56 lines
1.8 KiB
ReStructuredText
56 lines
1.8 KiB
ReStructuredText
.. _analytics_stamp:
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Analyze Time Stamps
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====================
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SDK provides a script for timestamp analysis ``stamp_analytics.py`` . Tool details are visible in `tools/README.md <https://github.com/slightech/MYNT-EYE-S-SDK/tree/master/tools>`_ .
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Reference run commands and results on Linux:
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.. code-block:: bash
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$ python tools/analytics/stamp_analytics.py -i dataset -c tools/config/mynteye/mynteye_config.yaml
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stamp analytics ...
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input: dataset
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outdir: dataset
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open dataset ...
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save to binary files ...
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binimg: dataset/stamp_analytics_img.bin
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binimu: dataset/stamp_analytics_imu.bin
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img: 1007, imu: 20040
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rate (Hz)
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img: 25, imu: 500
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sample period (s)
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img: 0.04, imu: 0.002
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diff count
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imgs: 1007, imus: 20040
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imgs_t_diff: 1006, imus_t_diff: 20039
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diff where (factor=0.1)
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imgs where diff > 0.04*1.1 (0)
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imgs where diff < 0.04*0.9 (0)
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imus where diff > 0.002*1.1 (0)
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imus where diff < 0.002*0.9 (0)
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image timestamp duplicates: 0
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save figure to:
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dataset/stamp_analytics.png
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stamp analytics done
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The analysis result graph will be saved in the dataset directory, as follows:
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.. image:: ../../../images/sdk/tools/stamp_analytics.png
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In addition, the script specific options can be executed ``-h`` to understand:
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.. code-block:: bash
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$ python tools/analytics/stamp_analytics.py -h
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.. tip::
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Suggestions when recording data sets ``record.cc`` annotation display image inside ``cv::imshow()``, ``dataset.cc`` annotation display image inside ``cv::imwrite()`` . Because these operations are time-consuming, they can cause images to be discarded. In other words, consumption can't keep up with production, so some images are discarded. ``GetStreamDatas()`` used in ``record.cc`` only caches the latest 4 images.
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