MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
MobileNetV2: Inverted Residuals and Linear Bottlenecks
Results of accuracy evaluation with tools/eval.
| Models | Top-1 Accuracy | Top-5 Accuracy |
|---|---|---|
| MobileNet V1 | 67.64 | 87.97 |
| MobileNet V1 quant | 55.53 | 78.74 |
| MobileNet V2 | 69.44 | 89.23 |
| MobileNet V2 quant | 68.37 | 88.56 |
*: 'quant' stands for 'quantized'.
Run the following command to try the demo:
# MobileNet V1
python demo.py --input /path/to/image
# MobileNet V2
python demo.py --input /path/to/image --model v2All files in this directory are licensed under Apache 2.0 License.
- MobileNet V1: https://arxiv.org/abs/1704.04861
- MobileNet V2: https://arxiv.org/abs/1801.04381
- MobileNet V1 weight and scripts for training: https://github.com/wjc852456/pytorch-mobilenet-v1
- MobileNet V2 weight: https://github.com/onnx/models/tree/main/vision/classification/mobilenet