yolov5系列自诞生已经持续迭代了很多个版本了，目前官方开发者迭代的最新版本是v6.2，已经覆盖了分类、检测盒分割三大主流CV任务了，基于yolov5融合各种tricks是很多开发者或者是学生喜欢做的事情，基于yolov5也已经诞生了很多学术文章了，bifpn是一种比较有效的特征融合技术，最早在efficientnet中提出，之后很多网络也都有尝试进行融合，今天正好有时间就想着，基于yolov5来开发融合bifpn的目标检测模型，用于隧道内的裂缝裂痕检测。
首先看下最终的效果图，如下所示：
为了整体直观，这里专门是开发了对应的界面，方便使用的。
完整项目截图如下所示：
下表是对整个项目中各个文件的介绍说明：
文件名称文件说明dataset/数据集目录models/模型配置目录runs/模型结果目录utils/公共组件目录data/数据参数目录weights/预训练权重目录app.gifapp效果动图demo.gif检测样例动图detect.py检测推理模块export.py模型转化模块guiAPP.pyAPP模块inference.py离线推理精简模块logs.out训练日志startAPP.bat双击启动APP脚本test.jpg测试样例图片train.py训练模块val.py评估模块yolov5s.onnxyolov5s原生模型yolov5s.ptyolov5s原生模型yolov5s-bifpn.onnxyolov5s-bifpn模型yolov5s-bifpn.ptyolov5s-bifpn模型
data目录如下所示：
logo是用于界面的这个不用管，可以根据自己需要直接替换接口，self.yaml是我们编写的用于训练的数据配置，如下：
其他的都是项目自带的这里就不再介绍了。
dataset是我们构建的训练集-测试集目录。数据样例如下所示：
models目录如下所示：
yolov5s.yaml和yolov5s_bifpn.yaml分别表示原生的yolov5s模型和融合bifpn的yolov5s模型，这里以原生的yolov5s为例，如下：
这里需要修改nc。
runs是项目运行自动创建的结果存储目录。
utils是项目公用组件目录。
weights是用于存放预训练权重的目录。
启动train.py模块即可执行模型的训练计算，日志输出如下：
Starting training for 100 epochs...Epoch gpu_mem box obj cls labels img_size0%| | 0/59 [00:00<?, ?it/s]0/99 6.29G 0.122 0.0985 0 611 640: 0%| | 0/59 [00:03<?, ?it/s]0/99 6.29G 0.122 0.0985 0 611 640: 2%|▏ | 1/59 [00:05<05:28, 5.67s/it]0/99 6.35G 0.1225 0.1005 0 699 640: 2%|▏ | 1/59 [00:09<05:28, 5.67s/it]0/99 6.35G 0.1225 0.1005 0 699 640: 3%|▎ | 2/59 [00:09<04:08, 4.36s/it]0/99 6.35G 0.1221 0.1014 0 655 640: 3%|▎ | 2/59 [00:12<04:08, 4.36s/it]0/99 6.35G 0.1221 0.1014 0 655 640: 5%|▌ | 3/59 [00:12<03:39, 3.92s/it]0/99 6.35G 0.1219 0.1022 0 671 640: 5%|▌ | 3/59 [00:15<03:39, 3.92s/it]0/99 6.35G 0.1219 0.1022 0 671 640: 7%|▋ | 4/59 [00:15<03:24, 3.72s/it]0/99 6.35G 0.1216 0.1006 0 573 640: 7%|▋ | 4/59 [00:19<03:24, 3.72s/it]0/99 6.35G 0.1216 0.1006 0 573 640: 8%|▊ | 5/59 [00:19<03:18, 3.68s/it]0/99 6.35G 0.1216 0.1013 0 676 640: 8%|▊ | 5/59 [00:23<03:18, 3.68s/it]0/99 6.35G 0.1216 0.1013 0 676 640: 10%|█ | 6/59 [00:23<03:15, 3.69s/it]0/99 6.35G 0.1215 0.1015 0 688 640: 10%|█ | 6/59 [00:26<03:15, 3.69s/it]0/99 6.35G 0.1215 0.1015 0 688 640: 12%|█▏ | 7/59 [00:26<03:07, 3.61s/it]0/99 6.35G 0.1213 0.1026 0 710 640: 12%|█▏ | 7/59 [00:29<03:07, 3.61s/it]0/99 6.35G 0.1213 0.1026 0 710 640: 14%|█▎ | 8/59 [00:29<02:59, 3.51s/it]0/99 6.35G 0.121 0.1038 0 701 640: 14%|█▎ | 8/59 [00:33<02:59, 3.51s/it]0/99 6.35G 0.121 0.1038 0 701 640: 15%|█▌ | 9/59 [00:33<02:52, 3.45s/it]0/99 6.35G 0.1208 0.1039 0 624 640: 15%|█▌ | 9/59 [00:36<02:52, 3.45s/it]0/99 