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Microsoft Windows [版本 10.0.19045.4412]
(c) Microsoft Corporation。保留所有权利。
E:\Code\gitproject\YoloTrainCsharp\YoloTrainCsharp\bin\x64\Debug\net6.0-windows>e:
E:\Code\gitproject\YoloTrainCsharp\YoloTrainCsharp\bin\x64\Debug\net6.0-windows>cd E:\Code\gitproject\seeneyAI
E:\Code\gitproject\seeneyAI>conda activate seeneyAI
(seeneyAI) E:\Code\gitproject\seeneyAI>yolo detect train data=datasets\shunluojiazhuang_biaozhu\shunluojiazhuang_biaozhu.yaml model=yolov8n.pt epochs=10 name=train\xunluojiazhuang_biaozhu_3rd optimizer=SGD lr0=0.001 lrf=0.01 patience=50 batch=32 box=0.05 cls=0.3 kobj=0.7 scale=0.9 hsv_h=0 hsv_s=0 hsv_v=0
New https://pypi.org/project/ultralytics/8.2.28 available 馃槂 Update with 'pip install -U ultralytics'
Ultralytics YOLOv8.2.27 馃殌 Python-3.9.19 torch-2.3.0+cu118 CUDA:0 (NVIDIA GeForce RTX 2080 Ti, 11264MiB)
[34m[1mengine\trainer: [0mtask=detect, mode=train, model=yolov8n.pt, data=datasets\shunluojiazhuang_biaozhu\shunluojiazhuang_biaozhu.yaml, epochs=10, time=None, patience=50, batch=32, imgsz=640, save=True, save_period=-1, cache=False, device=None, workers=8, project=None, name=xunluojiazhuang_biaozhu_3rd2, exist_ok=False, pretrained=True, optimizer=SGD, verbose=True, seed=0, deterministic=True, single_cls=False, rect=False, cos_lr=False, close_mosaic=10, resume=False, amp=True, fraction=1.0, profile=False, freeze=None, multi_scale=False, overlap_mask=True, mask_ratio=4, dropout=0.0, val=True, split=val, save_json=False, save_hybrid=False, conf=None, iou=0.7, max_det=300, half=False, dnn=False, plots=True, source=None, vid_stride=1, stream_buffer=False, visualize=False, augment=False, agnostic_nms=False, classes=None, retina_masks=False, embed=None, show=False, save_frames=False, save_txt=False, save_conf=False, save_crop=False, show_labels=True, show_conf=True, show_boxes=True, line_width=None, format=torchscript, keras=False, optimize=False, int8=False, dynamic=False, simplify=False, opset=None, workspace=4, nms=False, lr0=0.001, lrf=0.01, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=0.05, cls=0.3, dfl=1.5, pose=12.0, kobj=0.7, label_smoothing=0.0, nbs=64, hsv_h=0, hsv_s=0, hsv_v=0, degrees=0.0, translate=0.1, scale=0.9, shear=0.0, perspective=0.0, flipud=0.0, fliplr=0.5, bgr=0.0, mosaic=1.0, mixup=0.0, copy_paste=0.0, auto_augment=randaugment, erasing=0.4, crop_fraction=1.0, cfg=None, tracker=botsort.yaml, save_dir=runs\detect\train\xunluojiazhuang_biaozhu_3rd2
Overriding model.yaml nc=80 with nc=7
from n params module arguments
0 -1 1 464 ultralytics.nn.modules.conv.Conv [3, 16, 3, 2]
1 -1 1 4672 ultralytics.nn.modules.conv.Conv [16, 32, 3, 2]
2 -1 1 7360 ultralytics.nn.modules.block.C2f [32, 32, 1, True]
3 -1 1 18560 ultralytics.nn.modules.conv.Conv [32, 64, 3, 2]
