diff --git a/.vscode/settings.json b/.vscode/settings.json index a490b61..3d4d142 100644 --- a/.vscode/settings.json +++ b/.vscode/settings.json @@ -1,5 +1,9 @@ { "githubPullRequests.ignoredPullRequestBranches": [ "main" - ] + ], + "[python]": { + "editor.defaultFormatter": "ms-python.black-formatter" + }, + "python.formatting.provider": "none" } \ No newline at end of file diff --git a/audiodata.csv b/audiodata.csv new file mode 100644 index 0000000..e16c76d --- /dev/null +++ b/audiodata.csv @@ -0,0 +1 @@ +"" diff --git a/nulrdcscripts/staging/vqc/QCScript.py b/nulrdcscripts/staging/vqc/QCScript.py index e69de29..53cefc3 100644 --- a/nulrdcscripts/staging/vqc/QCScript.py +++ b/nulrdcscripts/staging/vqc/QCScript.py @@ -0,0 +1,8 @@ +import videoanalyses.fbyfYUV as fbyfYUV +from setupsteps import setup + +videoBitDepth = setup.setVideoBitDepth("--10bit") +videoBitDepth = setup.setvideobitdepthstandard(videoBitDepth) +videodata = "data\data.txt" + +errors = fbyfYUV.checkerrors(videodata, videoBitDepth) diff --git a/nulrdcscripts/staging/vqc/README.md b/nulrdcscripts/staging/vqc/__init__.py similarity index 100% rename from nulrdcscripts/staging/vqc/README.md rename to nulrdcscripts/staging/vqc/__init__.py diff --git a/nulrdcscripts/staging/vqc/data/ReferenceData10Bit.txt b/nulrdcscripts/staging/vqc/data/ReferenceData10Bit.txt new file mode 100644 index 0000000..6aa84be --- /dev/null +++ b/nulrdcscripts/staging/vqc/data/ReferenceData10Bit.txt @@ -0,0 +1,36 @@ +10 Bit Data Ranges for Average Videos + +Digital Luma Range: 64-940 +Digital Chroma Range: 64 - 960 +Ideal U & V Range: 340 - 680 +Yav: ~512 +Yrang: ~516 - 876 +Uav: ~512 +Vav: ~512 +TOUT: 0 - 0.009 +TOUTc: <10 +SAT Ideal Range: 0 - 88.7 +SATb: <1000 frames +SATi: <1000 frames +Hue Ideal Range: 480 - 588 (for skin tones) +BRNGav: <0.02 +BRNGc: <1000 +MSEf: ~0 +MSEfY: <10 +VREP Ideal: 0 + +Y Channel Range: 0-1020 IRE +Y Channel Ideal Range: 64 - 940 IRE + Y LOW : 64 IRE + Y AVG : 512 IRE + Y HIGH : 940 IRE + +U Channel Ideal Range: 340 - 680 IRE +V Channel Ideal Range: 340 - 680 IRE + + +YUV Diff : Closer to 0 the better + +SAT Ideal RAnge: 0 - 354.8 + + diff --git a/nulrdcscripts/staging/vqc/ReferenceData.txt b/nulrdcscripts/staging/vqc/data/__init__.py similarity index 100% rename from nulrdcscripts/staging/vqc/ReferenceData.txt rename to nulrdcscripts/staging/vqc/data/__init__.py diff --git a/nulrdcscripts/staging/vqc/data/dataframe.py b/nulrdcscripts/staging/vqc/data/dataframe.py new file mode 100644 index 0000000..45179bd --- /dev/null +++ b/nulrdcscripts/staging/vqc/data/dataframe.py @@ -0,0 +1,10 @@ +import pandas as pd + +csv = "Video8BitValues.csv" + +df = pd.read_csv(csv, index_col="criteria") +criteriaToCheck = "brngout" +criteria = "uhigh" +extraction = df.at[criteria, criteriaToCheck] + +print(extraction) diff --git a/nulrdcscripts/staging/vqc/data/severityLevels.py b/nulrdcscripts/staging/vqc/data/severityLevels.py new file mode 100644 index 0000000..0723dfa --- /dev/null +++ b/nulrdcscripts/staging/vqc/data/severityLevels.py @@ -0,0 +1,4 @@ +vrep = "CRITICAL" +tout = "CRITICAL" +brngout = "MODERATE" +clipping = "CRITICAL" diff --git a/nulrdcscripts/staging/vqc/data/test.py b/nulrdcscripts/staging/vqc/data/test.py new file mode 100644 index 0000000..a54e870 --- /dev/null +++ b/nulrdcscripts/staging/vqc/data/test.py @@ -0,0 +1,90 @@ +import videovalues10Bit + +videodata = "baddata.csv" + + +def runLOW(criteria): + criteria = criteria + "low" + return criteria + + +def runHIGH(criteria): + criteria = criteria + "high" + return criteria + + +def checkLOWHIGH(videodata, videoBitDepth, fullCriteria): + criteriaBRNG = videoBitDepth.get(fullCriteria["BRNG"]) + criteriaClipping = videoBitDepth.get(fullCriteria["clipping"]) + selectColumns = "" + fullCriteria + "," + "Frame Time" + "" + BRNGErrors = setAndRunBRNG(criteriaBRNG, fullCriteria, selectColumns, videodata) + clippingErrors = setAndRunClipping( + criteriaClipping, fullCriteria, selectColumns, videodata + ) + + if BRNGErrors.isEmpty and clippingErrors.isEmpty: + pass + elif BRNGErrors.isEmpty or clippingErrors.isEmpty: + if BRNGErrors.isEmpty: + videoYUVErrors = clippingErrors + else: + videoYUVErrors = BRNGErrors + else: + videoYUVErrors = [clippingErrors, BRNGErrors] + return videoYUVErrors + + +def setAndRunClipping(criteria, criteriaClipping, selectColumns, videodata): + criteriaEquation = "" + criteria + "==" + criteriaClipping + "" + clippingErrors = {} + subDF = videodata[[selectColumns]] + + clippingErrors = subDF.query(criteriaEquation) + if subDF.empty: + pass + else: + if criteria.contains("low"): + errortype = "Low Clipping" + elif criteria.contains("high"): + errortype = "High Clipping" + clippingErrors.assign(errortype) + + return clippingErrors + + +def setAndRunBRNG(criteria, criteriaBRNG, selectColumns, videodata): + if criteria.contains("low"): + firstOp = "=<" + clipVal = 0 + elif criteria.contains("high"): + firstOp = ">=" + clipVal = 1023 + criteriaEquation = ( + "" + criteria + firstOp + criteriaBRNG + "&" + criteria + "!=" + clipVal + "" + ) + BRNGErrors = {} + subDF = videodata[[selectColumns]] + + BRNGErrors = subDF.query(criteriaEquation) + if BRNGErrors.isEmpty: + pass + else: + if criteria.contains("low"): + errortype = "Low BRNG" + elif criteria.contains("high"): + errortype = "High BRNG" + BRNGErrors.assign(errortype) + return BRNGErrors + + +def check(): + videodata = "baddata.csv" + criteria = "Y" + videoBitDepth = videovalues10Bit + fullCriteria = runLOW(criteria) + checkLOWHIGH(videodata, videoBitDepth, fullCriteria) + fullCriteria = runHIGH(criteria) + checkLOWHIGH(videodata, videoBitDepth, fullCriteria) + + +check() diff --git a/nulrdcscripts/staging/vqc/docs/continue.py b/nulrdcscripts/staging/vqc/docs/continue.py new file mode 100644 index 0000000..05481c3 --- /dev/null +++ b/nulrdcscripts/staging/vqc/docs/continue.py @@ -0,0 +1,59 @@ +import pandas as pd +import xml.etree.ElementTree as etree +import cleaners + +audiodata = {} +videodata = {} +framenumberA = 0 +framenumberV = 0 + + +file = input("file") +data = "data.json" +tree = etree.parse(file) +root = tree.getroot() + + +for event, elem in etree.iterparse(file, events=["start", "end"]): + if event == "start": + if elem.tag == "frame": + if elem.get("media_type") == "audio": + framenumberA = framenumberA + 1 + frametime = elem.get("pkt_pts_time") + audiodata[framenumberA] = {} + for tag in elem.iter("tag"): + criteria = tag.attrib["key"] + criteria = cleaners.criteriacleaner(criteria) + value = tag.attrib["value"] + audiodata[framenumberA]["Frame Time"] = float(frametime) + audiodata[framenumberA][criteria] = value + else: + pass + else: + pass + elif event == "end": + elem.clear() + + +for event, elem in etree.iterparse(file, events=["end"]): + if event == "end": + if elem.tag == "frame": + if elem.get("media_type") == "video": + framenumberV = framenumberV + 1 + frametime = elem.get("pkt_pts_time") + videodata[framenumberV] = {} + for tag in elem.iter("tag"): + criteria = tag.attrib["key"] + criteria = cleaners.criteriacleaner(criteria) + value = tag.attrib["value"] + videodata[framenumberV]["Frame Time"] = float(frametime) + videodata[framenumberV][criteria] = float(value) + elem.clear() + +dfAudio = pd.DataFrame.from_dict(audiodata) +dfAudio = dfAudio.transpose() +dfAudio.to_csv("audiodata.csv", sep=",") + +dfVideo = pd.DataFrame.from_dict(videodata) +dfVideo = dfVideo.transpose() +dfVideo.to_csv("videodatashort.csv", sep=",") diff --git a/nulrdcscripts/staging/vqc/docs/summarizationStats.md b/nulrdcscripts/staging/vqc/docs/summarizationStats.md new file mode 100644 index 0000000..db4854b --- /dev/null +++ b/nulrdcscripts/staging/vqc/docs/summarizationStats.md @@ -0,0 +1,36 @@ +## Standards from QC Tools that have been altered for this script + +|Criteria|Original Value| +|:---:|:---:| +|TOUTc|<10 frames| +|SATb|<1000 frames| +|SATi|<1000 frames| +|BRNGc|<1000 frames| +|MSEfY|<10 frames| + + +## Knowns (rounded frames per second) + +30 frames/sec