6.35G 0.1208 0.1039 0 624 640: 17%|█▋ | 10/59 [00:36<02:46, 3.40s/it]0/99 6.35G 0.1207 0.1047 0 812 640: 17%|█▋ | 10/59 [00:40<02:46, 3.40s/it]0/99 6.35G 0.1207 0.1047 0 812 640: 19%|█▊ | 11/59 [00:40<02:45, 3.44s/it]0/99 6.35G 0.1203 0.1041 0 537 640: 19%|█▊ | 11/59 [00:43<02:45, 3.44s/it]0/99 6.35G 0.1203 0.1041 0 537 640: 20%|██ | 12/59 [00:43<02:41, 3.44s/it]0/99 6.35G 0.1197 0.1042 0 537 640: 20%|██ | 12/59 [00:46<02:41, 3.44s/it]0/99 6.35G 0.1197 0.1042 0 537 640: 22%|██▏ | 13/59 [00:46<02:36, 3.41s/it]0/99 6.35G 0.1193 0.1054 0 650 640: 22%|██▏ | 13/59 [00:50<02:36, 3.41s/it]0/99 6.35G 0.1193 0.1054 0 650 640: 24%|██▎ | 14/59 [00:50<02:32, 3.38s/it]0/99 6.35G 0.1189 0.105 0 549 640: 24%|██▎ | 14/59 [00:53<02:32, 3.38s/it]0/99 6.35G 0.1189 0.105 0 549 640: 25%|██▌ | 15/59 [00:53<02:31, 3.44s/it]0/99 6.35G 0.1189 0.1053 0 767 640: 25%|██▌ | 15/59 [00:57<02:31, 3.44s/it]0/99 6.35G 0.1189 0.1053 0 767 640: 27%|██▋ | 16/59 [00:57<02:30, 3.51s/it]0/99 6.35G 0.1185 0.1055 0 634 640: 27%|██▋ | 16/59 [01:00<02:30, 3.51s/it]0/99 6.35G 0.1185 0.1055 0 634 640: 29%|██▉ | 17/59 [01:00<02:26, 3.48s/it]0/99 6.35G 0.1181 0.1054 0 597 640: 29%|██▉ | 17/59 [01:04<02:26, 3.48s/it]0/99 6.35G 0.1181 0.1054 0 597 640: 31%|███ | 18/59 [01:04<02:20, 3.43s/it]0/99 6.35G 0.1179 0.1065 0 794 640: 31%|███ | 18/59 [01:07<02:20, 3.43s/it]0/99 6.35G 0.1179 0.1065 0 794 640: 32%|███▏ | 19/59 [01:07<02:16, 3.40s/it]0/99 6.35G 0.1175 0.1059 0 545 640: 32%|███▏ | 19/59 [01:10<02:16, 3.40s/it]0/99 6.35G 0.1175 0.1059 0 545 640: 34%|███▍ | 20/59 [01:10<02:11, 3.38s/it]0/99 6.35G 0.1171 0.1052 0 522 640: 34%|███▍ | 20/59 [01:14<02:11, 3.38s/it]0/99 6.35G 0.1171 0.1052 0 522 640: 36%|███▌ | 21/59 [01:14<02:07, 3.35s/it]0/99 6.35G 0.1167 0.1047 0 505 640: 36%|███▌ | 21/59 [01:17<02:07, 3.35s/it]0/99 6.35G 0.1167 0.1047 0 505 640: 37%|███▋ | 22/59 [01:17<02:05, 3.38s/it]0/99 6.35G 0.1164 0.1052 0 697 640: 37%|███▋ | 22/59 [01:21<02:05, 3.38s/it]0/99 6.35G 0.1164 0.1052 0 697 640: 39%|███▉ | 23/59 [01:21<02:04, 3.47s/it]0/99 6.35G 0.1161 0.1057 0 765 640: 39%|███▉ | 23/59 [01:24<02:04, 3.47s/it]0/99 6.35G 0.1161 0.1057 0 765 640: 41%|████ | 24/59 [01:24<02:02, 3.50s/it]0/99 6.35G 0.1158 0.1062 0 722 640: 41%|████ | 24/59 [01:28<02:02, 3.50s/it]0/99 6.35G 0.1158 0.1062 0 722 640: 42%|████▏ | 25/59 [01:28<01:56, 3.43s/it]0/99 6.35G 0.1155 0.1062 0 653 640: 42%|████▏ | 25/59 [01:31<01:56, 3.43s/it]0/99 6.35G 0.1155 0.1062 0 653 640: 44%|████▍ | 