PMG model can be used for fine-grained goods product recognition, for example, RP2K dataset. The model is Resnet18-based and the detailed model structure is shown in the picture below. On rp2k dataset, this model can achieve 96.4% top-1 float accuracy with 13.82M parameters and 2.28G Flops. Model final deployment and quantization top-1 accuracy are 96.19% and 96.18%, respectively.
Figure 1. Production Recognition Example
The following table lists the PMG models supported by the Vitis AI library.
| No | Model Name | Framework |
|---|---|---|
| 1 | pmg_pt | PyTorch |