Implemenation of Selective Kernel Networks by pytorch.

The architecture of SK is as follows

I trained SKNet50 on ImageNet-2012 from scratch and got an accuracy of 21.26, which did not reach the performance of 20.79 in the paper. If somebody know what caused the problem, please leave me a message.

The pretrained weights are provided below.

• pytorch 1.4.0+
• torchvision
• tensorboard 1.14+
• numpy
• pyyaml
• tqdm
• pillow

• ImageNet-2012

1. place the downloaded pretrained model in runs/sknet_imagenet/86028 folder under this project
2. config the attribute of runid and cuda in the config file configs/sknet_imagenet.yml
3. run validata.py or test.py (For test, you should specify the img_path in the test.py)