From dd6da41b0d538fd44218e73022a0c5af4ec18619 Mon Sep 17 00:00:00 2001
From: Artur Mukhamadiev <artur.mukhamadiev@lge.com>
Date: Sat, 11 Oct 2025 18:13:37 +0300
Subject: [PATCH] [autotest] add autorepeats

:Release Notes:
-

:Detailed Notes:
-

:Testing Performed:
-

:QA Notes:
-

:Issues Addressed:
-
---
 PyScripts/gstreamerAutotest.py | 77 ++++++++++++++++++----------------
 1 file changed, 40 insertions(+), 37 deletions(-)

diff --git a/PyScripts/gstreamerAutotest.py b/PyScripts/gstreamerAutotest.py
index f47487a..094f001 100644
--- a/PyScripts/gstreamerAutotest.py
+++ b/PyScripts/gstreamerAutotest.py
@@ -52,6 +52,8 @@ psnr_check = {
 
 with_docker = [ "nvv4l2h264enc" ]
 
+repeats = 3 
+
 formats = {
     "x264enc": "I420",
     "nvh264enc": "NV12",
@@ -239,43 +241,44 @@ def run_autotest():
         for params in combinations:
             for profile in profiles:
                 for videoName, videoPath in videos.items():
-                    filename = "autotest-" + encoder + "-" + profile + "-test-" + videoName + ".mp4"
-                    pipeline = Pipeline()
-                    pipeline = ( 
-                        pipeline.add_tracing()
-                        .add_source(makeVideoSrc(videoName))
-                        .add_encoder(encoder, params.split(" "))
-                        .add_profile(profile)
-                        .to_file(filename)
-                    )
-                    print(pipeline.pipeline)
-                    try:
-                        run_pipeline(pipeline.pipeline)
-                    except Exception as e:
-                        print(f"Error occurred: {e}")
-                        continue
-                    psnr_metrics, ssim_metrics = qa.run_quality_check(
-                        videoPath, 
-                        filename, 
-                        video_info[videoName] + " " + psnr_check[encoder]
-                    ) 
-                    dfPsnr = qa.parse_quality_report(psnr_metrics, ssim_metrics)
-                    print("-----")
-                    dfLatency = getLatencyTable(latency_filename)
-                    columnsQ = pd.MultiIndex.from_tuples(
-                        [(encoder, profile, videoName, params, col) for col in dfPsnr.columns]
-                    )
-                    columnsLatency = pd.MultiIndex.from_tuples(
-                        [(encoder, profile, videoName, params, col) for col in dfLatency.columns]
-                    )
-                    dfPsnr.columns = columnsQ
-                    dfLatency.columns = columnsLatency
-                    qualityDataframe = pd.concat([qualityDataframe, dfPsnr], axis=1)
-                    latencyDataframe = pd.concat([latencyDataframe, dfLatency], axis=1)
-                    print("=====")
-                    print("Current results:")
-                    print(dfPsnr)
-                    print(dfLatency)
+                    for _ in range(repeats):
+                        filename = "autotest-" + encoder + "-" + profile + "-test-" + videoName + ".mp4"
+                        pipeline = Pipeline()
+                        pipeline = ( 
+                            pipeline.add_tracing()
+                            .add_source(makeVideoSrc(videoName))
+                            .add_encoder(encoder, params.split(" "))
+                            .add_profile(profile)
+                            .to_file(filename)
+                        )
+                        print(pipeline.pipeline)
+                        try:
+                            run_pipeline(pipeline.pipeline)
+                        except Exception as e:
+                            print(f"Error occurred: {e}")
+                            continue
+                        psnr_metrics, ssim_metrics = qa.run_quality_check(
+                            videoPath, 
+                            filename, 
+                            video_info[videoName] + " " + psnr_check[encoder]
+                        ) 
+                        dfPsnr = qa.parse_quality_report(psnr_metrics, ssim_metrics)
+                        print("-----")
+                        dfLatency = getLatencyTable(latency_filename)
+                        columnsQ = pd.MultiIndex.from_tuples(
+                            [(encoder, profile, videoName, params, col) for col in dfPsnr.columns]
+                        )
+                        columnsLatency = pd.MultiIndex.from_tuples(
+                            [(encoder, profile, videoName, params, col) for col in dfLatency.columns]
+                        )
+                        dfPsnr.columns = columnsQ
+                        dfLatency.columns = columnsLatency
+                        qualityDataframe = pd.concat([qualityDataframe, dfPsnr], axis=1)
+                        latencyDataframe = pd.concat([latencyDataframe, dfLatency], axis=1)
+                        print("=====")
+                        print("Current results:")
+                        print(dfPsnr)
+                        print(dfLatency)
         qualityDataframe.to_csv(f"qualityResults{encoder}.csv")
         latencyDataframe.to_csv(f"latencyDataframe{encoder}.csv")