(yolo11) D:\2026\ultralytics-yolo11-main>D:/anaconda3/envs/yolo11/python.exe d:/2026/ultralytics-yolo11-main/train.py
Ultralytics 8.3.9 🚀 Python-3.9.23 torch-2.0.1+cu117 CUDA:0 (NVIDIA GeForce RTX 3050 Laptop GPU, 4096MiB)
engine\trainer: task=detect, mode=train, model=D:/2026/ultralytics-yolo11-main/ultralytics/cfg/models/11/yolo11n.yaml, data=D:/2026/YOLOv11/datasets/potholes/d.yaml, epochs=100, time=None, patience=100, batch=4, imgsz=640, save=True, save_period=-1, cache=False, device=None, workers=0, project=D:/2026/ultralytics-yolo11-main/runs/train, name=232, exist_ok=False, pretrained=True, optimizer=SGD, verbose=True, seed=0, deterministic=True, single_cls=False, rect=False, cos_lr=False, close_mosaic=0, resume=None, 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=True, opset=None, workspace=4, nms=False, lr0=0.005, lrf=0.01, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=7.5, cls=0.5, dfl=1.5, pose=12.0, kobj=1.0, label_smoothing=0.0, nbs=64, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.1, scale=0.5, 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, copy_paste_mode=flip, auto_augment=randaugment, erasing=0.4, crop_fraction=1.0, cfg=None, tracker=botsort.yaml, save_dir=D:\2026\ultralytics-yolo11-main\runs\train\exp+2025\7\232
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 6640 ultralytics.nn.modules.block.C3k2 [32, 64, 1, False, 0.25]
3 -1 1 36992 ultralytics.nn.modules.conv.Conv [64, 64, 3, 2]
4 -1 1 26080 ultralytics.nn.modules.block.C3k2 [64, 128, 1, False, 0.25]
5 -1 1 147712 ultralytics.nn.modules.conv.Conv [128, 128, 3, 2]
6 -1 1 87040 ultralytics.nn.modules.block.C3k2 [128, 128, 1, True]
7 -1 1 295424 ultralytics.nn.modules.conv.Conv [128, 256, 3, 2]
8 -1 1 346112 ultralytics.nn.modules.block.C3k2 [256, 256, 1, True]
9 -1 1 164608 ultralytics.nn.modules.block.SPPF [256, 256, 5]
10 -1 1 249728 ultralytics.nn.modules.block.C2PSA [256, 256, 1]
11 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
12 [-1, 6] 1 0 ultralytics.nn.modules.conv.Concat [1]
13 -1 1 111296 ultralytics.nn.modules.block.C3k2 [384, 128, 1, False]
14 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
15 [-1, 4] 1 0 ultralytics.nn.modules.conv.Concat [1]
16 -1 1 32096 ultralytics.nn.modules.block.C3k2 [256, 64, 1, False]
17 -1 1 36992 ultralytics.nn.modules.conv.Conv [64, 64, 3, 2]
18 [-1, 13] 1 0 ultralytics.nn.modules.conv.Concat [1]
19 -1 1 86720 ultralytics.nn.modules.block.C3k2 [192, 128, 1, False]
20 -1 1 147712 ultralytics.nn.modules.conv.Conv [128, 128, 3, 2]
21 [-1, 10] 1 0 ultralytics.nn.modules.conv.Concat [1]
22 -1 1 378880 ultralytics.nn.modules.block.C3k2 [384, 256, 1, True]
23 [16, 19, 22] 1 430867 ultralytics.nn.modules.head.Detect [1, [64, 128, 256]]
YOLO11n summary: 319 layers, 2,590,035 parameters, 2,590,019 gradients, 6.4 GFLOPs
Freezing layer 'model.23.dfl.conv.weight'
AMP: running Automatic Mixed Precision (AMP) checks with YOLO11n...
AMP: checks passed ✅
train: Scanning D:\2026\YOLOv11\datasets\potholes\train\labels... 263 images, 2709 backgrounds, 1 corrupt: 100%|██████████| 2973/2973 [00:01<00:00, 2478.82
train: WARNING ⚠️ D:\2026\YOLOv11\datasets\potholes\train\images\01883.jpg: ignoring corrupt image/label: invalid image format GIF. Supported formats are:
images: {'webp', 'jpeg', 'pfm', 'bmp', 'mpo', 'tif', 'tiff', 'png', 'jpg', 'dng'}
videos: {'mp4', 'mpeg', 'mov', 'asf', 'wmv', 'avi', 'mpg', 'gif', 'webm', 'ts', 'mkv', 'm4v'}
train: New cache created: D:\2026\YOLOv11\datasets\potholes\train\labels.cache
Traceback (most recent call last):
File "d:\2026\ultralytics-yolo11-main\ultralytics\data\base.py", line 121, in get_img_files
assert im_files, f"{self.prefix}No images found in {img_path}. {FORMATS_HELP_MSG}"
AssertionError: val: No images found in D:\2026\YOLOv11\datasets\potholes\val. Supported formats are:
images: {'webp', 'jpeg', 'pfm', 'bmp', 'mpo', 'tif', 'tiff', 'png', 'jpg', 'dng'}
videos: {'mp4', 'mpeg', 'mov', 'asf', 'wmv', 'avi', 'mpg', 'gif', 'webm', 'ts', 'mkv', 'm4v'}
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "d:\2026\ultralytics-yolo11-main\train.py", line 32, in <module>
model.train(data='D:/2026/YOLOv11/datasets/potholes/d.yaml', # 选择数据集配置路径
File "d:\2026\ultralytics-yolo11-main\ultralytics\engine\model.py", line 802, in train
self.trainer.train()
File "d:\2026\ultralytics-yolo11-main\ultralytics\engine\trainer.py", line 208, in train
self._do_train(world_size)
File "d:\2026\ultralytics-yolo11-main\ultralytics\engine\trainer.py", line 328, in _do_train
self._setup_train(world_size)
File "d:\2026\ultralytics-yolo11-main\ultralytics\engine\trainer.py", line 295, in _setup_train
self.test_loader = self.get_dataloader(
File "d:\2026\ultralytics-yolo11-main\ultralytics\models\yolo\detect\train.py", line 50, in get_dataloader
dataset = self.build_dataset(dataset_path, mode, batch_size)
File "d:\2026\ultralytics-yolo11-main\ultralytics\models\yolo\detect\train.py", line 43, in build_dataset
return build_yolo_dataset(self.args, img_path, batch, self.data, mode=mode, rect=mode == "val", stride=gs)
File "d:\2026\ultralytics-yolo11-main\ultralytics\data\build.py", line 87, in build_yolo_dataset
return dataset(
File "d:\2026\ultralytics-yolo11-main\ultralytics\data\dataset.py", line 64, in __init__
super().__init__(*args, **kwargs)
File "d:\2026\ultralytics-yolo11-main\ultralytics\data\base.py", line 73, in __init__
self.im_files = self.get_img_files(self.img_path)
File "d:\2026\ultralytics-yolo11-main\ultralytics\data\base.py", line 123, in get_img_files
raise FileNotFoundError(f"{self.prefix}Error loading data from {img_path}\n{HELP_URL}") from e
FileNotFoundError: val: Error loading data from D:\2026\YOLOv11\datasets\potholes\val
See https://docs.ultralytics.com/datasets for dataset formatting guidance.
最新发布
原因就是下面这个，修改文件夹名字后记得改路径啊家人们
博客提到修改文件夹名字后，记得更改路径，完成这些操作后就可以开始训练，涉及深度学习相关训练准备工作。
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