4 -1 2 49664 ultralytics.nn.modules.block.C2f [64, 64, 2, True]
5 -1 1 73984 ultralytics.nn.modules.conv.Conv [64, 128, 3, 2]
6 -1 2 197632 ultralytics.nn.modules.block.C2f [128, 128, 2, True]
7 -1 1 295424 ultralytics.nn.modules.conv.Conv [128, 256, 3, 2]
8 -1 1 460288 ultralytics.nn.modules.block.C2f [256, 256, 1, True]
9 -1 1 164608 ultralytics.nn.modules.block.SPPF [256, 256, 5]
10 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
11 [-1, 6] 1 0 ultralytics.nn.modules.conv.Concat [1]
12 -1 1 148224 ultralytics.nn.modules.block.C2f [384, 128, 1]
13 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
14 [-1, 4] 1 0 ultralytics.nn.modules.conv.Concat [1]
15 -1 1 37248 ultralytics.nn.modules.block.C2f [192, 64, 1]
16 -1 1 36992 ultralytics.nn.modules.conv.Conv [64, 64, 3, 2]
17 [-1, 12] 1 0 ultralytics.nn.modules.conv.Concat [1]
18 -1 1 123648 ultralytics.nn.modules.block.C2f [192, 128, 1]
19 -1 1 147712 ultralytics.nn.modules.conv.Conv [128, 128, 3, 2]
20 [-1, 9] 1 0 ultralytics.nn.modules.conv.Concat [1]
21 -1 1 493056 ultralytics.nn.modules.block.C2f [384, 256, 1]
22 [15, 18, 21] 1 752677 ultralytics.nn.modules.head.Detect [7, [64, 128, 256]]
Model summary: 225 layers, 3012213 parameters, 3012197 gradients, 8.2 GFLOPs
Transferred 319/355 items from pretrained weights
Freezing layer 'model.22.dfl.conv.weight'
[34m[1mAMP: [0mrunning Automatic Mixed Precision (AMP) checks with YOLOv8n...
[34m[1mAMP: [0mchecks passed 鉁?
线程 '.NET ThreadPool Worker' (16636) 已退出，返回值为 0 (0x0)。
线程 '.NET ThreadPool Worker' (17696) 已退出，返回值为 0 (0x0)。
线程 '.NET ThreadPool Worker' (34396) 已退出，返回值为 0 (0x0)。
Plotting labels to runs\detect\train\xunluojiazhuang_biaozhu_3rd2\labels.jpg...
[34m[1moptimizer:[0m SGD(lr=0.001, momentum=0.937) with parameter groups 57 weight(decay=0.0), 64 weight(decay=0.0005), 63 bias(decay=0.0)
Image sizes 640 train, 640 val
Using 8 dataloader workers
Logging results to [1mruns\detect\train\xunluojiazhuang_biaozhu_3rd2[0m
Starting training for 10 epochs...
Closing dataloader mosaic
线程 '.NET ThreadPool Worker' (14288) 已退出，返回值为 0 (0x0)。
线程 '.NET ThreadPool Worker' (19632) 已退出，返回值为 0 (0x0)。
Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size
1/10 4.57G 0.02496 5.201 2.974 75 640
1/10 4.57G 0.02377 4.812 2.739 73 640
1/10 4.57G 0.02309 5.09 2.555 56 640
1/10 4.75G 0.02259 4.963 2.487 60 640
1/10 4.75G 0.02335 5.005 2.566 69 640
1/10 4.75G 0.02355 5.044 2.555 65 640
1/10 4.75G 0.02294 5.032 2.474 58 640
1/10 4.78G 0.02301 5.122 2.449 59 640
1/10 4.78G 0.02244 5.169 2.387 49 640
1/10 4.78G 0.02218 5.13 2.34 59 640
1/10 4.78G 0.02239 5.144 2.375 67 640
1/10 4.78G 0.02197 5.022 2.315 100 640
1/10 4.78G 0.02205 4.981 2.324 84 640
1/10 4.78G 0.02203 4.925 2.324 84 640
1/10 4.78G 0.02203 4.912 2.308 74 640