+3,600 sec/hr
+108,000 frames/hr + +### Calculations for TOUTc and MSEfY +Equation: 10/((3600*timeHRs) \* 30) (This makes no sense as the values are E-5) + +### Calculations for SATb, SATi, BRNGc +Equation: 1000/((3600*timeHRs) \* 30) + +#### If we can assume that the 1000 benchmark value came from a video in the range of 1-2 hrs + +|Time|Percent Error Allowed Exact| Percent Error Allowed Rounded| +|:---:|:---:|:---:| +1 hr|0.92592593%|0.93% +1.25 hr|0.74074074%|0.74% +1.5 hr|0.61728395%|0.62% +1.75 hr| 0.52910053%|0.53% +2 hr|0.4629629%|0.46% +|| +AVG| 0.65520282%|0.66% + +Theoretically 0.66% of the videos frames are allowed to be greater \ No newline at end of file diff --git a/nulrdcscripts/staging/vqc/parseandclean/__init__.py b/nulrdcscripts/staging/vqc/parseandclean/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/nulrdcscripts/staging/vqc/parseandclean/schema.xsd b/nulrdcscripts/staging/vqc/parseandclean/schema.xsd new file mode 100644 index 0000000..a29715b --- /dev/null +++ b/nulrdcscripts/staging/vqc/parseandclean/schema.xsd @@ -0,0 +1,409 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/nulrdcscripts/staging/vqc/parseandclean/validate.py b/nulrdcscripts/staging/vqc/parseandclean/validate.py new file mode 100644 index 0000000..0338a57 --- /dev/null +++ b/nulrdcscripts/staging/vqc/parseandclean/validate.py @@ -0,0 +1,7 @@ +import xmlschema +from pprint import pprint + +file = "example.xml" +schema = xmlschema.XMLSchema("schema.xsd") + +schema.validate(file) diff --git a/nulrdcscripts/staging/vqc/setupsteps/__init__.py b/nulrdcscripts/staging/vqc/setupsteps/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/nulrdcscripts/staging/vqc/testbuilds/example.xml b/nulrdcscripts/staging/vqc/testbuilds/example.xml new file mode 100644 index 0000000..a52173b --- /dev/null +++ b/nulrdcscripts/staging/vqc/testbuilds/example.xml @@ -0,0 +1,108983 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 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b/nulrdcscripts/staging/vqc/videoanalyses/errortiers.py new file mode 100644 index 0000000..99a60b0 --- /dev/null +++ b/nulrdcscripts/staging/vqc/videoanalyses/errortiers.py @@ -0,0 +1,56 @@ +import json +tier1errors = ["SAT", "VREP", "BRNG"] +tier2errors = [""] +def errorsvideo (summaryvideoerrors): + if summaryvideoerrors.contains(tier1errors): + pass + + + + + + + + + +failstier1 = {} +failstier2 = {} +failstier3 = {} +videoreportbycriteria = [failstier1, failstier2, failstier3] +# A fail for tier one is a critical failure and should be top priority for assessment + +def tier1error (criteria, description, value): + failstier1 = {criteria[value, description]} + return failstier1 + +# A fail for tier two is a moderate failure, requires attention but is not as severe as a tier one + +def tier2error(criteria, description, value): + failstier2 = {criteria[value, description]} + return failstier2 + +# A fail for tier three is a mild error that is of the lowest priority for assessment, but should still be assessed + +def tier3error (criteria, description, value): + failstier3 = {criteria[value, description]} + return failstier3 + + +def assignVideoSummaryTiers (failstier1,failstier2,failstier3): + if failstier1: + videosummaryreport = "Error Rank: Critical - High priority for assessment" + elif failstier2: + videosummaryreport = "Error Rank: Moderate - Mid-level priority for assessment" + elif failstier3: + videosummaryreport = "Error Rank: Mild - Lowest priority for assessment" + else: + videosummaryreport = "Cleared Automated QC" + return videosummaryreport + + + + + + + +# These results will now be pooled into a JSON file that will list the ranking of videos criterias as well as an overall score. \ No newline at end of file diff --git a/nulrdcscripts/staging/vqc/videoanalyses/fbyfTOUTVREP.py b/nulrdcscripts/staging/vqc/videoanalyses/fbyfTOUTVREP.py new file mode 100644 index 0000000..3e10b23 --- /dev/null +++ b/nulrdcscripts/staging/vqc/videoanalyses/fbyfTOUTVREP.py @@ -0,0 +1,75 @@ +import pandas as pd + +levels = ["ideal", "max"] +criteria = ["tout", "vrep"] +level = 0 +item = 0 + +videodata = "YHighData.csv" + + +def runCriteria(videoBitDepth, videodata): + while item <= len(criteria): + criteriaToCheck = criteria[item] + errors = runLevels(videoBitDepth, videodata, criteriaToCheck) + item = item + 1 + print(errors) + + +def runLevels(videoBitDepth, videodata, criteriaToCheck): + while level <= len(levels): + levelToCheck = levels[level] + errors = setUpCheckErrors( + levelToCheck, criteriaToCheck, videoBitDepth, videodata + ) + level = level + 1 + return errors + + +def setUpCheckErrors(levelToCheck, criteriaToCheck, videoBitDepth, videodata): + criteriaValue = videoBitDepth.at[criteriaToCheck, levelToCheck] + criteria = criteriaToCheck + levelToCheck + data = setColumn(videodata, criteriaToCheck) + equationSign = setEquationSign(criteriaValue) + equation = setEquation(equationSign, criteriaToCheck, criteriaValue) + errorType = setErrorType(criteriaToCheck) + errors = checkErrors(equation, data, errorType) + return errors + + +def checkErrors(Equation, data, errorType): + errors = data.query(Equation) + errors = assignETColumn(data, errorType) + print(errors) + return errors + + +def setEquation(equationSign, criteriaValue, criteria): + equation = "" + criteria + equationSign + criteriaValue + "" + return equation + + +def setEquationSign(criteriaValue): + # Ideal Value + if criteriaValue == 0: + equationSign = "==" + # Max Value + elif criteriaValue > 0: + equationSign = ">=" + return equationSign + + +def setColumn(criteriaToCheck, videodata): + viewColumns = "" + criteriaToCheck + "Frame Time" + "Frame" + "" + data = videodata(viewColumns) + return data + + +def setErrorType(criteriaToCheck): + errorType = criteriaToCheck + return errorType + + +def assignETColumn(data, errorType): + data = data.assign(ErrorType=errorType) + return data diff --git a/nulrdcscripts/staging/vqc/videoanalyses/fbyfYUV.py b/nulrdcscripts/staging/vqc/videoanalyses/fbyfYUV.py new file mode 100644 index 0000000..0045c62 --- /dev/null +++ b/nulrdcscripts/staging/vqc/videoanalyses/fbyfYUV.py @@ -0,0 +1,107 @@ +import pandas as pd + + +def checkerrors(videodata, videoBitDepth): + prefix = ["y", "u", "v"] + value = 0 + videoerrors = pd.DataFrame() + while value < len(prefix): + prefix = prefix[value] + if prefix == "y": + videoerrors = check(videodata, videoBitDepth, videoerrors, prefix) + elif prefix == "u": + videoerrors = check(videodata, videoBitDepth, videoerrors, prefix) + if prefix == "v": + videoerrors = check(videodata, videoBitDepth, videoerrors, prefix) + value = value + 1 + return videoerrors + + +def check(prefix, videodata, videoBitDepth, videoerrors): + fullCriteria = runLOW(prefix) + checkLOWHIGH(videodata, videoBitDepth, fullCriteria, videoerrors) + fullCriteria = runHIGH(prefix) + checkLOWHIGH(videodata, videoBitDepth, fullCriteria, videoerrors) + + +def runLOW(prefix): + criteria = prefix + "low" + return criteria + + +def runHIGH(prefix): + criteria = prefix + "high" + return criteria + + +def checkLOWHIGH(videodata, videoBitDepth, fullCriteria, videoerrors): + valuecriteria = str(fullCriteria) + criteriaBRNG = videoBitDepth.loc[fullCriteria, "brngout"] + criteriaClipping = videoBitDepth.loc[fullCriteria, "clipping"] + selectColumns = "" + fullCriteria + "," + "Frame Time" + "" + BRNGErrors = setAndRunBRNG(criteriaBRNG, fullCriteria, selectColumns, videodata) + clippingErrors = setAndRunClipping( + criteriaClipping, fullCriteria, selectColumns, videodata + ) + + if BRNGErrors.isEmpty and clippingErrors.isEmpty: + pass + elif BRNGErrors.isEmpty or clippingErrors.isEmpty: + if BRNGErrors.isEmpty: + videoerrors = clippingErrors + else: + videoerrors = BRNGErrors + else: + videoerrors = [clippingErrors, BRNGErrors] + return videoerrors + + +def setAndRunClipping(fullCriteria, criteriaClipping, selectColumns, videodata): + criteriaEquation = "" + fullCriteria + "==" + criteriaClipping + "" + clippingErrors = {} + subDF = videodata[[selectColumns]] + + clippingErrors = subDF.query(criteriaEquation) + if subDF.empty: + pass + else: + if fullCriteria.contains("low"): + errortype = "Low Clipping" + elif fullCriteria.contains("high"): + errortype = "High Clipping" + clippingErrors.assign(errortype) + + return clippingErrors + + +def setAndRunBRNG(fullCriteria, criteriaBRNG, selectColumns, videodata): + if fullCriteria.contains("low"): + firstOp = "=<" + clipVal = 0 + elif fullCriteria.contains("high"): + firstOp = ">=" + clipVal = 1023 + criteriaEquation = ( + "" + + fullCriteria + + firstOp + + criteriaBRNG + + "&" + + fullCriteria + + "!=" + + clipVal + + "" + ) + BRNGErrors = {} + subDF = videodata[[selectColumns]] + + BRNGErrors = subDF.query(criteriaEquation) + if BRNGErrors.isEmpty: + pass + else: + if fullCriteria.contains("low"): + errortype = "Low BRNG" + elif fullCriteria.contains("high"): + errortype = "High BRNG" + BRNGErrors.assign(errortype) + return BRNGErrors diff --git a/nulrdcscripts/staging/vqc/videoanalyses/overallstatistics.py b/nulrdcscripts/staging/vqc/videoanalyses/overallstatistics.py new file mode 100644 index 0000000..3f4f90d --- /dev/null +++ b/nulrdcscripts/staging/vqc/videoanalyses/overallstatistics.py @@ -0,0 +1,35 @@ +import pandas as pd + + +# Gathers general video data for summary report +def videodatastatistics(videodata): + videostats = videodata.describe() + return videostats + +# Outputs summary video stats as a dictionary - which will be used for comparison analysis +def videostatstodict (videostats): + summarydatavideodict = videostats.to_dict() + return summarydatavideodict + +#Outputs summary video stats as a csv +def videostatstocsv (videostats): + summarydatavideocsv = videostats.to_csv("videosummarystats.csv", index=True) + return summarydatavideocsv + +#Gathers general audio data for summary report +def audiodatastatistics(audiodata): + audiodata = audiodata.describe() + return audiodata + +#Output summary audio stats as dictionary - which will be used for comparison analysis +def audiostatstodict (audiostats): + summarydataaudiodict = audiostats.to_dict() + return summarydataaudiodict + +#Output summary audio stats as a csv +def audiostatstocsv (audiostats): + summarydataaudiocsv = audiostats.to_csv("audiosummarystats.csv", index = True) + return summarydataaudiocsv + + + diff --git a/nulrdcscripts/staging/vqc/videoanalyses/specificerrorchecks.py b/nulrdcscripts/staging/vqc/videoanalyses/specificerrorchecks.py new file mode 100644 index 0000000..b31a2ff --- /dev/null +++ b/nulrdcscripts/staging/vqc/videoanalyses/specificerrorchecks.py @@ -0,0 +1,53 @@ +# Checks for TBC errors + +def checkVideoGainError (): + pass + # will use the Y AVG (range?) and look for dramatic peaks + +def checkChrominanceNoiseBW (): + pass + # will use the U and V readings to make sure that this is at zero as this is solely for BW video + +def checkColorDropout (): + pass + # will use the U and V readings to make sure that there is activity. Solely for color video + +def checkChrominanceNoiseColor (): + pass + # will look for abrupt spikes in Min and Max values for UV + +def checkLuminanceNoise (): + pass + # will use the BRNG and TOUT values & Y High and Low. + +# Checks for mechanical errors + +def checkTrackingError (): + pass + # will use TOUT and VREP (VREP rules out color errors) + +def checkVideoHeadClog (): + pass + # will use PSNRf and MSEf along with the YUV difference. Lower PSNRf, higher MSEf, and large difference and prolonged spikes in YUV + +# Checks for tape damage + +def checkDropouts (): + pass + # VREP and TOUT + +def standardChecks (): + checkVideoGainError() + checkLuminanceNoise() + checkTrackingError() + checkVideoHeadClog() + checkDropouts() + +def checkBWVideo(): + checkChrominanceNoiseBW() + standardChecks() + +def checkColorVideo (): + checkChrominanceNoiseColor() + checkColorDropout() + standardChecks() \ No newline at end of file diff --git a/nulrdcscripts/staging/vqc/videoanalyses/videoanalysis.py b/nulrdcscripts/staging/vqc/videoanalyses/videoanalysis.py new file mode 100644 index 0000000..5154e15 --- /dev/null +++ b/nulrdcscripts/staging/vqc/videoanalyses/videoanalysis.py @@ -0,0 +1,65 @@ +import pandas as pd +from argparser import args + +videoerrors = {} + + +def checkAllVideo(videostats, videoBitDepth): + MINsCheck(videostats, videoBitDepth) + LOWsCheck(videostats, videoBitDepth) + AVGsCheck(videostats, videoBitDepth) + HIGHsCheck(videostats, videoBitDepth) + MAXsCheck(videostats, videoBitDepth) + + def check(criteria, videostats, videoBitDepth): + setcriteria = videoBitDepth.get[criteria] + lowEnd = videostats.at[3, criteria] + highEnd = videostats.at[8, criteria] + if highEnd < setcriteria > lowEnd: + values = [lowEnd, highEnd] + videoerrors[criteria] = values + else: + pass + return videoerrors + + def MINsCheck(): + criteriaprefix = ["Y", "U", "V", "SAT"] + i = 0 + while i < len(criteriaprefix): + criteria = criteriaprefix[i] + "MIN" + check(criteria) + i = i + 1 + + def MAXsCheck(): + criteriaprefix = ["Y", "U", "V", "SAT", "BRNG", "VREP", "TOUT"] + i = 0 + while i < len(criteriaprefix): + criteria = criteriaprefix[i] + "MAX" + check(criteria) + i = i + 1 + + def AVGsCheck(): + criteriaprefix = ["Y", "U", "V", "SAT"] + i = 0 + while i < len(criteriaprefix): + criteria = criteriaprefix[i] + "AVG" + check(criteria) + i = i + 1 + + def LOWsCheck(): + criteriaprefix = ["Y", "U", "V", "SAT"] + i = 0 + while i < len(criteriaprefix): + criteria = criteriaprefix[i] + "LOW" + check(criteria) + i = i + 1 + + def HIGHsCheck(): + criteriaprefix = ["Y", "U", "V", "SAT"] + i = 0 + while i < len(criteriaprefix): + criteria = criteriaprefix[i] + "HIGH" + check(criteria) + i = i + 1 + + return videoerrors diff --git a/nulrdcscripts/tools/ffprobedata/try.py b/nulrdcscripts/tools/ffprobedata/try.py new file mode 100644 index 0000000..630c8df --- /dev/null +++ b/nulrdcscripts/tools/ffprobedata/try.py @@ -0,0 +1,26 @@ +from params import args +import subprocess +import os + + +def swapSlashes(item): + fixed_path = item.replace("\\", "/") + fixed_path = fixed_path.replace(":", "\\\\:") + return fixed_path + + +norm_input = os.path.normpath(args.input_path) +fixed_input = swapSlashes(norm_input) +filepath = norm_input.replace(".mp4", "_framebyframe.xml") +command = [ + args.ffprobe_path, + "-f", + "lavfi", + "movie=" + fixed_input + ",signalstats='stat=tout+vrep+brng'", + "-show_frames", + "-of", + "xml", +] +with open(filepath, "w") as f: + subprocess.run(command, stdout=f) + f.close() diff --git a/nulrdcscripts/vproc/checks.py b/nulrdcscripts/vproc/checks.py index e1c1b00..b3e373d 100644 --- a/nulrdcscripts/vproc/checks.py +++ b/nulrdcscripts/vproc/checks.py @@ -2,6 +2,7 @@ def inventory_check(item_csvDict): + """Checks if item is in the inventory csv provided""" if item_csvDict is None: print("unable to locate file in csv