Day35 - 删除P5检测头+添加P2检测头（P234）在FLIR上的表现

yolov5n/s/m和yolov8n/s删除P5检测头+添加P2检测头,在FLIR上训练200epochs

• Yolov5n-p234

  Parameters: 1.956M

  Class	Precision	Recall	mAP50	mAP50-95
  all	0.553	0.491	0.504	0.304
  person	0.792	0.709	0.8	0.463
  bike	0.461	0.465	0.424	0.259
  car	0.815	0.786	0.861	0.616
  motor	0.565	0.527	0.596	0.304
  bus	0.706	0.469	0.606	0.416
  truck	0.231	0.413	0.148	0.0833
  light	0.697	0.483	0.559	0.273
  other vehicle	0.157	0.0794	0.0391	0.0146

• Yolov5s-p234

  Parameters: 6.273M

  Class	Precision	Recall	mAP50	mAP50-95
  all	0.605	0.531	0.563	0.349
  person	0.837	0.733	0.834	0.5
  bike	0.507	0.518	0.513	0.316
  car	0.845	0.827	0.889	0.65
  motor	0.717	0.552	0.644	0.334
  bus	0.763	0.521	0.662	0.458
  truck	0.263	0.435	0.262	0.192
  light	0.748	0.582	0.642	0.318
  other vehicle	0.162	0.0794	0.0597	0.0218

• Yolov5m-p234

  Parameters: 17.162M

  Class	Precision	Recall	mAP50	mAP50-95
  all	0.649	0.572	0.596	0.381
  person	0.845	0.755	0.846	0.527
  bike	0.631	0.565	0.553	0.355
  car	0.841	0.844	0.899	0.668
  motor	0.716	0.673	0.739	0.415
  bus	0.751	0.547	0.682	0.497
  truck	0.356	0.435	0.263	0.188
  light	0.784	0.594	0.672	0.339
  other vehicle	0.272	0.166	0.117	0.0596

• Yolov8n-p234

  Parameters: 2.332M

  Class	Precision	Recall	mAP50	mAP50-95
  all	0.615	0.49	0.527	0.32
  person	0.821	0.684	0.799	0.466
  bike	0.486	0.465	0.436	0.254
  car	0.851	0.778	0.867	0.623
  motor	0.848	0.564	0.643	0.345
  bus	0.824	0.464	0.643	0.435
  truck	0.283	0.457	0.216	0.145
  light	0.737	0.481	0.574	0.277
  other vehicle	0.0679	0.0317	0.0342	0.015

• Yolov8s-p234

  Parameters: 7.781M

  Class	Precision	Recall	mAP50	mAP50-95
  all	0.666	0.508	0.57	0.356
  person	0.878	0.69	0.836	0.503
  bike	0.51	0.494	0.472	0.304
  car	0.887	0.798	0.889	0.65
  motor	0.815	0.582	0.692	0.377
  bus	0.866	0.506	0.695	0.484
  truck	0.324	0.375	0.242	0.17
  light	0.81	0.539	0.649	0.32
  other vehicle	0.242	0.0794	0.0862	0.0383