1/10 4.78G 0.02177 4.886 2.267 62 640
1/10 4.78G 0.02164 4.892 2.232 52 640
1/10 4.78G 0.0217 4.899 2.229 64 640
1/10 4.78G 0.02166 4.86 2.224 97 640
1/10 4.78G 0.02159 4.932 2.198 53 640
1/10 4.78G 0.02152 4.877 2.184 81 640
1/10 4.78G 0.02165 4.867 2.193 72 640
1/10 4.78G 0.02177 4.846 2.192 92 640
1/10 4.78G 0.02171 4.813 2.177 80 640
1/10 4.78G 0.02164 4.806 2.16 64 640
1/10 4.78G 0.02153 4.782 2.134 61 640
1/10 4.78G 0.02141 4.758 2.114 65 640
1/10 4.78G 0.02142 4.734 2.106 78 640
1/10 4.78G 0.02133 4.706 2.091 64 640
1/10 4.78G 0.0212 4.668 2.075 87 640
1/10 4.78G 0.0211 4.64 2.058 97 640
1/10 4.78G 0.02102 4.624 2.043 59 640
1/10 4.78G 0.02097 4.617 2.035 55 640
1/10 4.78G 0.02087 4.617 2.016 59 640
1/10 4.78G 0.02069 4.594 1.995 67 640
1/10 4.78G 0.02063 4.589 1.982 69 640
1/10 4.78G 0.02055 4.567 1.97 66 640
1/10 4.78G 0.02056 4.543 1.967 77 640
1/10 4.83G 0.02068 4.641 1.961 2 640
Class Images Instances P R mAP50 mAP50-95
all 1218 2703 0 0 0 0
Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size
2/10 4.55G 0.02136 4.612 1.752 53 640
2/10 4.55G 0.01993 4.119 1.664 84 640
2/10 4.55G 0.01914 4.011 1.576 66 640
2/10 4.55G 0.0193 3.958 1.6 80 640
2/10 4.55G 0.01896 3.917 1.578 77 640
2/10 4.55G 0.0191 3.914 1.595 65 640
2/10 4.55G 0.01894 3.836 1.572 101 640
2/10 4.55G 0.01888 3.773 1.595 86 640
2/10 4.55G 0.01899 3.73 1.618 82 640
2/10 4.55G 0.01896 3.695 1.616 76 640
2/10 4.55G 0.01898 3.707 1.618 50 640
2/10 4.55G 0.01894 3.702 1.607 74 640
2/10 4.55G 0.0189 3.701 1.601 70 640
2/10 4.55G 0.01877 3.679 1.603 60 640
2/10 4.55G 0.0188 3.678 1.604 58 640
2/10 4.55G 0.01877 3.724 1.597 55 640
2/10 4.55G 0.01879 3.725 1.598 50 640
2/10 4.55G 0.01873 3.703 1.585 86 640
2/10 4.55G 0.01854 3.684 1.566 62 640
2/10 4.55G 0.01844 3.656 1.564 89 640
2/10 4.55G 0.0184 3.655 1.562 58 640
2/10 4.55G 0.01828 3.63 1.552 70 640
2/10 4.55G 0.01824 3.614 1.545 80 640
2/10 4.55G 0.01835 3.61 1.551 88 640
2/10 4.55G 0.0184 3.603 1.56 65 640
2/10 4.55G 0.01835 3.591 1.553 62 640
2/10 4.55G 0.01838 3.59 1.55 57 640
2/10 4.55G 0.01838 3.57 1.556 90 640
2/10 4.55G 0.0184 3.556 1.554 95 640
2/10 4.55G 0.01837 3.548 1.553 58 640
2/10 4.55G 0.01834 3.535 1.551 72 640
2/10 4.55G 0.01828 3.523 1.548 74 640
2/10 4.55G 0.01821 3.521 1.547 40 640
2/10 4.55G 0.01818 3.509 1.545 70 640
2/10 4.55G 0.01814 3.497 1.538 59 640
2/10 4.55G 0.01804 3.489 1.532 51 640
2/10 4.55G 0.01805 3.49 1.532 63 640
2/10 4.55G 0.01805 3.477 1.53 59 640
2/10 4.6G 0.01797 3.453 1.527 3 640
Class Images Instances P R mAP50 mAP50-95
all 1218 2703 0.00545 0.0649 0.028 0.0121
Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size
3/10 4.58G 0.01865 3.243 1.732 58 640
3/10 4.58G 0.01847 3.385 1.669 51 640
3/10 4.58G 0.01873 3.331 1.646 72 640
3/10 4.58G 0.01792 3.177 1.577 47 640
