yolov8代码中，
# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# DOTA8 dataset 8 images from split DOTAv1 dataset by Ultralytics
# Documentation: https://docs.ultralytics.com/datasets/obb/dota8/
# Example usage: yolo train model=yolov8n-obb.pt data=dota8.yaml
# parent
# ├── ultralytics
# └── datasets
# └── dota8 ← downloads here (1MB)
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: ../datasets/NWPU_VHR-10 # dataset root dir
train: images/train # train images (relative to 'path') 4 images
val: images/val # val images (relative to 'path') 4 images
test: images/test # val images (relative to 'path') 4 images
# Classes
names:
0: airplane
1: ship
2: storage tank
3: baseball diamond
4: tennis court
5: basketball court
6: ground track field
7: harbor
8: bridge
9: vehicle
这是D:\WorkSpace\ultralytics-main\ultralytics\cfg\datasets\NWPU_VHR-10.yaml
import warnings
warnings.filterwarnings('ignore')
from ultralytics import YOLO
if __name__ == '__main__':
model = YOLO('ultralytics/cfg/models/v8/yoloe-v8.yaml')
# 如何切换模型版本, 上面的ymal文件可以改为 yolov8s.yaml就是使用的v8s,
# 类似某个改进的yaml文件名称为yolov8-XXX.yaml那么如果想使用其它版本就把上面的名称改为yolov8l-XXX.yaml即可（改的是上面YOLO中间的名字不是配置文件的）！
# model.load('yolov8m.pt') # 是否加载预训练权重,科研不建议大家加载否则很难提升精度
model.train(
data="ultralytics/cfg/datasets/NWPU_VHR-10.yaml",
# 如果大家任务是其它的'ultralytics/cfg/default.yaml'找到这里修改task可以改成detect, segment, classify, pose
cache=False,
imgsz=640,
epochs=100,
single_cls=False, # 是否是单类别检测
batch=4,
close_mosaic=0,
workers=0,
device='0',
optimizer='SGD', # using SGD
# resume=, # 这里是填写last.pt地址
amp=True, # 如果出现训练损失为Nan可以关闭amp
project='runs/train',
name='exp',
)
这是D:\WorkSpace\ultralytics-main\train.py
D:\WorkSoftware\anaconda3\envs\pytorch\python.exe D:\WorkSpace\ultralytics-main\train.py
WARNING Known issue with torch==2.4.0 on Windows with CPU, recommend upgrading to torch>=2.4.1 to resolve https://github.com/ultralytics/ultralytics/issues/15049
WARNING no model scale passed. Assuming scale='n'.
Ultralytics 8.3.127 Python-3.8.19 torch-2.4.0 CUDA:0 (NVIDIA GeForce RTX 4060 Ti, 16380MiB)
engine\trainer: agnostic_nms=False, amp=True, augment=False, auto_augment=randaugment, batch=4, bgr=0.0, box=7.5, cache=False, cfg=None, classes=None, close_mosaic=0, cls=0.5, conf=None, copy_paste=0.0, copy_paste_mode=flip, cos_lr=False, cutmix=0.0, data=D:\WorkSpace\ultralytics-main\ultralytics\cfg\datasets\NWPU_VHR-10.yaml, degrees=0.0, deterministic=True, device=cuda:0, dfl=1.5, dnn=False, dropout=0.0, dynamic=False, embed=None, epochs=100, erasing=0.4, exist_ok=False, fliplr=0.5, flipud=0.0, format=torchscript, fraction=1.0, freeze=None, half=False, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, imgsz=640, int8=False, iou=0.7, keras=False, kobj=1.0, line_width=None, lr0=0.01, lrf=0.01, mask_ratio=4, max_det=300, mixup=0.0, mode=train, model=ultralytics\cfg\models\v8\yoloe-v8.yaml, momentum=0.937, mosaic=1.0, multi_scale=False, name=exp5, nbs=64, nms=False, opset=None, optimize=False, optimizer=SGD, overlap_mask=False, patience=100, perspective=0.0, plots=True, pose=12.0, pretrained=True, profile=False, project=runs/train, rect=False, resume=False, retina_masks=False, save=True, save_conf=False, save_crop=False, save_dir=runs\train\exp5, save_frames=False, save_json=False, save_period=-1, save_txt=False, scale=0.5, seed=0, shear=0.0, show=False, show_boxes=True, show_conf=True, show_labels=True, simplify=True, single_cls=False, source=None, split=val, stream_buffer=False, task=detect, time=None, tracker=botsort.yaml, translate=0.1, val=True, verbose=True, vid_stride=1, visualize=False, warmup_bias_lr=0.1, warmup_epochs=3.0, warmup_momentum=0.8, weight_decay=0.0005, workers=0, workspace=None
Traceback (most recent call last):
File "D:\WorkSpace\ultralytics-main\ultralytics\engine\trainer.py", line 582, in get_dataset
data = check_det_dataset(self.args.data)
File "D:\WorkSpace\ultralytics-main\ultralytics\data\utils.py", line 454, in check_det_dataset
raise FileNotFoundError(m)
FileNotFoundError: Dataset 'D://WorkSpace/ultralytics-main/ultralytics/cfg/datasets/NWPU_VHR-10.yaml' images not found, missing path 'D:\WorkSpace\ultralytics-main\datasets\NWPU_VHR-10\images\val'
Note dataset download directory is 'D:\WorkSpace\ultralytics-main\datasets'. You can update this in 'C:\Users\Administrator\AppData\Roaming\Ultralytics\settings.json'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "D:\WorkSpace\ultralytics-main\train.py", line 10, in <module>
model.train(
File "D:\WorkSpace\ultralytics-main\ultralytics\engine\model.py", line 787, in train
self.trainer = (trainer or self._smart_load("trainer"))(overrides=args, _callbacks=self.callbacks)
File "D:\WorkSpace\ultralytics-main\ultralytics\models\yolo\yoloe\train.py", line 38, in __init__
super().__init__(cfg, overrides, _callbacks)
File "D:\WorkSpace\ultralytics-main\ultralytics\engine\trainer.py", line 138, in __init__
self.trainset, self.testset = self.get_dataset()
File "D:\WorkSpace\ultralytics-main\ultralytics\engine\trainer.py", line 586, in get_dataset
raise RuntimeError(emojis(f"Dataset '{clean_url(self.args.data)}' error ❌ {e}")) from e
RuntimeError: Dataset 'D://WorkSpace/ultralytics-main/ultralytics/cfg/datasets/NWPU_VHR-10.yaml' error Dataset 'D://WorkSpace/ultralytics-main/ultralytics/cfg/datasets/NWPU_VHR-10.yaml' images not found, missing path 'D:\WorkSpace\ultralytics-main\datasets\NWPU_VHR-10\images\val'
Note dataset download directory is 'D:\WorkSpace\ultralytics-main\datasets'. You can update this in 'C:\Users\Administrator\AppData\Roaming\Ultralytics\settings.json'
Process finished with exit code 1
这是报错信息
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