ 0,1,2,3,4,5 ,6,7,8,9]
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cls_en: [ "单一热班","大面积热斑","单一热班&异常低温","大面积热班&异常低温","异常低温","单一热斑&遮挡","异常低温&热斑","二极管短路","阳光反射","二极管短路&异常低温"]
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cls_description: "之前的模型，基于红外判断光伏情况"
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- model_func_id: 100007 #对应到postgres 表的model_func_Id字段
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filter_cls: [ 0,1,2,3 ] # 增加过滤字段，仅识别模型中的哪几个字段
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func_description: "当前方法主要用作xxxxxxxx"
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yolo_version: "11"
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path: "pt/HWRC.pt"
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cls: [ "human","track","car","bicycle"]
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cls_index: [ 0,1,2,3]
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cls_en: [ "人","卡车","车","自行车"]
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cls_description: "之前的模型，判断红外人车"
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- model_func_id: 100008 #对应到postgres 表的model_func_Id字段
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filter_cls: [ 0,1,2,3,4,5,6,7,8,9 ] # 增加过滤字段，仅识别模型中的哪几个字段
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func_description: "当前方法主要用作xxxxxxxx"
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yolo_version: "11"
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path: "pt/KeJianGangSolarProblems.pt"
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cls: [ "ygfs","zw","yyzd_zw","ns","ygfs_yyzd","yyzd_ns","zw_ns","gfbzjbx","gfbqs","mbsl"]
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cls_index: [ 0,1,2,3,4,5 ,6,7,8,9]
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cls_en: ["遮挡","阳光反射","脏污","遮挡&脏污","鸟粪","阳光反射&遮挡","遮挡&鸟粪","脏污&鸟粪","光伏板变形","光伏板缺失","面板破裂"]
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cls_description: "之前的模型，判断光伏相关"
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- model_func_id: 100009 #对应到postgres 表的model_func_Id字段
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filter_cls: [ 0,1 ] # 增加过滤字段，仅识别模型中的哪几个字段
|
||
func_description: "当前方法主要用作xxxxxxxx"
|
||
yolo_version: "11"
|
||
path: "pt/smoke.pt"
|
||
cls: [ "smoke","hote(infrared)&fire"]
|
||
cls_index: [ 0,1]
|
||
cls_en: [ "烟","火"]
|
||
cls_description: "之前的模型，判断烟火"
|
||
|
||
|
||
|
||
- model_func_id: 100010 #对应到postgres 表的model_func_Id字段
|
||
filter_cls: [ 0 ] # 增加过滤字段，仅识别模型中的哪几个字段
|
||
func_description: "当前方法主要用作xxxxxxxx"
|
||
yolo_version: "11"
|
||
path: "pt/trash.pt"
|
||
cls: [ "垃圾"] #当前模型确实中文
|
||
cls_index: [ 0]
|
||
cls_en: [ "垃圾"]
|
||
cls_description: "之前的模型，判断垃圾"
|
||
|
||
|
||
|
||
- model_func_id: 100011 #对应到postgres 表的model_func_Id字段
|
||
filter_cls: [ 0 ] # 增加过滤字段，仅识别模型中的哪几个字段
|
||
func_description: "当前方法主要用作xxxxxxxx"
|
||
yolo_version: "11"
|
||
path: "pt/tree.pt"
|
||
cls: [ "unhealthy"]
|
||
cls_index: [ 0]
|
||
cls_en: [ "不健康"]
|
||
cls_description: "之前的模型，判断病树"
|
||
|
||
|
||
- model_func_id: 100012 #对应到postgres 表的model_func_Id字段
|
||
filter_cls: [ 0,1 ] # 增加过滤字段，仅识别模型中的哪几个字段
|
||
func_description: "当前方法主要用作xxxxxxxx"
|
||
yolo_version: "11"
|
||
path: "pt/yanwu2.pt"
|
||
cls: [ "YanWu","ReYuan" ]
|
||
cls_index: [ 0,1]
|
||
cls_en: [ "烟雾","热源"]
|
||
cls_description: "之前的模型，判断烟雾"
|
||
|
||
|
||
|
||
- model_func_id: 100013 #对应到postgres 表的model_func_Id字段
|
||
filter_cls: [ 0,1,2,3,4,5 ] # 增加过滤字段，仅识别模型中的哪几个字段
|
||
func_description: "当前方法主要用作xxxxxxxx"
|
||
yolo_version: "11"
|
||
path: "pt/LF.pt"
|
||
cls: [ "鳄鱼纹裂缝","纵向裂缝","斜裂缝","坑洞","修补","横向裂缝"] #当前模型确实中文
|
||
cls_index: [ 0,1,2,3,4,5]
|
||
cls_en: [ "鳄鱼纹裂缝","纵向裂缝","斜裂缝","坑洞","修补","横向裂缝"]
|
||
cls_description: "之前的模型，判断裂缝"
|
||
|
||
|
||
- model_func_id: 100014 #对应到postgres 表的model_func_Id字段
|
||
filter_cls: [ 0] # 0
|
||
func_description: "当前方法用作判断是否是否带帽子(鸭舌帽也算帽子)"
|
||
yolo_version: "11"
|
||
path: "pt/gdaq_hat0903_background.pt"
|
||
# path: "pt/yolo11m_gdaq_hat_0902.pt"
|
||
cls: [ "NoHat","Hat"] #当前模型确实中文
|
||
cls_index: [ 0,1]
|
||
cls_en: [ "没带安全帽","安全帽"]
|
||
cls_description: "当前方法用作判断是否是否带帽子(鸭舌帽也算帽子)"
|