26/59 [01:31<01:52, 3.40s/it]0/99 6.35G 0.1152 0.1061 0 693 640: 44%|████▍ | 26/59 [01:34<01:52, 3.40s/it]0/99 6.35G 0.1152 0.1061 0 693 640: 46%|████▌ | 27/59 [01:34<01:47, 3.37s/it]0/99 6.35G 0.1149 0.1056 0 629 640: 46%|████▌ | 27/59 [01:38<01:47, 3.37s/it]0/99 6.35G 0.1149 0.1056 0 629 640: 47%|████▋ | 28/59 [01:38<01:43, 3.35s/it]0/99 6.35G 0.1146 0.105 0 603 640: 47%|████▋ | 28/59 [01:41<01:43, 3.35s/it]0/99 6.35G 0.1146 0.105 0 603 640: 49%|████▉ | 29/59 [01:41<01:40, 3.35s/it]0/99 6.35G 0.1141 0.1045 0 521 640: 49%|████▉ | 29/59 [01:44<01:40, 3.35s/it]0/99 6.35G 0.1141 0.1045 0 521 640: 51%|█████ | 30/59 [01:44<01:39, 3.42s/it]0/99 6.35G 0.1138 0.1047 0 748 640: 51%|█████ | 30/59 [01:49<01:39, 3.42s/it]0/99 6.35G 0.1138 0.1047 0 748 640: 53%|█████▎ | 31/59 [01:49<01:40, 3.60s/it]0/99 6.35G 0.1134 0.1044 0 581 640: 53%|█████▎ | 31/59 [01:52<01:40, 3.60s/it]0/99 6.35G 0.1134 0.1044 0 581 640: 54%|█████▍ | 32/59 [01:52<01:34, 3.51s/it]0/99 6.35G 0.113 0.1041 0 579 640: 54%|█████▍ | 32/59 [01:55<01:34, 3.51s/it]0/99 6.35G 0.113 0.1041 0 579 640: 56%|█████▌ | 33/59 [01:55<01:29, 3.44s/it]0/99 6.35G 0.1126 0.1042 0 720 640: 56%|█████▌ | 33/59 [01:58<01:29, 3.44s/it]0/99 6.35G 0.1126 0.1042 0 720 640: 58%|█████▊ | 34/59 [01:58<01:24, 3.39s/it]0/99 6.35G 0.1122 0.1039 0 603 640: 58%|█████▊ | 34/59 [02:02<01:24, 3.39s/it]0/99 6.35G 0.1122 0.1039 0 603 640: 59%|█████▉ | 35/59 [02:02<01:20, 3.36s/it]0/99 6.35G 0.1119 0.1037 0 702 640: 59%|█████▉ | 35/59 [02:05<01:20, 3.36s/it]0/99 6.35G 0.1119 0.1037 0 702 640: 61%|██████ | 36/59 [02:05<01:18, 3.41s/it]0/99 6.35G 0.1115 0.1036 0 616 640: 61%|██████ | 36/59 [02:09<01:18, 3.41s/it]0/99 6.35G 0.1115 0.1036 0 616 640: 63%|██████▎ | 37/59 [02:09<01:16, 3.50s/it]0/99 6.35G 0.1111 0.1034 0 655 640: 63%|██████▎ | 37/59 [02:12<01:16, 3.50s/it]0/99 6.35G 0.1111 0.1034 0 655 640: 64%|██████▍ | 38/59 [02:12<01:13, 3.49s/it]0/99 6.35G 0.1107 0.1036 0 728 640: 64%|██████▍ | 38/59 [02:16<01:13, 3.49s/it]0/99 6.35G 0.1107 0.1036 0 728 640: 66%|██████▌ | 39/59 [02:16<01:08, 3.44s/it]0/99 6.35G 0.1103 0.1038 0 801 640: 66%|██████▌ | 39/59 [02:19<01:08, 3.44s/it]0/99 6.35G 0.1103 0.1038 0 801 640: 68%|██████▊ | 40/59 [02:19<01:04, 3.40s/it]0/99 6.35G 0.11 0.1038 0 723 640: 68%|██████▊ | 40/59 [02:22<01:04, 3.40s/it]0/99 6.35G 0.11 0.1038 0 723 640: 69%|██████▉ | 41/59 [02:22<01:00, 3.37s/it]0/99 6.35G 0.1096 0.1034 0 555 640: 69%|██████▉ | 41/59 [02:26<01:00, 3.37s/it]0/99 6.35G 