This thread has been locked.
If you have a related question, please click the "Ask a related question" button in the top right corner. The newly created question will be automatically linked to this question.
Part Number: TDA2EVM5777
Hello,
Since the provided testing python script for caffe jacinto trained SSD models doesn't support quantization. I wonder does TI or anywhere else has the python API to quantize models for accuracy testing?
The testing we are doing is not just hit or miss, but evaluating the offsets of accuracy in cm compare to ground truth.
Thanks,
Wei Chih
Hi Wei Chih,
We do not support quantizing the models in Caffe - but you can do that directly in TIDL for TDA2x. But if your purpose is just to get an approximate sense of accuracy, we have it in our scripts.
For example, this script: https://git.ti.com/cgit/jacinto-ai-devkit/caffe-jacinto-models/tree/scripts/train_imagenet_classification.sh
has a last phase called test_quantize that reports rough accuracy with quantization. An example config file and log is captured here:
But this has not been matched properly with what TIDL produces and may not always be correct.
Your best bet is to measure the accuracy using TIDL.
Best regards,