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tf_model_dir=/home/xxx/ml_work/dnn-models/tensorflow
336 0.0000000 label #336
168 0.0000000 label #168
99 0.0000000 label #99
44 0.0000000 label #44
378 0.0000000 label #378
153 0.0000000 label #153
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Hi Wang,
The problem here is that you don't have the normalization values that were used when training for the models so the results will be incorrect without you supplying those at the time that your run model optimizer with the --mean_values and --scale_values parameter. I've reproduced the incorrect result with the mobilenet V1 224x224 model case, classification sample, and a different cat picture and then I added --scale_values [255,255,255] to the model optimizer command line. Let me know if this helps.
We are looking to improve documentation by putting the normalization parameters(--mean_values and --scale values) in documentation so that you can render the correct results.
Kind Regards,
Monique Jones
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Hi Wang,
The problem here is that you don't have the normalization values that were used when training for the models so the results will be incorrect without you supplying those at the time that your run model optimizer with the --mean_values and --scale_values parameter. I've reproduced the incorrect result with the mobilenet V1 224x224 model case, classification sample, and a different cat picture and then I added --scale_values [255,255,255] to the model optimizer command line. Let me know if this helps.
We are looking to improve documentation by putting the normalization parameters(--mean_values and --scale values) in documentation so that you can render the correct results.
Kind Regards,
Monique Jones
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Hi Wang,
The loss of accuracy would be due to the normalization values not being exactly what the training normalization values are. This can be found usually in the published paper on the model, in the model zoo, or comments of the source code of the model. You can also play with the values as well.
Kind Regards,
Monique Jones
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