0.1096 0.1034 0 555 640: 71%|███████ | 42/59 [02:26<00:57, 3.36s/it]0/99 6.35G 0.1093 0.1034 0 642 640: 71%|███████ | 42/59 [02:29<00:57, 3.36s/it]0/99 6.35G 0.1093 0.1034 0 642 640: 73%|███████▎ | 43/59 [02:29<00:54, 3.43s/it]0/99 6.35G 0.1089 0.1032 0 632 640: 73%|███████▎ | 43/59 [02:33<00:54, 3.43s/it]0/99 6.35G 0.1089 0.1032 0 632 640: 75%|███████▍ | 44/59 [02:33<00:52, 3.47s/it]0/99 6.35G 0.1085 0.103 0 544 640: 75%|███████▍ | 44/59 [02:36<00:52, 3.47s/it]0/99 6.35G 0.1085 0.103 0 544 640: 76%|███████▋ | 45/59 [02:36<00:47, 3.41s/it]0/99 6.35G 0.1081 0.1025 0 485 640: 76%|███████▋ | 45/59 [02:39<00:47, 3.41s/it]0/99 6.35G 0.1081 0.1025 0 485 640: 78%|███████▊ | 46/59 [02:39<00:43, 3.38s/it]0/99 6.35G 0.1077 0.1023 0 600 640: 78%|███████▊ | 46/59 [02:43<00:43, 3.38s/it]0/99 6.35G 0.1077 0.1023 0 600 640: 80%|███████▉ | 47/59 [02:43<00:40, 3.35s/it]0/99 6.35G 0.1073 0.102 0 513 640: 80%|███████▉ | 47/59 [02:46<00:40, 3.35s/it]0/99 6.35G 0.1073 0.102 0 513 640: 81%|████████▏ | 48/59 [02:46<00:36, 3.34s/it]0/99 6.35G 0.1069 0.1019 0 522 640: 81%|████████▏ | 48/59 [02:49<00:36, 3.34s/it]0/99 6.35G 0.1069 0.1019 0 522 640: 83%|████████▎ | 49/59 [02:49<00:33, 3.35s/it]0/99 6.35G 0.1065 0.102 0 687 640: 83%|████████▎ | 49/59 [02:53<00:33, 3.35s/it]0/99 6.35G 0.1065 0.102 0 687 640: 85%|████████▍ | 50/59 [02:53<00:30, 3.43s/it]0/99 6.35G 0.1061 0.1018 0 541 640: 85%|████████▍ | 50/59 [02:57<00:30, 3.43s/it]0/99 6.35G 0.1061 0.1018 0 541 640: 86%|████████▋ | 51/59 [02:57<00:28, 3.52s/it]0/99 6.35G 0.1058 0.1017 0 615 640: 86%|████████▋ | 51/59 [03:00<00:28, 3.52s/it]0/99 6.35G 0.1058 0.1017 0 615 640: 88%|████████▊ | 52/59 [03:00<00:24, 3.49s/it]0/99 6.35G 0.1055 0.1018 0 781 640: 88%|████████▊ | 52/59 [03:03<00:24, 3.49s/it]0/99 6.35G 0.1055 0.1018 0 781 640: 90%|████████▉ | 53/59 [03:03<00:20, 3.44s/it]0/99 6.35G 0.1052 0.1017 0 586 640: 90%|████████▉ | 53/59 [03:07<00:20, 3.44s/it]0/99 6.35G 0.1052 0.1017 0 586 640: 92%|█████████▏| 54/59 [03:07<00:16, 3.39s/it]0/99 6.35G 0.1049 0.1016 0 575 640: 92%|█████████▏| 54/59 [03:10<00:16, 3.39s/it]0/99 6.35G 0.1049 0.1016 0 575 640: 93%|█████████▎| 55/59 [03:10<00:13, 3.36s/it]0/99 6.35G 0.1046 0.1019 0 715 640: 93%|█████████▎| 55/59 [03:13<00:13, 3.36s/it]0/99 6.35G 0.1046 0.1019 0 715 640: 95%|█████████▍| 56/59 [03:13<00:10, 3.36s/it]0/99 6.35G 0.1042 0.1019 0 618 640: 95%|█████████▍| 56/59 [03:17<00:10, 3.36s/it]0/99 6.35G 0.1042 0.1019 0 618 640: 97%|█████████▋| 