Shuffle Attention for MobileNetV3
Attempt | Parameters | Madds | Top1-acc | Sample visualization |
---|---|---|---|---|
MobileNetV3-Large | 5.4 M | 448.69 M | 75.2% | |
SA-MobileNetV3-Large | 3.9 M | 445.68 M | 76.8% |
Attempt | Parameters | Madds | Top1-acc | Sample visualization |
---|---|---|---|---|
MobileNetV3-Large | 4.2 M | 446.16 M | ||
SA-MobileNetV3-Large | 2.7 M | 443.14 M |
Attempt | Parameters | Madds | Top1-acc | Sample visualization | Sample visualization |
---|---|---|---|---|---|
MobileNetV3-Large | 4.2 M | 446.16 M | 0.997% | ![]() | ![]() |
SA-MobileNetV3-Large | 2.7 M | 443.14 M | 0.998% | ![]() | ![]() |
Run the following command for train model on your own dataset:
python train.py --dataset mnist
Run the following command for evaluation trained model on test dataset:
python test.py --dataset mnist
Run the following command for classification images:
python predict.py --input /path/to/image.jpg
Please cite our paper if you find this repo useful in your research.
@article{
}
Author: SajjadAemmi
Official Website: https://github.com/SajjadAemmi/SA-MobileNetV3