3/10 4.58G 0.01793 3.169 1.585 56 640
3/10 4.58G 0.01832 3.146 1.579 74 640
3/10 4.58G 0.01828 3.127 1.588 57 640
3/10 4.58G 0.0183 3.103 1.594 67 640
3/10 4.58G 0.01797 3.065 1.556 65 640
3/10 4.58G 0.01801 3.057 1.557 76 640
3/10 4.58G 0.01796 3.024 1.551 66 640
3/10 4.58G 0.01791 2.984 1.554 68 640
3/10 4.58G 0.01796 2.964 1.554 87 640
3/10 4.58G 0.01803 2.941 1.557 79 640
3/10 4.58G 0.01786 2.908 1.554 51 640
3/10 4.58G 0.01783 2.894 1.549 99 640
3/10 4.58G 0.01781 2.875 1.55 56 640
3/10 4.58G 0.01769 2.859 1.548 61 640
3/10 4.58G 0.01758 2.854 1.545 53 640
3/10 4.58G 0.01754 2.846 1.539 79 640
3/10 4.58G 0.0175 2.834 1.536 66 640
3/10 4.58G 0.01753 2.827 1.547 70 640
3/10 4.58G 0.0175 2.813 1.547 50 640
3/10 4.58G 0.01752 2.804 1.55 59 640
3/10 4.58G 0.01749 2.801 1.547 53 640
3/10 4.58G 0.01749 2.799 1.545 54 640
3/10 4.58G 0.01741 2.775 1.535 85 640
3/10 4.58G 0.0174 2.766 1.539 83 640
3/10 4.58G 0.01745 2.762 1.539 84 640
3/10 4.58G 0.01745 2.746 1.534 85 640
3/10 4.58G 0.01739 2.739 1.527 65 640
3/10 4.58G 0.01744 2.739 1.526 101 640
3/10 4.58G 0.01751 2.743 1.526 107 640
3/10 4.58G 0.01743 2.721 1.519 71 640
3/10 4.58G 0.0175 2.713 1.524 102 640
3/10 4.58G 0.01747 2.713 1.522 45 640
3/10 4.58G 0.01743 2.703 1.519 59 640
3/10 4.58G 0.01744 2.693 1.52 78 640
3/10 4.62G 0.01746 2.696 1.526 2 640
Class Images Instances P R mAP50 mAP50-95
线程 '.NET ThreadPool Worker' (37352) 已退出，返回值为 0 (0x0)。
线程 '.NET ThreadPool Worker' (27724) 已退出，返回值为 0 (0x0)。
all 1218 2703 0.847 0.137 0.152 0.0576
Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size
4/10 4.53G 0.01493 2.169 1.461 55 640
4/10 4.53G 0.01518 2.184 1.379 76 640
4/10 4.53G 0.01557 2.237 1.464 70 640
4/10 4.53G 0.01608 2.268 1.481 80 640
4/10 4.53G 0.01644 2.455 1.448 56 640
4/10 4.53G 0.01655 2.414 1.489 79 640
4/10 4.53G 0.01657 2.411 1.486 58 640
4/10 4.53G 0.0167 2.395 1.488 84 640
4/10 4.53G 0.0166 2.358 1.47 71 640
4/10 4.53G 0.01637 2.327 1.463 51 640
4/10 4.53G 0.01634 2.327 1.462 60 640
4/10 4.53G 0.0164 2.316 1.47 78 640
4/10 4.53G 0.01636 2.322 1.467 45 640
4/10 4.53G 0.01634 2.33 1.463 62 640
4/10 4.53G 0.01657 2.35 1.469 72 640
4/10 4.53G 0.01652 2.328 1.468 77 640
4/10 4.53G 0.0165 2.309 1.466 103 640
4/10 4.53G 0.01647 2.289 1.457 68 640
4/10 4.53G 0.01643 2.301 1.453 40 640
4/10 4.53G 0.01645 2.281 1.449 100 640
4/10 4.53G 0.0164 2.291 1.449 59 640
4/10 4.53G 0.01639 2.288 1.446 64 640
4/10 4.53G 0.01635 2.282 1.447 71 640
4/10 4.53G 0.01634 2.277 1.453 64 640
4/10 4.53G 0.0163 2.266 1.451 54 640
4/10 4.53G 0.01628 2.263 1.454 66 640
4/10 4.53G 0.01627 2.253 1.453 71 640
4/10 4.53G 0.01637 2.256 1.452 87 640
4/10 4.53G 0.01639 2.252 1.452 66 640
4/10 4.53G 0.01639 2.249 1.451 74 640
4/10 4.53G 0.01637 2.246 1.451 64 640