57/59 [03:17<00:06, 3.45s/it]0/99 6.35G 0.1039 0.1017 0 544 640: 97%|█████████▋| 57/59 [03:21<00:06, 3.45s/it]0/99 6.35G 0.1039 0.1017 0 544 640: 98%|█████████▊| 58/59 [03:21<00:03, 3.49s/it]0/99 6.35G 0.1036 0.1016 0 96 640: 98%|█████████▊| 58/59 [03:21<00:03, 3.49s/it]0/99 6.35G 0.1036 0.1016 0 96 640: 100%|██████████| 59/59 [03:21<00:00, 2.61s/it]0/99 6.35G 0.1036 0.1016 0 96 640: 100%|██████████| 59/59 [03:21<00:00, 3.42s/it]Class Images Labels P R mAP@.5 mAP@.5:.95: 0%| | 0/4 [00:00<?, ?it/s]Class Images Labels P R mAP@.5 mAP@.5:.95: 25%|██▌ | 1/4 [00:02<00:07, 2.63s/it]Class Images Labels P R mAP@.5 mAP@.5:.95: 50%|█████ | 2/4 [00:05<00:05, 2.75s/it]Class Images Labels P R mAP@.5 mAP@.5:.95: 75%|███████▌ | 3/4 [00:07<00:02, 2.61s/it]Class Images Labels P R mAP@.5 mAP@.5:.95: 100%|██████████| 4/4 [00:08<00:00, 1.95s/it]Class Images Labels P R mAP@.5 mAP@.5:.95: 100%|██████████| 4/4 [00:08<00:00, 2.21s/it]all 207 3407 0.115 0.277 0.0747 0.0141Epoch gpu_mem box obj cls labels img_size0%| | 0/59 [00:00<?, ?it/s]1/99 6.35G 0.08355 0.09766 0 566 640: 0%| | 0/59 [00:03<?, ?it/s]1/99 6.35G 0.08355 0.09766 0 566 640: 2%|▏ | 1/59 [00:03<03:26, 3.56s/it]1/99 6.35G 0.08539 0.09904 0 652 640: 2%|▏ | 1/59 [00:07<03:26, 3.56s/it]1/99 6.35G 0.08539 0.09904 0 652 640: 3%|▎ | 2/59 [00:07<03:27, 3.65s/it]1/99 6.35G 0.08526 0.09853 0 596 640: 3%|▎ | 2/59 [00:10<03:27, 3.65s/it]1/99 6.35G 0.08526 0.09853 0 596 640: 5%|▌ | 3/59 [00:10<03:20, 3.58s/it]1/99 6.35G 0.08491 0.09569 0 511 640: 5%|▌ | 3/59 [00:14<03:20, 3.58s/it]1/99 6.35G 0.08491 0.09569 0 511 640: 7%|▋ | 4/59 [00:14<03:11, 3.48s/it]1/99 6.35G 0.08466 0.09637 0 581 640: 7%|▋ | 4/59 [00:17<03:11, 3.48s/it]1/99 6.35G 0.08466 0.09637 0 581 640: 8%|▊ | 5/59 [00:17<03:04, 3.42s/it]1/99 6.35G 0.08471 0.09602 0 556 640: 8%|▊ | 5/59 [00:20<03:04, 3.42s/it]1/99 6.35G 0.08471 0.09602 0 556 640: 10%|█ | 6/59 [00:20<02:58, 3.37s/it]1/99 6.35G 0.08454 0.09583 0 533 640: 10%|█ | 6/59 [00:24<02:58, 3.37s/it]1/99 6.35G 0.08454 0.09583 0 533 640: 12%|█▏ | 7/59 [00:24<02:54, 3.36s/it]1/99 6.35G 0.08531 0.09746 0 717 640: 12%|█▏ | 7/59 [00:27<02:54, 3.36s/it]1/99 6.35G 0.08531 0.09746 0 717 640: 14%|█▎ | 8/59 [00:27<02:54, 3.43s/it]1/99 6.35G 0.08575 0.09843 0 679 640: 14%|█▎ | 8/59 [00:31<02:54, 3.43s/it]1/99 6.35G 0.08575 0.09843 0 679 640: 15%|█▌ | 9/59 [00:31<02:55, 3.52s/it]1/99 6.35G 0.08565 0.09742 0 526 640: 15%|█▌ | 9/59 [00:34<02:55, 3.52s/it]1/99 6.35G 0.08565 0.09742 0 