YOLO-Tutorial-v2/iclab

General Image Classification Laboratory

Train a CNN

We have kindly provided a bash script train.sh to train the models. You can modify some hyperparameters in the script file according to your own needs.

For example, we are going to use 8 GPUs to train ELANDarkNet-S designed in this repo, so we can use the following command:

bash train.sh elandarknet_s imagenet_1k path/to/imagnet_1k 8 1699 None

Evaluate a CNN

• Evaluate the top1 & top5 accuracy of ViT-Tiny on ImageNet-1K dataset:

  python main.py --cuda -dataset imagenet_1k --root path/to/imagnet_1k -m elandarknet_s --batch_size 256 --img_size 224 --eval --resume path/to/elandarknet_s.pth
  

Experimental results

Tips:

• Weak augmentation: includes random hflip and random crop resize.
• Strong augmentation: includes mixup, cutmix, rand aug, random erase and so on. However, we don't use the strong augmentation.
• The AdamW with weight decay = 0.05 and base lr = 4e-3 (for bs of 4096) is deployed as the optimzier, and the CosineAnnealingLR is deployed as the lr scheduler, where the min lr is set to 1e-6.

ImageNet-1K

• Modified DarkNet (Yolov3's DarkNet with width and depth scaling factors)

Model	Augment	Batch	Epoch	size	acc@1	GFLOPs	Params	Weight
DarkNet-S	weak	4096	100	224	68.5	1.6	4.6 M	ckpt
DarkNet-M	weak	4096	100	224
DarkNet-L	weak	4096	100	224
DarkNet-X	weak	4096	100	224

• Modified CSPDarkNet (Yolov5's DarkNet with width and depth scaling factors)

Model	Augment	Batch	Epoch	size	acc@1	GFLOPs	Params	Weight
CSPDarkNet-S	weak	4096	100	224	70.2	1.3	4.0 M	ckpt
CSPDarkNet-M	weak	4096	100	224
CSPDarkNet-L	weak	4096	100	224
CSPDarkNet-X	weak	4096	100	224

• ElANDarkNet (Yolov8's backbone)

Model	Augment	Batch	Epoch	size	acc@1	GFLOPs	Params	Weight
ElANDarkNet-N	weak	4096	100	224	62.1	0.38	1.36 M	ckpt
ElANDarkNet-S	weak	4096	100	224	71.3	1.48	4.94 M	ckpt
ElANDarkNet-M	weak	4096	100	224		4.67	11.60 M
ElANDarkNet-L	weak	4096	100	224		10.47	19.66 M
ElANDarkNet-X	weak	4096	100	224		20.56	37.86 M

• GELAN (Proposed by YOLOv9)

Model	Augment	Batch	Epoch	size	acc@1	GFLOPs	Params	Weight
GELAN-S	weak	4096	100	224	68.4	0.9	1.9 M	ckpt
GELAN-C	weak	4096	100	224		5.2	8.8 M	[ckpt]()