model = YOLO('ultralytics/cfg/models/v8/yolov8n.yaml')
model.load('yolov8n.pt') # loading pretrain weights
model.train(data='/root/group/lyBaseModel/ultralytics-main/dataset/data01.yaml',
cache=False,
imgsz=640,
epochs=200,
batch=24,
close_mosaic=0,
workers=4,
device=[0, 1, 2],
optimizer='Adam', # using SGD
# patience=0, # close earlystop
# resume='', # last.pt path
# amp=False, # close amp
# fraction=0.2,
project='runs/train',
name='exp',
)
保存了训练的图片和标签、不加预训练权重
model = YOLO('ultralytics/cfg/models/v8/yolov8n.yaml')
#model.load('yolov8n.pt') # loading pretrain weights
model.train(data='/root/group/lyBaseModel/ultralytics-main/dataset/data01.yaml',
cache=False,
imgsz=640,
epochs=200,
batch=24,
close_mosaic=0,
workers=4,
device=[0, 1, 2],
optimizer='Adam', # using SGD
# patience=0, # close earlystop
# resume='', # last.pt path
# amp=False, # close amp
# fraction=0.2,
project='runs/train',
name='exp',
) 
DCNv4
backbone:
# [from, repeats, module, args]
- [-1, 1, Conv, [64, 3, 2]] # 0-P1/2
- [-1, 1, Conv, [128, 3, 2]] # 1-P2/4
- [-1, 3, C2f, [128, True]]
- [-1, 1, Conv, [256, 3, 2]] # 3-P3/8
- [-1, 6, C2f, [256, True]]
- [-1, 1, Conv, [512, 3, 2]] # 5-P4/16
- [-1, 6, C2f, [512, True]]
- [-1, 1, Conv, [1024, 3, 2]] # 7-P5/32
- [-1, 3, C2f_DCNv4, [1024, True]]
- [-1, 1, SPPF, [1024, 5]] # 9
DCNv3
yolov8-SPPF-LSKA
SPPF-LSKA+Dattention
FPS:88.0
原地不动
