vptyp/gstAutotest
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move testing commands under if __main__

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This commit is contained in:
Artur 2025-10-12 16:30:38 +03:00
parent 7bff99a6c7
commit 76f852f856
3 changed files with 35 additions and 31 deletions
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1
gstreamerAutotest.py
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@ -224,4 +224,5 @@ def run_autotest():
qualityDataframe.to_csv(f"qualityResults{encoder}.csv") qualityDataframe.to_csv(f"qualityResults{encoder}.csv")
latencyDataframe.to_csv(f"latencyDataframe{encoder}.csv") latencyDataframe.to_csv(f"latencyDataframe{encoder}.csv")
if __name__ == "__main__":
run_autotest() run_autotest()

3
latencyParse.py
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@ -93,4 +93,5 @@ def getLatencyTable(filename):
print(resultDf) print(resultDf)
return resultDf return resultDf
# getLatencyTable("latency_traces-x264enc-kpop-test-10.log") if __name__ == "__main__":
getLatencyTable("latency_traces-x264enc-kpop-test-10.log")

60
qa.py
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@ -79,40 +79,42 @@ def parse_quality_report(psnr_metrics, ssim_metrics):
combined = combined.fillna(0) combined = combined.fillna(0)
return combined return combined
# psnr, ssim = run_quality_check(
# "base-x264enc-kpop-test-10.yuv",
# "encoded-x264enc-kpop-test-10.mp4",
# "-pixel_format yuv420p -color_range tv -video_size 1920x1080 -framerate 23.98 "
# )
# combined = parse_quality_report( if __name__ == "__main__":
# psnr, psnr, ssim = run_quality_check(
# ssim "base-x264enc-kpop-test-10.yuv",
# ) "encoded-x264enc-kpop-test-10.mp4",
"-pixel_format yuv420p -color_range tv -video_size 1920x1080 -framerate 23.98 "
)
# encoder = "x264enc" combined = parse_quality_report(
# profile = "main" psnr,
# params = "bitrate=5000" ssim
)
# columns = pd.MultiIndex.from_tuples( encoder = "x264enc"
# [(encoder, profile, params, col) for col in combined.columns] profile = "main"
# ) params = "bitrate=5000"
# combined.columns = columns columns = pd.MultiIndex.from_tuples(
[(encoder, profile, params, col) for col in combined.columns]
)
# main_df = combined combined.columns = columns
# profile = "baseline"
# combined2 = parse_quality_report( main_df = combined
# psnr, profile = "baseline"
# ssim
# )
# columns = pd.MultiIndex.from_tuples(
# [(encoder, profile, params, col) for col in combined2.columns]
# )
# combined2.columns = columns
# main_df = pd.concat([main_df, combined2], axis=1)
# print(main_df)
# main_df.to_csv("quality_report.csv") combined2 = parse_quality_report(
psnr,
ssim
)
columns = pd.MultiIndex.from_tuples(
[(encoder, profile, params, col) for col in combined2.columns]
)
combined2.columns = columns
main_df = pd.concat([main_df, combined2], axis=1)
print(main_df)
main_df.to_csv("quality_report.csv")