data!") inventoryCheck = "FAIL" diff --git a/nulrdcscripts/vproc/docs/FFMPEGArgumentsDecoded.md b/nulrdcscripts/vproc/docs/FFMPEGArgumentsDecoded.md new file mode 100644 index 0000000..e69de29 diff --git a/nulrdcscripts/vqc/.gitignore b/nulrdcscripts/vqc/.gitignore new file mode 100644 index 0000000..b5f5686 --- /dev/null +++ b/nulrdcscripts/vqc/.gitignore @@ -0,0 +1,12 @@ +# Prevents CSVs from being uploaded to GitHub and wasting space +*.csv +*.conda +*.vscode + + +# Exceptions +!Video8BitValues.csv +!Video10BitValues.csv +!testdata.csv +!data.csv +!ExampleVideoDataCSV.csv \ No newline at end of file diff --git a/nulrdcscripts/vqc/ExampleVideoDataCSV.csv b/nulrdcscripts/vqc/ExampleVideoDataCSV.csv new file mode 100644 index 0000000..9d5f620 --- /dev/null +++ b/nulrdcscripts/vqc/ExampleVideoDataCSV.csv @@ -0,0 +1,596 @@ +Frame,Frame Time,ymin,ylow,yavg,yhigh,ymax,umin,ulow,uavg,uhigh,umax,vmin,vlow,vavg,vhigh,vmax,vdif,udif,ydif,satmin,satlow,satavg,sathigh,satmax,huemed,hueavg,tout,vrep,brng,vbitdepth,ubitdepth,ybitdepth,psnr mse v,psnr mse u,psnr mse y,psnr psnr v,psnr psnr u,psnr psnr y,psnr mse avg,psnr psnr avg +1,0,4,130,308.942,607,927,428,496,504.94,512,538,477,498,507.424,513,552,0,0,0,0,2,9.86364,21,89,71,88.089,0.024217,0,0.015409,10,10,10,19.83686,42.1919,2513.076,47.22279,43.94522,26.19546,1272.045,29.15249 +2,0.033367,4,131,309.752,608,921,428,496,504.98,512,537,476,499,507.769,514,558,3.41559,4.96636,12.1676,0,2,9.68,21,88,71,90.6784,0.022391,0,0.015378,10,10,10,19.50628,43.33405,3734.214,47.29577,43.82922,24.47552,1882.817,27.44943 +3,0.066733,4,132,310.883,610,928,424,496,504.836,512,551,477,498,507.624,514,540,3.37086,4.95113,13.2429,0,2,9.85045,21,91,71,88.3575,0.022031,0,0.015366,10,10,10,19.36941,44.97586,3934.834,47.32635,43.66772,24.24825,1983.503,27.22318 +4,0.1001,4,132,310.724,611,935,423,496,504.78,512,538,474,498,507.526,514,544,3.34909,4.90158,15.3419,0,2,9.95884,22,93,71,88.6069,0.020968,0,0.015412,10,10,10,19.29672,43.26735,3825.373,47.34268,43.83591,24.37078,1928.328,27.34571 +5,0.133467,4,131,310.531,610,930,428,496,504.841,512,586,476,498,507.5,514,569,3.40554,4.98656,12.4051,0,2,9.96192,22,93,71,88.7756,0.022785,0,0.015478,10,10,10,19.14269,42.26197,2653.343,47.37748,43.93802,25.95958,1342.023,28.91991 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+594,19.78645,4,129,297.806,582,930,428,496,504.83,512,539,448,502,508.926,514,542,3.1449,4.74258,12.0842,0,2,9.05159,19,89,75,90.9084,0.023934,0,0.015852,10,10,10,17.08242,45.54693,3223.639,47.87202,43.61292,25.11405,1627.477,28.08237 +595,19.81982,4,129,297.142,580,931,423,496,504.586,512,533,478,502,508.917,514,540,3.12984,4.74693,12.8627,0,2,9.2205,19,93,75,89.5333,0.024457,0,0.015872,10,10,10,16.81424,44.50341,2544.489,47.94074,43.71358,26.14151,1287.574,29.09979 \ No newline at end of file diff --git a/nulrdcscripts/vqc/LICENSE b/nulrdcscripts/vqc/LICENSE new file mode 100644 index 0000000..9008668 --- /dev/null +++ b/nulrdcscripts/vqc/LICENSE @@ -0,0 +1,23 @@ +MIT License + +Copyright (c) 2023 Northwestern University Libraries + +Created by Sophia Francis + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/nulrdcscripts/vqc/QCScript.py b/nulrdcscripts/vqc/QCScript.py new file mode 100644 index 0000000..101fe77 --- /dev/null +++ b/nulrdcscripts/vqc/QCScript.py @@ -0,0 +1,55 @@ +import os +import setup +from argparser import args +from nulrdcscripts.vqc import dataparsing +from nulrdcscripts.vqc import overallStatistics +from nulrdcscripts.vqc import framebyframestatistics +import progressbar + +inputPath = os.path.normpath(args.input_path) +bitDepth = args.videobitdepth +outputPath = args.output_path + +print("***Starting Setup***") +with progressbar.ProgressBar(max_value=100) as setupBar: + for i in range(100): + standardDF = setup.setVideoBitDepth(bitDepth) + setupBar.update(i) + setup.inputCheck(inputPath) + setupBar.update(i) + outputLocation = setup.outputCheck(inputPath, outputPath) + setupBar.update(i) + inputFileType = setup.setInputFileType(inputPath) +print("***Setup Complete***") + +print("***Parsing File Video***") + +if inputFileType == "JSON": + with progressbar.ProgressBar(max_value=100) as parsingBar: + for i in range(100): + # audiodata = dataparsing.dataparsingandtabulatingaudioJSON(inputPath) + parsingBar.update(i) + videodata = dataparsing.dataparsingandtabulatingvideoJSON(inputPath) +else: + with progressbar.ProgressBar(max_value=100) as parsingBar: + for i in range(100): + # audiodata = dataparsing.dataparsingandtabulatingaudioXML(inputPath) + parsingBar.update(i) + videodata = dataparsing.dataparsingandtabulatingvideoXML(inputPath) +print("***Parsing complete***") + +print("***Generating Full Video Descriptive Statistics***") +sumdatavideo = dataparsing.videodatastatistics(videodata) +# sumdataaudio = dataparsing.audiodatastatistics(audiodata) +sumdatavideocsv = dataparsing.videostatsdftocsv(sumdatavideo) +# sumdataaudiocsv = dataparsing.audiostatstocsv(sumdataaudio) +print("***Generated Full Video Descriptive Statistics***") + +print("***Analysing Full Video Descriptive Statistics***") +overallStatistics.runOverallVideo(standardDF, sumdatavideo) +print("***Generated report for full video descriptive statistics***") + +print("***Analyzing video for frame by frame statistics***") +frameerrors = framebyframestatistics.runfbyfanalysis(standardDF, videodata) +framebyframestatistics.dictodftojson(frameerrors) +print("***Analyzed frame by frame video statisitics***") diff --git a/nulrdcscripts/vqc/README.md b/nulrdcscripts/vqc/README.md new file mode 100644 index 0000000..8b82808 --- /dev/null +++ b/nulrdcscripts/vqc/README.md @@ -0,0 +1,118 @@ +Version Date: 10/30/2023 + +Document Owner: Sophia Francis
+ +Software Used: Terminal or Command Prompt, VSCode (optional), QCTools (requires the output files not the software itself), Excel (or other CSV reader if accessing CSV file) + +Packages required (also see .toml file): pandas, lxml, beautifulsoup4, tabulate, json, os, + +Description:
+This document provides information about running the QC Script and what information is required in order to do so. + +## Important information: + +If you are planning on running this in batch form (one folder with multiple xml files), make sure that if there are a mix of black and white videos and color videos, they are in separate folders and run separately to ensure the proper tests get run. + +### Changing Value ranges: +If you want to edit the value ranges that are used, then you can edit the CSVs Video8BitValues and Video10BitValues. However, caution must be used as these are used in equations throughout the script. I _do not_ recommend this. + +### _Regarding the YAvg reporting_: + +There are no ranges that are supplied for YAvg in the QCTools documentation. I have tried my best to modify the values that are from UAvg and Vavg, if there is a more correct range, please contact me (Sophia) at repository@northwestern.edu. + +### _Regarding Summarization Stats from QCTools:_ + +Due to the nature of the summarization stats from the QCTools worksheet, these have been adapted so that they are less likely to incur skewing due to framecount (this concept has been communicated a developer of QCTools.) That being said, in order to see the documentation about how these numbers came to be see [this](docs/summarizationStats.md) document. If you have any better values for these statistics, please contact me (Sophia) at repository@northwestern.edu + +## Running with Parser (still in development - not functional): + +### 1. Drag and drop the run.py file into the terminal +### 2. Locate your file or file folder path: + +For this example I will be using: +- example.xml as the file version +- /files/example.xml as the filepath version + +### 3. Type --input or -i (they do the same thing) followed by your file or folder path + +``` +run.py --input example.xml +``` +``` +run.py -i /files/example.xml +``` +### 4. Depending on whether or not you are running a black and white video or a color video, different processes should be run. To select: +- Use ```--blackwhite``` or ```-bw``` for black and white video +- Use ```--color``` or ```-c``` for color video + +Adding to the first example in step 3, these options would look like this: + +#### Black and white video + +``` +run.py --input example.xml --blackandwhite +``` +``` +run.py --input example.xml -bw +``` + +#### Color video + +``` +run.py --input example.xml --color +``` +``` +run.py --input example.xml -c +``` + +### 5. Depending on what bitdepth you are utilizing, different values need to be used. To select: + +- Use ```--10bit``` or ```-10``` for 10 Bit video + +- Use ```--8bit``` or ```-8``` for 8 Bit Video + +Adding to the example above, for a color video this would look like: + +#### 10 Bit Video + +``` +run.py --input example.xml --color --10bit +``` +``` +run.py --input example.xml --color -10 +``` + +#### 8 Bit Video + +``` +run.py --input example.xml --color --8bit +``` +``` +run.py --input example.xml --color -8 +``` + + + +## Many thanks to the contributers to this project: + +Alec Bertoy + +Dan Zellner + +Morgan Morel + +Brendan Coates + +Ben Turkus + +Dave Rice + + + +## Some of the reference material utilized: + +_Python for Data Analytics - Wes McKinney_
+_Python Data Analytics: With Pandas, NumPy, and Matplotlib_ - Fabio Nelli
+_Practical Python Data Wrangling and Data Quality_ - Susan E. McGregor
+_Data Wrangling with Python_ - Jacqueline Kazil, Katharine Jarmul
+_How to convert an XML file to python pandas dataframe - reading xml with python_ - Paris Nakita Kejser - https://www.youtube.com/watch?v=WWgiRkvl1Ws&ab_channel=ParisNakitaKejser \ No newline at end of file diff --git a/nulrdcscripts/vqc/Video10BitValues.csv b/nulrdcscripts/vqc/Video10BitValues.csv new file mode 100644 index 0000000..f3aa868 --- /dev/null +++ b/nulrdcscripts/vqc/Video10BitValues.csv @@ -0,0 +1,17 @@ +criteria,brngout,clipping,avglow,avghigh,brnglimit,clippinglimit,illegal,ideal,max +ylow,64,0,,,,,,, +yhigh,940,1023,,,,,,, +yavg,,,321,682,,,,, +ulow,64,0,,,,,,, +uhigh,960,1023,,,,,,, +uavg,,,341,682,,,,, +vlow,64,0,,,,,,, +vhigh,960,1023,,,,,,, +vavg,,,341,682,,,,, +tout,,,,,,,,0,0.009 +vrep,,,,,,,,0,0.03 +brng,,,,,,,,0,1 +sat,,,,,354.8,472.8,724.08,, +msef,,,,,,,,0, +psnrideal,,,,,30,,50,, +psnrmax,,,,,0,,60,, diff --git a/nulrdcscripts/vqc/Video8BitValues.csv b/nulrdcscripts/vqc/Video8BitValues.csv new file mode 100644 index 0000000..00af05e --- /dev/null +++ b/nulrdcscripts/vqc/Video8BitValues.csv @@ -0,0 +1,17 @@ +criteria,brngout,clipping,avglow,avghigh,brnglimit,clippinglimit,illegal,ideal,max +ylow,16,0,,,,,,, +yhigh,235,255,,,,,,, +yavg,,,80,170,,,,, +ulow,16,0,,,,,,, +uhigh,240,255,,,,,,, +uavg,,,85,170,,,,, +vlow,16,0,,,,,,, +vhigh,240,255,,,,,,, +vavg,,,85,170,,,,, +tout,,,,,,,,0,0.009 +vrep,,,,,,,,0,0.03 +brng,,,,,,,,0,1 +sat,,,,,88.7,118.2,181.02,, +msef,,,,,,,,0, +psnrideal,,,,,,,,30,50 +psnrmax,,,,,,,,0,60 diff --git a/nulrdcscripts/vqc/__init__.py b/nulrdcscripts/vqc/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/nulrdcscripts/vqc/argparser.py b/nulrdcscripts/vqc/argparser.py new file mode 100644 index 0000000..548b7f4 --- /dev/null +++ b/nulrdcscripts/vqc/argparser.py @@ -0,0 +1,51 @@ +#!/usr/bin/env python3 +import argparse + +parser = argparse.ArgumentParser( + description="Allows input of files for video analysis statistics for automated quality control" +) + +parser.add_argument( + "--input", + "-i", + action="store", + dest="input_path", + required=True, + type=str, + help="Enter the full path to input file folder", +) + +parser.add_argument( + "--output", + "-o", + action="store", + dest="output_path", + default="", + type=str, + help="Enter the full path to where you want your output files", +) + +# This may actually be able to come directly from video +parser.add_argument( + "--videobitdepth", + "-vbd", + choices=["10", "10bit", "10Bit", "8", "8bit", "8Bit"], + action="store", + default="10bit", + dest="videobitdepth", + required=True, + type=str, + help="Use to specify what bit depth your video is", +) + +# Need to add one for B/W or Color video option + +parser.add_argument( + "--videotype", + "-vt", + choices=["bw", "blackandwhite", "co", "color"], + action="store", + dest="videotype", + help="Tells script what video type to run: black and white or color", +) +args = parser.parse_args() diff --git a/nulrdcscripts/vqc/cleaners.py b/nulrdcscripts/vqc/cleaners.py new file mode 100644 index 0000000..ca28c45 --- /dev/null +++ b/nulrdcscripts/vqc/cleaners.py @@ -0,0 +1,44 @@ +def criteriacleaner(criteria): + criteriaclean1 = criteria.replace("lavfi.astats", "") + criteriaclean2 = criteriaclean1.replace("lavfi.", "") + criteriaclean3 = criteriaclean2.replace("signalstats.", "") + criteriaclean4 = criteriaclean3.replace(".", " ") + cleanedcriteria = criteriaclean4.replace("_", " ") + cleanCriteria = cleanedcriteria.lower() + return cleanCriteria + + +# Makes the criteria more legible so that it can be strung together later for a easy interpretation without relying on acronyms + + +def cleanCriteria(criteria): + for i in criteria: + if criteria.contains("MIN"): + criteria = criteria.replace("MIN", "minimum") + elif criteria.contains("LOW"): + criteria = criteria.lower() + elif criteria.contains("AVG"): + criteria = criteria.replace("AVG", "average") + elif criteria.contains("HIGH"): + criteria = criteria.lower() + elif criteria.contains("MAX"): + criteria = criteria("maximum") + + if criteria.contains("Y"): + criteria = criteria.replace("Y", "Y ") + # U has to use the startswith method instead as otherwise it will replace the U in TOUT which is not wanted + elif criteria.startswith("U"): + criteria = criteria.replace("U", "U ") + # V has to use the startswith method instead as otherwise it will replace the V in VREP which is not wanted + elif criteria.startswith("V"): + criteria = criteria.replace("V", "V ") + elif criteria.contains("BRNG"): + criteria = criteria.replace("BRNG", "Broadcasting Range ") + elif criteria.contains("TOUT"): + criteria = criteria.replace("TOUT", "Temporal Outliers ") + elif criteria.contains("SAT"): + criteria = criteria.replace("SAT", "Saturation") + elif criteria.conains("VREP"): + criteria = criteria.replace("VREP", "Vertical Line Repetitions") + + return criteria diff --git a/nulrdcscripts/vqc/dataparsing.py b/nulrdcscripts/vqc/dataparsing.py new file mode 100644 index 0000000..734ae32 --- /dev/null +++ b/nulrdcscripts/vqc/dataparsing.py @@ -0,0 +1,87 @@ +import pandas as pd +from nulrdcscripts.vqc import cleaners +import xml.etree.ElementTree as etree +import os + + +def dataparsingandtabulatingaudioXML(inputPath): + """Cleans and parses the audio data from XML for analysis. Returns dataframe.""" + audiodata = {} + framenumberA = 0 + for event, elem in etree.iterparse(inputPath, events=["end"]): + if event == "end": + if elem.tag == "frame": + if elem.get("media_type") == "audio": + framenumberA = framenumberA + 1 + frametime = elem.get("pkt_pts_time") + audiodata[framenumberA] = {} + for tag in elem.iter("tag"): + criteria = tag.attrib["key"] + criteria = cleaners.criteriacleaner(criteria) + value = tag.attrib["value"] + audiodata[framenumberA]["Frame Time"] = float(frametime) + audiodata[framenumberA][criteria] = value + elem.clear() + dfAudio = pd.DataFrame.from_dict(audiodata) + dfAudio = dfAudio.transpose() + dfAudio.to_csv("audiodata.csv", index=True) + return dfAudio + + +def dataparsingandtabulatingvideoXML(inputPath): + """Cleans and parses the video data from XML for analysis. Returns dataframe and generates csv.""" + videodata = {} + framenumberV = 0 + + for event, elem in etree.iterparse(inputPath, events=["end"]): + if event == "end": + if elem.tag == "frame": + if elem.get("media_type") == "video": + framenumberV = framenumberV + 1 + frametime = elem.get("pts_time") + videodata[framenumberV] = {} + for tag in elem.iter("tag"): + criteria = tag.attrib["key"] + criteria = cleaners.criteriacleaner(criteria) + value = tag.attrib["value"] + videodata[framenumberV]["Frame Time"] = float(frametime) + videodata[framenumberV][criteria] = float(value) + elem.clear() + dfVideo = pd.DataFrame.from_dict(videodata) + dfVideo = dfVideo.transpose() + videodataDF = dfVideo.to_csv("videodata.csv", index=True) + return dfVideo + + +def videodatastatistics(videodata): + """Generates descriptive video statistics for the entire video in a dataframe""" + videostatsDSDF = videodata.describe() + return videostatsDSDF + + +def audiodatastatistics(audiodata): + """Generates descriptive audio statistics for the entire video in a dataframe""" + audiodataDSDF = audiodata.describe() + return audiodataDSDF + + +def videostatsdftocsv(videoDSDF): + """Takes video descriptive statistics and puts them into a csv file""" + summarydatavideocsv = videoDSDF.to_csv("videosummarystats.csv", index=True) + return summarydatavideocsv + + +def audiostatsdftocsv(audioDSDF): + """Takes audio descriptive statistics and puts them into a csv file.""" + summarydataaudiocsv = audioDSDF.to_csv("audiosummarystats.csv", index=True) + return summarydataaudiocsv + + +def rawvideodatatocsv(videodata): + videodatacsv = videodata.to_csv("videodata.csv", index=True) + + +input_path = os.path.abspath( + "Z:\RDC\SCRATCH\sophiatestfiles\\test_badLevels\\test\\badlevels2\\p\\badlevels2_signalstats.xml" +) +dataparsingandtabulatingvideoXML(input_path) diff --git a/nulrdcscripts/vqc/file.py b/nulrdcscripts/vqc/file.py new file mode 100644 index 0000000..4ca1fba --- /dev/null +++ b/nulrdcscripts/vqc/file.py @@ -0,0 +1,30 @@ +import dataparsing + +inputpath = "Z:\\RDC\\SCRATCH\\sophiatestfiles\\test_badLevels\\test\\badlevels2\\a\\badlevels2_a_framebyframe.xml" + + +def runIndividualFile(inputpath): + # Parses the raw XML into individual readings by frame (determined by frametime) + videodata = dataparsing.dataparsingandtabulatingvideoXML(inputpath) + audiodata = dataparsing.dataparsingandtabulatingaudioXML(inputpath) + + # videodataCSV = dataparsing.videostatsdftocsv(videodata) + # Collects the video summary data - outputs CSV and Dictionary + videostats = dataparsing.rawvideodatatocsv(videodata) + + # videofeedtodict = dataparsing.videostatstodict(videostats) + + # Collects the audio summary data - outputs CSV and Dictionary + # audiostats = overallstatistics.audiodatastatistics(audiodata) + + # audiofeedtodict = overallstatistics.audiostatstodict(audiostats) + # audiofeedtocsv = overallstatistics.audiostatstocsv(audiostats) + + # Video analysis for summary report + # summaryvideoerrors = videoanalysis.checkAllVideo(videostats, videoBitDepth) + + # Assigns errors to tiers for verbose reporting + # errortiers.errorsvideo(summaryvideoerrors) + + +runIndividualFile(inputpath) diff --git a/nulrdcscripts/vqc/fix.py b/nulrdcscripts/vqc/fix.py new file mode 100644 index 0000000..0baaed7 --- /dev/null +++ b/nulrdcscripts/vqc/fix.py @@ -0,0 +1,142 @@ +import pandas as pd +from tabulate import tabulate +from nulrdcscripts.vqc import setup +from nulrdcscripts.vqc.multiuse import ( + setLevel, + setOperatorCL, + setOperatorIR, +) + +frameerrors = {} +videodata = "nulrdcscripts/vqc/testdata.csv" +standard = 8 + +standardDF = setup.setVideoBitDepth(standard) +csvDF = pd.read_csv(videodata) + + +def runyuvfbyfanalysis(standardDF, csvDF, fullCriteria, level, frame): + exVideoVal = csvDF.at[frame, fullCriteria] + exStandBRNG = standardDF.at[fullCriteria, "brngout"] + exStandClipping = standardDF.at[fullCriteria, "clipping"] + operatorIR = setOperatorIR(level) + equationIR = str(exVideoVal) + operatorIR + str(exStandBRNG) + tfIR = eval(equationIR) + if tfIR: + errors = {"Video Value": exVideoVal, "Pass/Fail": "Pass"} + else: + operatorCL = setOperatorCL(level) + equationCL = str(exVideoVal) + operatorCL + str(exStandClipping) + tfCL = eval(equationCL) + if tfCL: + errors = { + "Error Type": "Clipping", + "Video Value": exVideoVal, + "Standard Value": "above " + str(exStandBRNG), + "Pass/Fail": "Fail", + } + else: + errors = { + "Error Type": "Out of Broadcast Range", + "Video Value": exVideoVal, + "Standard Value": "above " + str(exStandBRNG), + "Pass/Fail": "Fail", + } + return errors + + +def runfbyfyuv(standardDF, csvDF, frame): + criteria = ["y", "u", "v"] + levels = ["low", "high"] + errors = {} + for fullCriteria in (f"{c}{l}" for c in criteria for l in levels): + level = setLevel(fullCriteria) + errorCriteria = str(fullCriteria) + errors[errorCriteria] = runyuvfbyfanalysis( + standardDF, csvDF, fullCriteria, level, frame + ) + return errors + + +def runfbyfsat(standardDF, csvDF, frame): + errors = {} + criteria = "sat" + leveltoCheck = "max" + fullCriteria = criteria + leveltoCheck + exVideoVal = csvDF.at[frame, fullCriteria] + exBRNG = standardDF.at[criteria, "brnglimit"] + exClipping = standardDF.at[criteria, "clippinglimit"] + exIllegal = standardDF.at[criteria, "illegal"] + if exVideoVal <= exBRNG: + errors[fullCriteria] = {"Video Values": exVideoVal, "Pass/Fail": "Pass"} + else: + if exVideoVal >= exIllegal: + errors[fullCriteria] = { + "Error Type": "Illegal", + "Video Value": exVideoVal, + "Standard Value": exIllegal, + "Pass/Fail": "Fail", + } + # error = errortuple("illegal",fullCriteria, extractSumData, extractStandDataIllegal) + else: + errors[fullCriteria] = { + "Error Type": "Clipping", + "Video Value": exVideoVal, + "Standard Value": exClipping, + "Pass/Fail": "Fail", + } + # error = errortuple("clipping", fullCriteria, extractSumData,extractStandDataClipping) + return errors + + +def runTOUTandVREPanalysis(standardDF, csvDF, frame): + criteria = ["tout", "vrep"] + for c in criteria: + level = "max" + exVideoVal = csvDF.at[frame, c] + exStandMax = standardDF.at[c, level] + errors = runfbyfToutVrep(exStandMax, exVideoVal, c) + return errors + + +def runfbyfToutVrep(exStandMax, exVideoVal, criteria): + errors = {} + if exVideoVal >= exStandMax: + errors[criteria] = { + "Error Type": "Exceeds Standard", + "Video Value": exVideoVal, + "Standard Value": exStandMax, + "Pass/Fail": "Fail", + } + else: + errors[criteria] = {"Video Value": exVideoVal, "Pass/Fail": "Pass"} + return errors + + +def joindict(errors, errorsSat, errorsTOUTVREP): + errors.update(errorsSat) + errors.update(errorsTOUTVREP) + return errors + + +def runfbyfanalysis(standardDF, csvDF): + frameerrors.clear() + frame = 1 + videodataDFlen = len(csvDF) + while frame <= (videodataDFlen - 1): + errors = runfbyfyuv(standardDF, csvDF, frame) + errorsSat = runfbyfsat(standardDF, csvDF, frame) + errorsTOUTVREP = runTOUTandVREPanalysis(standardDF, csvDF, frame) + frameerrors[frame] = joindict(errors, errorsSat, errorsTOUTVREP) + frame += 1 + return frameerrors + + +def dictodftojson(frameerrors): + + df = pd.DataFrame.from_dict(frameerrors, orient="index") + print(tabulate(df)) + + +frameerrors = runfbyfanalysis(standardDF, csvDF) +dictodftojson(frameerrors) diff --git a/nulrdcscripts/vqc/folder.py