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Some questions about OpenVINO Post-Training Optimization Tool (POT)

New Contributor I
Some questions about OpenVINO Post-Training Optimization Tool (POT) 

I would like to ask some questions about OpenVINO Post-Training Optimization Tool (POT).

My task is to quantify the YOLOv4-Tiny model of FP32 and FP16 into an INT8 model.

I have referred to similar questions, but I have successfully quantified YOLOv4-Tiny Model (FP32-INT8/FP16-INT8) in OpenVINO 2021.3 and used it normally.

I refer to the parameters of OpenVINO Accuracy Checker Tool to configure the json file needed by POT.

The quantification can be successful, but the mAP after verification is always 0. I want to know where I went wrong.

Please check my attachment, thank you.

My OpenVINO Post-Training Optimization Tool and OpenVINO Accuracy Checker Tool are installed correctly. The version of OpenVINO I use is 2021.3.
The instructions I use are:


pot -c yolov4-tiny_voc.json --output-dir backup -e

The results that appear are as follows:

INFO:compression.pipeline.pipeline:Evaluation of generated model
INFO:compression.engines.ac_engine:Start inference on the whole dataset
Total dataset size: 26
26 objects processed in 1.023 seconds
INFO:compression.engines.ac_engine:Inference finished 0.0


accuracy_check -c yolov4-tiny_voc.yml -td CPU

The results that appear are as follows:

26 objects processed in 16.514 seconds
09:50:28 accuracy_checker WARNING: /opt/intel/openvino_2021/deployment_tools/open_model_zoo/tools/accuracy_checker/accuracy_checker/metrics/ UserWarning: No detections to compute mAP
warnings.warn("No detections to compute mAP")

map: 0.00%
AP@0.5: 0.00%
AP@0.5:0.05:95: 0.00%

Please help me, why mAP is always 0, please refer to my attachment.

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Hello Peng Chang-Jan,


I noticed that this is a duplicate case. Please refer to this thread for the discussion. Therefore this thread is no longer be monitored by intel.