526 640: 17%|█▋ | 10/59 [00:34<02:51, 3.49s/it]1/99 6.35G 0.08555 0.09815 0 670 640: 17%|█▋ | 10/59 [00:38<02:51, 3.49s/it]1/99 6.35G 0.08555 0.09815 0 670 640: 19%|█▊ | 11/59 [00:38<02:44, 3.43s/it]1/99 6.35G 0.08521 0.09721 0 519 640: 19%|█▊ | 11/59 [00:41<02:44, 3.43s/it]1/99 6.35G 0.08521 0.09721 0 519 640: 20%|██ | 12/59 [00:41<02:39, 3.40s/it]1/99 6.35G 0.08517 0.09802 0 659 640: 20%|██ | 12/59 [00:44<02:39, 3.40s/it]1/99 6.35G 0.08517 0.09802 0 659 640: 22%|██▏ | 13/59 [00:44<02:35, 3.37s/it]1/99 6.35G 0.08511 0.09739 0 530 640: 22%|██▏ | 13/59 [00:47<02:35, 3.37s/it]1/99 6.35G 0.08511 0.09739 0 530 640: 24%|██▎ | 14/59 [00:47<02:30, 3.34s/it]1/99 6.35G 0.08502 0.097 0 529 640: 24%|██▎ | 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[02:58<00:24, 3.50s/it]1/99 6.35G 0.08775 0.09695 0 630 640: 88%|████████▊ | 52/59 [03:01<00:24, 3.50s/it]1/99 6.35G 0.08775 0.09695 0 630 640: 90%|████████▉ | 53/59 [03:01<00:20, 3.43s/it]1/99 6.35G 0.08779 0.09712 0 693 640: 90%|████████▉ | 53/59 [03:04<00:20, 3.43s/it]1/99 6.35G 0.08779 0.09712 0 693 640: 92%|█████████▏| 54/59 [03:04<00:16, 3.39s/it]1/99 6.35G 0.08769 0.09716 0 585 640: 92%|█████████▏| 54/59 [03:08<00:16, 3.39s/it]1/99 6.35G 0.08769 0.09716 0 585 640: 93%|█████████▎| 55/59 [03:08<00:13, 3.36s/it]1/99 6.35G 0.08763 0.09685 0 515 640: 93%|█████████▎| 55/59 [03:11<00:13, 3.36s/it]1/99 6.35G 0.08763 0.09685 0 515 640: 95%|█████████▍| 56/59 [03:11<00:10, 3.34s/it]1/99 6.35G 0.08765 0.09699 0 705 640: 95%|█████████▍| 56/59 [03:14<00:10, 3.34s/it]1/99 6.35G 0.08765 0.09699 0 705 640: 97%|█████████▋| 57/59 [03:14<00:06, 3.36s/it]1/99 6.35G 0.08765 0.09736 0 726 640: 97%|█████████▋| 57/59 [03:18<00:06, 3.36s/it]1/99 6.35G 0.08765 0.09736 0 726 640: 98%|█████████▊| 58/59 [03:18<00:03, 3.47s/it]1/99 6.37G 0.08766 0.09725 0 91 640: 98%|█████████▊| 58/59 [03:18<00:03, 3.47s/it]1/99 6.37G 0.08766 0.09725 0 91 640: 100%|██████████| 59/59 [03:18<00:00, 2.58s/it]1/99 6.37G 0.08766 0.09725 0 91 640: 100%|██████████| 59/59 [03:18<00:00, 3.37s/it]Class Images Labels P R mAP@.5 mAP@.5:.95: 0%| | 0/4 [00:00<?, ?it/s]Class Images Labels P R mAP@.5 mAP@.5:.95: 25%|██▌ | 1/4 [00:02<00:07, 2.44s/it]Class Images Labels P R mAP@.5 mAP@.5:.95: 50%|█████ | 2/4 [00:05<00:05, 2.62s/it]Class Images Labels P R mAP@.5 mAP@.5:.95: 75%|███████▌ | 3/4 [00:07<00:02, 2.53s/it]Class Images Labels P R mAP@.5 mAP@.5:.95: 100%|██████████| 4/4 [00:08<00:00, 1.90s/it]Class Images Labels P R mAP@.5 mAP@.5:.95: 100%|██████████| 4/4 [00:08<00:00, 2.14s/it]all 207 3407 0.12 0.382 0.0979 0.0192
