| # TensorFlow Inception V3 QAT | |
| ## Model Source | |
| The model used in this example come from: | |
| https://storage.googleapis.com/download.tensorflow.org/models/tflite_11_05_08/inception_v3_quant.tgz | |
| ## Script Usage | |
| *Usage:* | |
| ``` | |
| python test.py | |
| ``` | |
| *rknn_convert usage:* | |
| ``` | |
| python3 -m rknn.api.rknn_convert -t rk3568 -i ./model_config.yml -o ./ | |
| ``` | |
| *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'. | |
| - This is a QAT model, and the do_quantization of rknn.build needs to be set to False. | |
| ## Expected Results | |
| This example will print the TOP5 labels and corresponding scores of the test image classification results, as follows: | |
| ``` | |
| -----TOP 5----- | |
| [ 2] score:0.996572 class:"goldfish, Carassius auratus" | |
| [ 408] score:0.000464 class:"ambulance" | |
| [ 795] score:0.000201 class:"shower curtain" | |
| [ 352] score:0.000070 class:"hartebeest" | |
| [ 974] score:0.000051 class:"coral reef" | |
| ``` | |
| - Note: Different platforms, different versions of tools and drivers may have slightly different results. |