4/10 4.53G 0.01631 2.243 1.448 58 640
4/10 4.53G 0.01629 2.229 1.445 85 640
4/10 4.53G 0.01628 2.223 1.446 62 640
4/10 4.53G 0.01625 2.212 1.446 70 640
4/10 4.53G 0.01624 2.205 1.446 73 640
4/10 4.53G 0.01631 2.199 1.449 91 640
4/10 4.53G 0.01633 2.195 1.454 77 640
4/10 4.58G 0.01639 2.181 1.443 6 640
Class Images Instances P R mAP50 mAP50-95
all 1218 2703 0.215 0.198 0.219 0.0904
Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size
5/10 4.64G 0.01483 1.76 1.33 76 640
5/10 4.64G 0.01536 1.859 1.44 47 640
5/10 4.64G 0.01591 1.864 1.467 72 640
5/10 4.64G 0.0159 1.845 1.473 68 640
5/10 4.64G 0.01581 1.846 1.471 63 640
5/10 4.64G 0.01596 1.845 1.508 73 640
5/10 4.64G 0.01589 1.864 1.498 47 640
5/10 4.64G 0.01596 1.892 1.48 50 640
5/10 4.64G 0.01571 1.887 1.471 58 640
5/10 4.64G 0.01569 1.908 1.458 62 640
5/10 4.64G 0.01587 1.918 1.471 85 640
5/10 4.64G 0.01604 1.904 1.491 95 640
5/10 4.64G 0.01612 1.913 1.498 73 640
5/10 4.64G 0.01586 1.92 1.48 41 640
5/10 4.64G 0.01591 1.914 1.49 77 640
5/10 4.64G 0.01591 1.914 1.482 73 640
5/10 4.64G 0.01592 1.895 1.483 110 640
5/10 4.64G 0.01589 1.898 1.486 66 640
5/10 4.64G 0.0158 1.923 1.477 45 640
5/10 4.64G 0.01578 1.92 1.47 47 640
5/10 4.64G 0.01577 1.915 1.471 76 640
5/10 4.64G 0.01584 1.927 1.47 80 640
5/10 4.64G 0.01586 1.913 1.473 84 640
5/10 4.64G 0.01582 1.903 1.466 81 640
5/10 4.64G 0.01576 1.893 1.463 77 640
5/10 4.64G 0.01583 1.925 1.462 46 640
5/10 4.64G 0.01575 1.927 1.455 52 640
5/10 4.64G 0.01572 1.929 1.447 60 640
5/10 4.64G 0.01577 1.924 1.448 97 640
5/10 4.64G 0.01571 1.923 1.444 49 640
5/10 4.64G 0.01567 1.921 1.439 61 640
5/10 4.64G 0.01564 1.915 1.436 80 640
5/10 4.64G 0.01574 1.918 1.448 105 640
5/10 4.64G 0.01569 1.91 1.443 55 640
5/10 4.64G 0.01564 1.905 1.439 58 640
5/10 4.64G 0.01562 1.899 1.442 76 640
5/10 4.64G 0.01563 1.899 1.442 62 640
5/10 4.64G 0.01566 1.897 1.445 68 640
5/10 4.68G 0.01574 1.886 1.445 4 640
Class Images Instances P R mAP50 mAP50-95
all 1218 2703 0.341 0.323 0.341 0.138
Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size
6/10 4.61G 0.01473 1.605 1.569 58 640
6/10 4.61G 0.01454 1.758 1.425 62 640
6/10 4.61G 0.01407 1.618 1.367 62 640
6/10 4.61G 0.0146 1.618 1.42 72 640
6/10 4.61G 0.01535 1.636 1.453 91 640
6/10 4.61G 0.01524 1.636 1.425 62 640
6/10 4.61G 0.0153 1.645 1.425 78 640
6/10 4.61G 0.01519 1.647 1.41 70 640
6/10 4.61G 0.015 1.673 1.4 48 640
6/10 4.61G 0.015 1.678 1.388 78 640
6/10 4.61G 0.01516 1.701 1.43 47 640
6/10 4.61G 0.01517 1.686 1.437 93 640
6/10 4.61G 0.01509 1.686 1.424 54 640
6/10 4.61G 0.01503 1.682 1.416 60 640
6/10 4.61G 0.01504 1.683 1.412 62 640
6/10 4.61G 0.01498 1.687 1.406 62 640
6/10 4.61G 0.01487 1.676 1.393 59 640
6/10 4.61G 0.01489 1.686 1.389 67 640
6/10 4.61G 0.01483 1.679 1.386 47 640
6/10 4.61G 0.01474 1.671 1.379 60 640