训练过程中，结果会自动创建目录存储在runs下，如下所示：
yolov5s-bifpn模型结果：
yolov5s模型结果：
随机选取样例图像测试如下：
为了便于后续使用结果数据，这里对其结果数据进行解析存储如下：
{"crack": [[0.26700732111930849,[0,296,23,392]],[0.2672766149044037,[686,648,767,689]],[0.2740951180458069,[1,393,26,498]],[0.27556174993515017,[631,634,722,671]],[0.27758586406707766,[582,247,630,295]],[0.2786214053630829,[801,711,869,753]],[0.28326842188835146,[911,761,966,819]],[0.2855015993118286,[726,61,765,126]],[0.2891019582748413,[541,621,613,658]],[0.28970593214035036,[863,745,932,780]],[0.28980544209480288,[752,8,785,76]],[0.2912375032901764,[986,860,1020,918]],[0.29403477907180788,[619,205,663,261]],[0.29819419980049136,[666,641,740,677]],[0.30100756883621218,[1005,903,1024,951]],[0.30114322900772097,[548,281,588,338]],[0.30483242869377139,[1,342,26,450]],[0.3290395140647888,[820,720,890,763]],[0.3302559554576874,[652,165,695,221]],[0.3334021270275116,[0,693,35,736]],[0.33690938353538515,[605,222,650,275]],[0.34495481848716738,[0,533,27,615]],[0.37444597482681277,[963,713,1018,755]],[0.37496164441108706,[686,121,735,176]],[0.3889273703098297,[358,590,432,633]],[0.40112408995628359,[5,612,38,693]],[0.40698984265327456,[593,235,640,287]],[0.41528889536857607,[633,185,677,244]],[0.4153532385826111,[446,474,492,534]],[0.41710415482521059,[996,879,1024,942]],[0.42140141129493716,[762,0,792,47]],[0.42363840341567995,[675,137,724,187]],[0.42380252480506899,[422,583,483,635]],[0.43151307106018069,[709,93,750,155]],[0.4327857792377472,[844,734,915,775]],[0.4366927146911621,[555,272,604,315]],[0.4374251663684845,[233,649,297,688]],[0.44089221954345705,[714,657,784,701]],[0.448123574256897,[739,37,774,107]],[0.4551221430301666,[161,641,238,690]],[0.45720604062080386,[769,688,830,736]],[0.4593600630760193,[963,839,1007,886]],[0.48793330788612368,[607,626,690,664]],[0.4884047508239746,[925,772,979,835]],[0.5071386694908142,[222,597,306,647]],[0.5111898183822632,[473,431,514,497]],[0.5346865057945252,[105,662,182,713]],[0.5522925853729248,[540,303,569,378]],[0.5579397082328796,[506,367,552,432]],[0.5627263784408569,[295,580,388,633]],[0.5672629475593567,[475,617,569,653]],[0.574158251285553,[24,693,108,731]],[0.5847405791282654,[426,526,461,594]]]}
与我之前的文章中的结果格式保持一致。
本文转载自: https://blog.csdn.net/Together_CZ/article/details/127735859
版权归原作者 Together_CZ 所有， 如有侵权，请联系我们删除。
版权归原作者 Together_CZ 所有， 如有侵权，请联系我们删除。