| # Example of resnet18 | |
| ## Model Source | |
| ### Original model | |
| The models used in this example come from the torchvision project: | |
| https://github.com/pytorch/vision/tree/main/torchvision/models | |
| ### Convert to RKNN model | |
| Please refer to the example in the RKNN Toolkit2 project to generate the RKNN model: | |
| https://github.com/rockchip-linux/rknn-toolkit2/tree/master/examples/pytorch/resnet18 | |
| ## Script Usage | |
| Usage | |
| ``` | |
| python test.py | |
| ``` | |
| ## Expected results | |
| This example will print the TOP5 labels and corresponding scores of the test image classification results. For example, the inference results of this example are as follows: | |
| ``` | |
| -----TOP 5----- | |
| [812] score:0.999680 class:"space shuttle" | |
| [404] score:0.000249 class:"airliner" | |
| [657] score:0.000013 class:"missile" | |
| [466] score:0.000009 class:"bullet train, bullet" | |
| [895] score:0.000008 class:"warplane, military plane" | |
| ``` | |
| 1. The label index with the highest score is 812, the corresponding label is `space shuttle`. | |
| 2. Different platforms, different versions of tools and drivers may have slightly different results. | |