| # How to convert multi-input model | |
| ## Model Source | |
| The model used in this example come from 'gen_pb.py'. | |
| ## Script Usage | |
| *Usage:* | |
| ``` | |
| python test.py | |
| ``` | |
| *Description:* | |
| - The default target platform in script is 'rk3566', please modify the 'target_platform' parameter of 'rknn.config' according to the actual platform. | |
| - If connecting board is required, please add the 'target' parameter in 'rknn.init_runtime'. | |
| - The model has multiple inputs, so multiple input files need to be set in 'dataset.txt': | |
| ``` | |
| dog_128x128.jpg input2.npy input3.npy dog_128x128_gray.png | |
| ``` | |
| - The 'inputs' and 'data_format' of 'rknn.inference' should also be set accordingly, as follows: | |
| ``` | |
| rknn.inference(inputs=[img, input2, input3, img_gray], data_format=['nhwc', 'nchw', 'nchw', 'nhwc']) | |
| ``` | |
| ## Expected Results | |
| This example will print outputs of inference, as follows: | |
| ``` | |
| inference result: [array([[ -3.1041162, -7.0548096, -5.361655 , ..., -14.391811 , | |
| -15.802773 , -11.287695 ]], dtype=float32)] | |
| ``` | |
| - Note: Different platforms, different versions of tools and drivers may have slightly different results. |