6/10 4.61G 0.01465 1.658 1.373 75 640
6/10 4.61G 0.0146 1.657 1.368 57 640
6/10 4.61G 0.01454 1.657 1.364 55 640
6/10 4.61G 0.01458 1.67 1.361 78 640
6/10 4.61G 0.01461 1.669 1.368 78 640
6/10 4.61G 0.01463 1.673 1.37 51 640
6/10 4.61G 0.01473 1.677 1.374 92 640
6/10 4.61G 0.01477 1.68 1.387 48 640
6/10 4.61G 0.01477 1.677 1.383 62 640
6/10 4.61G 0.01476 1.678 1.381 61 640
6/10 4.61G 0.01484 1.683 1.387 93 640
6/10 4.61G 0.01494 1.683 1.398 109 640
6/10 4.61G 0.01495 1.688 1.404 71 640
6/10 4.61G 0.01493 1.684 1.4 108 640
6/10 4.61G 0.01499 1.682 1.403 75 640
6/10 4.61G 0.01498 1.676 1.401 74 640
6/10 4.61G 0.015 1.68 1.399 83 640
6/10 4.61G 0.01505 1.675 1.405 78 640
6/10 4.66G 0.01506 1.689 1.409 2 640
Class Images Instances P R mAP50 mAP50-95
all 1218 2703 0.344 0.356 0.362 0.147
Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size
7/10 4.63G 0.01619 2.144 1.243 68 640
7/10 4.63G 0.01519 1.812 1.312 93 640
7/10 4.63G 0.01523 1.798 1.367 52 640
7/10 4.63G 0.01545 1.777 1.386 90 640
7/10 4.63G 0.01513 1.712 1.356 71 640
7/10 4.63G 0.01476 1.714 1.337 50 640
7/10 4.63G 0.01488 1.682 1.363 102 640
7/10 4.63G 0.01473 1.646 1.371 63 640
7/10 4.63G 0.01453 1.62 1.37 64 640
7/10 4.63G 0.0145 1.656 1.364 51 640
7/10 4.63G 0.01448 1.661 1.372 56 640
7/10 4.63G 0.01446 1.649 1.379 67 640
7/10 4.63G 0.01442 1.645 1.377 65 640
7/10 4.63G 0.01431 1.629 1.366 63 640
7/10 4.63G 0.01427 1.633 1.376 57 640
7/10 4.63G 0.01431 1.622 1.373 79 640
7/10 4.63G 0.01431 1.616 1.367 58 640
7/10 4.63G 0.01425 1.609 1.356 68 640
7/10 4.63G 0.0142 1.606 1.346 58 640
7/10 4.63G 0.01421 1.599 1.349 76 640
7/10 4.63G 0.01426 1.597 1.349 100 640
7/10 4.63G 0.01427 1.585 1.349 89 640
7/10 4.63G 0.01433 1.587 1.356 69 640
7/10 4.63G 0.01431 1.581 1.357 70 640
7/10 4.63G 0.01435 1.589 1.361 45 640
7/10 4.63G 0.01429 1.579 1.358 62 640
7/10 4.63G 0.01427 1.586 1.353 71 640
7/10 4.63G 0.01435 1.583 1.355 85 640
7/10 4.63G 0.01441 1.593 1.36 68 640
7/10 4.63G 0.01441 1.592 1.36 58 640
7/10 4.63G 0.0144 1.587 1.357 70 640
7/10 4.63G 0.01435 1.583 1.351 68 640
7/10 4.63G 0.01434 1.582 1.347 72 640
7/10 4.63G 0.01434 1.584 1.349 83 640
7/10 4.63G 0.01434 1.583 1.346 73 640
7/10 4.63G 0.0144 1.583 1.353 102 640
7/10 4.63G 0.01441 1.586 1.353 64 640
7/10 4.63G 0.01436 1.582 1.348 60 640
7/10 4.67G 0.01419 1.567 1.34 3 640
Class Images Instances P R mAP50 mAP50-95
all 1218 2703 0.512 0.347 0.397 0.172
Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size
8/10 4.56G 0.01529 1.795 1.314 62 640
8/10 4.57G 0.0146 1.616 1.266 73 640
8/10 4.57G 0.01426 1.598 1.271 57 640
8/10 4.57G 0.01488 1.6 1.361 70 640
8/10 4.57G 0.01452 1.564 1.345 63 640
8/10 4.57G 0.01423 1.537 1.326 56 640
8/10 4.57G 0.01435 1.517 1.335 75 640
8/10 4.57G 0.01438 1.519 1.342 62 640
8/10 4.57G 0.01441 1.5 1.356 71 640
8/10 4.57G 0.01446 1.503 1.374 69 640
8/10 4.57G 0.01442 1.495 1.364 77 640
8/10 4.57G 0.01443 1.482 1.369 84 640
8/10 4.57G 0.01468 1.529 1.393 84 640
8/10 4.57G 0.01452 1.538 1.378 42 640
8/10 4.57G 0.01456 1.534 1.385 91 640
8/10 4.57G 0.01448 1.532 1.382 48 640
8/10 4.57G 0.01441 1.509 1.377 61 640
8/10 4.57G 0.01438 1.51 1.371 67 640
8/10 4.57G 0.0144 1.509 1.369 87 640
8/10 4.57G 0.01436 1.514 1.364 59 640
8/10 4.57G 0.01447 1.522 1.374 87 640
8/10 4.57G 0.01439 1.515 1.366 58 640
8/10 4.57G 0.01444 1.526 1.37 77 640
8/10 4.57G 0.01441 1.527 1.369 71 640
8/10 4.57G 0.01436 1.518 1.363 77 640
8/10 4.57G 0.01442 1.529 1.361 69 640
8/10 4.57G 0.01437 1.517 1.359 84 640
8/10 4.57G 0.01431 1.51 1.354 68 640
8/10 4.57G 0.01432 1.5 1.352 113 640
8/10 4.57G 0.01436 1.5 1.353 78 640
8/10 4.57G 0.01432 1.491 1.348 60 640
8/10 4.57G 0.01427 1.485 1.343 62 640
8/10 4.57G 0.01428 1.488 1.347 75 640
8/10 4.57G 0.01422 1.483 1.346 71 640
8/10 4.57G 0.01415 1.473 1.34 61 640
8/10 4.57G 0.01421 1.481 1.342 60 640
8/10 4.57G 0.0142 1.48 1.337 58 640
8/10 4.57G 0.01422 1.479 1.339 66 640
8/10 4.62G 0.01452 1.519 1.341 3 640
Class Images Instances P R mAP50 mAP50-95
all 1218 2703 0.444 0.386 0.415 0.179
Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size
9/10 4.58G 0.01421 1.5 1.26 68 640
9/10 4.58G 0.01331 1.483 1.236 56 640
9/10 4.58G 0.01269 1.419 1.198 62 640
9/10 4.58G 0.01325 1.456 1.25 97 640
9/10 4.58G 0.01355 1.505 1.277 78 640
9/10 4.58G 0.01386 1.54 1.282 70 640
9/10 4.58G 0.01382 1.534 1.277 73 640
9/10 4.58G 0.01395 1.555 1.282 70 640
9/10 4.58G 0.01364 1.506 1.275 51 640
9/10 4.58G 0.01374 1.521 1.311 78 640
9/10 4.58G 0.01355 1.501 1.306 59 640
9/10 4.58G 0.01358 1.504 1.299 54 640
9/10 4.58G 0.01356 1.496 1.297 62 640
9/10 4.58G 0.01337 1.472 1.286 56 640
9/10 4.58G 0.01335 1.465 1.291 67 640
9/10 4.58G 0.01355 1.481 1.306 89 640
9/10 4.58G 0.01368 1.494 1.308 86 640
9/10 4.58G 0.01381 1.493 1.319 84 640
9/10 4.58G 0.0138 1.485 1.324 73 640
9/10 4.58G 0.01381 1.48 1.32 72 640
9/10 4.58G 0.01378 1.47 1.318 57 640
9/10 4.58G 0.01386 1.477 1.323 79 640
9/10 4.58G 0.01383 1.482 1.314 55 640
9/10 4.58G 0.01381 1.478 1.313 61 640
9/10 4.58G 0.01373 1.468 1.306 59 640
9/10 4.58G 0.01373 1.466 1.305 57 640
9/10 4.58G 0.01377 1.469 1.306 79 640
9/10 4.58G 0.01375 1.46 1.306 76 640
9/10 4.58G 0.01368 1.454 1.301 65 640
9/10 4.58G 0.01369 1.458 1.305 49 640
9/10 4.58G 0.01376 1.465 1.314 76 640
9/10 4.58G 0.01372 1.467 1.31 61 640
9/10 4.58G 0.01371 1.46 1.308 89 640
9/10 4.58G 0.01376 1.468 1.307 65 640
9/10 4.58G 0.01376 1.463 1.307 87 640
9/10 4.58G 0.01377 1.461 1.308 71 640
9/10 4.58G 0.01374 1.459 1.307 51 640
9/10 4.58G 0.01375 1.457 1.308 80 640
9/10 4.62G 0.01373 1.446 1.311 3 640
Class Images Instances P R mAP50 mAP50-95
all 1218 2703 0.416 0.439 0.427 0.191
Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size
10/10 4.63G 0.01455 1.38 1.312 82 640
10/10 4.63G 0.01424 1.462 1.31 56 640
10/10 4.63G 0.01371 1.536 1.272 53 640
10/10 4.63G 0.01373 1.566 1.261 55 640
10/10 4.63G 0.01376 1.511 1.263 85 640
10/10 4.63G 0.0139 1.507 1.272 70 640
10/10 4.63G 0.01403 1.512 1.256 75 640
10/10 4.63G 0.01404 1.483 1.256 87 640
10/10 4.63G 0.01403 1.488 1.258 49 640
10/10 4.63G 0.01428 1.506 1.29 77 640
10/10 4.63G 0.01431 1.497 1.31 80 640
10/10 4.63G 0.01425 1.491 1.312 77 640
10/10 4.63G 0.01422 1.479 1.311 73 640
10/10 4.63G 0.01426 1.474 1.319 72 640
10/10 4.63G 0.01417 1.464 1.308 77 640
10/10 4.63G 0.01413 1.454 1.317 65 640
10/10 4.63G 0.01417 1.459 1.32 67 640
10/10 4.63G 0.01409 1.453 1.318 68 640
10/10 4.63G 0.01421 1.47 1.314 114 640
10/10 4.63G 0.01418 1.467 1.315 68 640
10/10 4.63G 0.01411 1.462 1.311 47 640
10/10 4.63G 0.01408 1.461 1.312 60 640
10/10 4.63G 0.01404 1.459 1.308 58 640
10/10 4.63G 0.0141 1.461 1.307 93 640
10/10 4.63G 0.01414 1.457 1.313 73 640
10/10 4.63G 0.01411 1.457 1.311 57 640
10/10 4.63G 0.01413 1.459 1.319 70 640
10/10 4.63G 0.01406 1.457 1.315 54 640
10/10 4.63G 0.014 1.449 1.316 71 640
10/10 4.63G 0.01407 1.456 1.315 94 640
10/10 4.63G 0.0141 1.453 1.319 74 640
10/10 4.63G 0.01407 1.451 1.316 76 640
10/10 4.63G 0.014 1.448 1.312 58 640
10/10 4.63G 0.01396 1.443 1.309 61 640
10/10 4.63G 0.01395 1.441 1.307 62 640
10/10 4.63G 0.01396 1.445 1.304 69 640
10/10 4.63G 0.0139 1.446 1.298 50 640
10/10 4.63G 0.01395 1.451 1.296 65 640
10/10 4.67G 0.014 1.541 1.286 2 640
Class Images Instances P R mAP50 mAP50-95
all 1218 2703 0.394 0.459 0.429 0.191
10 epochs completed in 0.126 hours.
Optimizer stripped from runs\detect\train\xunluojiazhuang_biaozhu_3rd2\weights\last.pt, 6.2MB
Optimizer stripped from runs\detect\train\xunluojiazhuang_biaozhu_3rd2\weights\best.pt, 6.2MB
Validating runs\detect\train\xunluojiazhuang_biaozhu_3rd2\weights\best.pt...
Ultralytics YOLOv8.2.27 馃殌 Python-3.9.19 torch-2.3.0+cu118 CUDA:0 (NVIDIA GeForce RTX 2080 Ti, 11264MiB)
Model summary (fused): 168 layers, 3007013 parameters, 0 gradients, 8.1 GFLOPs
Class Images Instances P R mAP50 mAP50-95
all 1218 2703 0.395 0.46 0.43 0.191
handianduidie 611 836 0.527 0.934 0.877 0.431
xianquanyiwu 152 583 0.486 0.708 0.623 0.279
paixianbuliang 81 722 0.13 0.135 0.0724 0.0196
xianwei 188 199 0.804 0.786 0.834 0.353
dianjizangwu 60 156 0.261 0.141 0.11 0.0454
duanxian 125 207 0.161 0.0529 0.0632 0.0171
Speed: 0.1ms preprocess, 0.8ms inference, 0.0ms loss, 1.0ms postprocess per image
Results saved to [1mruns\detect\train\xunluojiazhuang_biaozhu_3rd2[0m
馃挕 Learn more at https://docs.ultralytics.com/modes/train