b/nulrdcscripts/vqc/folder.py new file mode 100644 index 0000000..78c403c --- /dev/null +++ b/nulrdcscripts/vqc/folder.py @@ -0,0 +1,32 @@ +from pathlib import Path +from parseandclean import dataparsing +from videoanalysis import errortiers, fbyfYUV, overallstatistics, videoanalysis + + +def runBulkFolder(inputpath, videoBitDepth): + # Parses the raw XML into individual readings by frame (determined by frametime) + videodata = dataparsing.dataparsingandtabulatingvideo(inputpath) + audiodata = dataparsing.dataparsingandtabulatingaudio(inputpath) + + # Video analysis frame by frame + fbferrors = fbyfYUV.checkerrors(videodata, videoBitDepth) + + # Collects the video summary data - outputs CSV and Dictionary + videostats = overallstatistics.videodatastatistics(videodata) + + videofeedtodict = overallstatistics.videostatstodict(videostats) + videofeedtocsv = overallstatistics.videostatstocsv(videostats) + + # Collects the audio summary data - outputs CSV and Dictionary + audiostats = overallstatistics.audiodatastatistics(audiodata) + + audiofeedtodict = overallstatistics.audiostatstodict(audiostats) + audiofeedtocsv = overallstatistics.audiostatstocsv(audiostats) + + # Video analysis for summary report + summaryvideoerrors = videoanalysis.checkAllVideo(videostats, videoBitDepth) + + # Assigns errors to tiers for verbose reporting + errortiers.errorsvideo(summaryvideoerrors) + + file = file + 1 diff --git a/nulrdcscripts/vqc/framebyframestatistics.py b/nulrdcscripts/vqc/framebyframestatistics.py new file mode 100644 index 0000000..1a50040 --- /dev/null +++ b/nulrdcscripts/vqc/framebyframestatistics.py @@ -0,0 +1,137 @@ +import pandas as pd +from tabulate import tabulate +from nulrdcscripts.vqc.multiuse import ( + setLevel, + setOperatorCL, + setOperatorIR, +) + +frameerrors = {} + + +def runyuvfbyfanalysis(standardDF, videodata, fullCriteria, level, frame): + exVideoVal = videodata.at[frame, fullCriteria] + exStandBRNG = standardDF.at[fullCriteria, "brngout"] + exStandClipping = standardDF.at[fullCriteria, "clipping"] + operatorIR = setOperatorIR(level) + equationIR = str(exVideoVal) + operatorIR + str(exStandBRNG) + tfIR = eval(equationIR) + if tfIR: + errors = {"Video Value": exVideoVal, "Pass/Fail": "Pass"} + else: + operatorCL = setOperatorCL(level) + equationCL = str(exVideoVal) + operatorCL + str(exStandClipping) + tfCL = eval(equationCL) + if tfCL: + errors = { + "Error Type": "Clipping", + "Video Value": exVideoVal, + "Standard Value": "above " + str(exStandBRNG), + "Pass/Fail": "Fail", + } + else: + errors = { + "Error Type": "Out of Broadcast Range", + "Video Value": exVideoVal, + "Standard Value": "above " + str(exStandBRNG), + "Pass/Fail": "Fail", + } + return errors + + +def runfbyfyuv(standardDF, videodata, frame): + criteria = ["y", "u", "v"] + levels = ["low", "high"] + errors = {} + for fullCriteria in (f"{c}{l}" for c in criteria for l in levels): + level = setLevel(fullCriteria) + errorCriteria = str(fullCriteria) + errors[errorCriteria] = runyuvfbyfanalysis( + standardDF, videodata, fullCriteria, level, frame + ) + return errors + + +def runfbyfsat(standardDF, videodata, frame): + errors = {} + criteria = "sat" + leveltoCheck = "max" + fullCriteria = criteria + leveltoCheck + exVideoVal = videodata.at[frame, fullCriteria] + exBRNG = standardDF.at[criteria, "brnglimit"] + exClipping = standardDF.at[criteria, "clippinglimit"] + exIllegal = standardDF.at[criteria, "illegal"] + if exVideoVal <= exBRNG: + errors[fullCriteria] = {"Video Values": exVideoVal, "Pass/Fail": "Pass"} + else: + if exVideoVal >= exIllegal: + errors[fullCriteria] = { + "Error Type": "Illegal", + "Video Value": exVideoVal, + "Standard Value": exIllegal, + "Pass/Fail": "Fail", + } + # error = errortuple("illegal",fullCriteria, extractSumData, extractStandDataIllegal) + else: + errors[fullCriteria] = { + "Error Type": "Clipping", + "Video Value": exVideoVal, + "Standard Value": exClipping, + "Pass/Fail": "Fail", + } + # error = errortuple("clipping", fullCriteria, extractSumData,extractStandDataClipping) + return errors + + +def runTOUTandVREPanalysis(standardDF, videodata, frame): + criteria = ["tout", "vrep"] + for c in criteria: + level = "max" + exVideoVal = videodata.at[frame, c] + exStandMax = standardDF.at[c, level] + errors = runfbyfToutVrep(exStandMax, exVideoVal, c) + return errors + + +def runfbyfToutVrep(exStandMax, exVideoVal, criteria): + errors = {} + if exVideoVal >= exStandMax: + errors[criteria] = { + "Error Type": "Exceeds Standard", + "Video Value": exVideoVal, + "Standard Value": exStandMax, + "Pass/Fail": "Fail", + } + else: + errors[criteria] = {"Video Value": exVideoVal, "Pass/Fail": "Pass"} + return errors + + +def joindict(errors, errorsSat, errorsTOUTVREP): + errors.update(errorsSat) + errors.update(errorsTOUTVREP) + return errors + + +def runfbyfanalysis(standardDF, videodata): + frame = 1 + videodataDFlen = len(videodata) + while frame <= (videodataDFlen - 1): + errors = runfbyfyuv(standardDF, videodata, frame) + errorsSat = runfbyfsat(standardDF, videodata, frame) + errorsTOUTVREP = runTOUTandVREPanalysis(standardDF, videodata, frame) + frameerrors[frame] = joindict(errors, errorsSat, errorsTOUTVREP) + frame += 1 + return frameerrors + + +def dictodftojson(frameerrors): + + frameerrorsDF = pd.DataFrame.from_dict(frameerrors) + with pd.option_context("display.max_rows", 20): + print(tabulate(frameerrorsDF, headers="key", tablefmt="psql")) + + +# framefails = frameerrorsDF[frameerrorsDF["Pass/Fail"] == "Fail"] +# jsonframefails = framefails.to_json("samplefbyf.json", orient="table") +# return jsonframefails diff --git a/nulrdcscripts/vqc/multiuse.py b/nulrdcscripts/vqc/multiuse.py new file mode 100644 index 0000000..2174be5 --- /dev/null +++ b/nulrdcscripts/vqc/multiuse.py @@ -0,0 +1,33 @@ +def setOperatorIR(level): + """Sets the operator to assess if video value is in range""" + if level == ("low"): + operatorIR = ">" + else: + operatorIR = "<" + return operatorIR + + +def setOperatorCL(level): + """Sets operator to use to assess clipping""" + if level == ("low"): + operatorCL = "<=" + else: + operatorCL = ">=" + return operatorCL + + +def setLevel(fullCriteria): + boollevel = fullCriteria.endswith("high") + if boollevel: + level = "high" + else: + level = "low" + return level + + +def setLeveltoCheck(level): + if level == "high": + leveltoCheck = "max" + else: + leveltoCheck = "min" + return leveltoCheck diff --git a/nulrdcscripts/vqc/output/output.py b/nulrdcscripts/vqc/output/output.py new file mode 100644 index 0000000..e224b56 --- /dev/null +++ b/nulrdcscripts/vqc/output/output.py @@ -0,0 +1,12 @@ +from jinja2 import Template as temp + +values = ["clipping","illegal","brng","Exceeds Standards"] +v=0 + +def fullvideoSVR (errors): + ylpassfail = errors[ylow]["Pass/Fail"] + ylVideoValue == errors[ylow]["Video Value"] + if ylpassfail == "Pass": + pass + else: + ylVideoValue \ No newline at end of file diff --git a/nulrdcscripts/vqc/output/output.txt b/nulrdcscripts/vqc/output/output.txt new file mode 100644 index 0000000..ee0f27e --- /dev/null +++ b/nulrdcscripts/vqc/output/output.txt @@ -0,0 +1,39 @@ +Date: {pl_date} +Your video {pl_filename}, contains the following errors: + +YLow {pl_ylpassfail}: + Error Type: {pl_ylerrorType} + Video Value: {pl_ylVideoValue} + +YHigh {pl_yhpassfail}: + Error Type: {pl_yherrorType} + Video Value: {pl_yhVideoValue} + + +ULow {pl_ulpassfail}: + Error Type: {pl_ulerrorType} + Video Value: {pl_ulVideoValue} + +UHigh {pl_uhpassfail}: + Error Type: {pl_uherrorType} + Video Value: {pl_uhVideoValue} + +VLow {pl_vlpassfail}: + Error Type: {pl_vlerrorType} + Video Value: {pl_vlVideoValue} + +VHigh {pl_vhpassfail}: + Error Type: {pl_vherrorType} + Video Value: {pl_vhVideoValue} + +SAT {pl_satpassfail}: + Error Type: {pl_saterrorType} + Video Value: {pl_satVideoValue} + +TOUT {pl_toutpassfail}: + Error Type: {pl_touterrorType} + Video Value: {pl_toutVideoValue} + +VREP {pl_vreppassfail}: + Error Type: {pl_vreperrorType} + Video Value: {pl_vrepVideoValue} \ No newline at end of file diff --git a/nulrdcscripts/vqc/overallStatistics.py b/nulrdcscripts/vqc/overallStatistics.py new file mode 100644 index 0000000..d533741 --- /dev/null +++ b/nulrdcscripts/vqc/overallStatistics.py @@ -0,0 +1,123 @@ +import pandas as pd +import progressbar +import json +from nulrdcscripts.vqc.multiuse import ( + setLevel, + setOperatorCL, + setOperatorIR, + setLeveltoCheck, +) + +# errortuple = namedtuple("Error", ["type", "criteria", "video value", "standard value"]) + +errors = {} + + +def runyuvanalysis(standardDF, sumdatavideo, fullCriteria, level): + leveltoCheck = setLeveltoCheck(level) + extractSumData = sumdatavideo.at[leveltoCheck, fullCriteria] + extractStandDataBRNG = standardDF.at[fullCriteria, "brngout"] + extractStandDataClipping = standardDF.at[fullCriteria, "clipping"] + operatorIR = setOperatorIR(level) + equationIR = str(extractSumData) + operatorIR + str(extractStandDataBRNG) + tfIR = eval(equationIR) + if tfIR: + errors = {"Video Value": extractSumData, "Pass/Fail": "Pass"} + else: + operatorCL = setOperatorCL(level) + equationCL = str(extractSumData) + operatorCL + str(extractStandDataClipping) + tfCL = eval(equationCL) + if tfCL: + errors = { + "Error Type": "Clipping", + "Video Value": extractSumData, + "Standard Value": extractStandDataClipping, + "Pass/Fail": "Fail", + } + # error = errortuple("clipping",fullCriteria,extractSumData,extractStandDataClipping) + else: + errors = { + "Error Type": "Out of Broadcasting Range", + "Video Value": extractSumData, + "Standard Value": extractStandDataBRNG, + "Pass/Fail": "Fail", + } + # error = errortuple("brngout",fullCriteria,extractSumData,extractStandDataBRNG) + return errors + + +def runcheckyuv(standardDF, sumdatavideo): + """Runs the yuvchecks by looping through each yuv value and then the level that is being checked. Returns errors.""" + criteria = ["y", "u", "v"] + levels = ["low", "high"] + for fullCriteria in (f"{c}{l}" for c in criteria for l in levels): + level = setLevel(fullCriteria) + errorcriteria = str(fullCriteria) + errors[errorcriteria] = runyuvanalysis( + standardDF, sumdatavideo, fullCriteria, level + ) + return errors + + +def runsatanalysis(standardDF, sumdatavideo): + """Runs the saturation max value to see if the value is in range, out of broadcasting range,or illegal""" + criteria = "sat" + leveltoCheck = "max" + fullCriteria = criteria + leveltoCheck + extractSumData = sumdatavideo.at[leveltoCheck, fullCriteria] + extractStandDataBRNG = standardDF.at[criteria, "brnglimit"] + extractStandDataClipping = standardDF.at[criteria, "clippinglimit"] + extractStandDataIllegal = standardDF.at[criteria, "illegal"] + if extractSumData <= extractStandDataBRNG: + errors[fullCriteria] = {"Video Values": extractSumData, "Pass/Fail": "Pass"} + else: + if extractSumData >= extractStandDataIllegal: + errors[fullCriteria] = { + "Error Type": "Illegal", + "Video Value": extractSumData, + "Standard Value": extractStandDataIllegal, + "Pass/Fail": "Fail", + } + # error = errortuple("illegal",fullCriteria, extractSumData, extractStandDataIllegal) + else: + errors[fullCriteria] = { + "Error Type": "Clipping", + "Video Value": extractSumData, + "Standard Value": extractStandDataClipping, + "Pass/Fail": "Fail", + } + # error = errortuple("clipping", fullCriteria, extractSumData,extractStandDataClipping) + return errors + + +def runTOUTandVREPanalysis(standardDF, sumdatavideo): + criterium = ["tout", "vrep"] + for criteria in criterium: + level = "max" + extractSumData = sumdatavideo.at[level, criteria] + extractStandDataMax = standardDF.at[criteria, level] + errors = toutVREPcheck(extractSumData, extractStandDataMax, criteria) + return errors + + +def toutVREPcheck(extractSumData, extractStandDataMax, criteria): + if extractSumData >= extractStandDataMax: + errors[criteria] = { + "Error Type": "Exceeds Standard", + "Video Value": extractSumData, + "Standard Value": extractStandDataMax, + "Pass/Fail": "Fail", + } + else: + errors[criteria] = {"Video Value": extractSumData, "Pass/Fail": "Pass"} + return errors + + +def runOverallVideo(standardDF, sumdatavideo): + errors.clear() + + runcheckyuv(standardDF, sumdatavideo) + runsatanalysis(standardDF, sumdatavideo) + runTOUTandVREPanalysis(standardDF, sumdatavideo) + with open("sample.json", "w") as outfile: + json.dump(errors, outfile, indent=4) diff --git a/nulrdcscripts/vqc/poetry.lock b/nulrdcscripts/vqc/poetry.lock new file mode 100644 index 0000000..3846fd0 --- /dev/null +++ b/nulrdcscripts/vqc/poetry.lock @@ -0,0 +1,369 @@ +# This file is automatically @generated by Poetry 1.7.0 and should not be changed by hand. + +[[package]] +name = "beautifulsoup4" +version = "4.12.3" +description = "Screen-scraping library" +optional = false +python-versions = ">=3.6.0" +files = [ + {file = 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pandas as pd +import pathlib + +path8Bit = "Video8BitValues.csv" +path10Bit = "Video10BitValues.csv" + +csv8Bit = os.path.join(os.path.dirname(os.path.abspath(__file__)), path8Bit) +csv10Bit = os.path.join(os.path.dirname(os.path.abspath(__file__)), path10Bit) + + +def inputCheck(inputPath): + """Checks that the input path is a file and not a folder which is currently not supported""" + if os.path.isdir(inputPath): + raise ValueError("Folders are currently not supported by this script") + else: + pass + + +def outputCheck(inputPath, outputPath): + """Checks if there is an output path. If there isn't, the file goes to the directory of the input file. Otherwise, checks if the output path is a folder""" + if outputPath == "": + outputPath = os.path.dirname(inputPath) + else: + outputPathTF = os.path.isdir(outputPath) + if outputPathTF: + outputPath = os.path.normpath(outputPath) + else: + raise ValueError("The output path must be a folder") + return outputPath + + +def setVideoBitDepth(videobitdepth): + """Sets and assigns the values for bit depth for data comparison""" + if videobitdepth == "8bit" or "8" or "8Bit": + standardDF = pd.read_csv(csv8Bit, sep=",", index_col="criteria") + elif videobitdepth == "10bit" or "10" or "10Bit": + standardDF = pd.read_csv(csv10Bit, sep=",", index_col="criteria") + return standardDF + + +def setInputFileType(inputPath): + """Sets the file type of the input file""" + fileExt = pathlib.Path(inputPath).suffix + if fileExt == ".json": + fileType = "JSON" + elif fileExt == ".xml": + fileType = "XML" + else: + raise ValueError("This filetype is not currently supported.") + return fileType diff --git 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+bottomframe.pack(side="bottom") + +leftframe = ttk.Frame(mainframe, padding="10") +leftframe.pack(side="left") + +rightframe = ttk.Frame(mainframe, padding="10") +rightframe.pack(side="right") + +title = ttk.Label(mainframe, text="Video Quality Control", font=("Helvetica", 16)) +title.pack(pady=10) + +# Creates input entry box +input_label = ttk.Label(leftframe, text="Input Path:") +input_label.pack(anchor=W) +input_path = ttk.Entry(leftframe, width=30) +input_path.insert(0, "Input Path to File or Folder") +input_path.pack(pady=5) + +# Creates output entry box +output_label = ttk.Label(leftframe, text="Output Path:") +output_label.pack(anchor=W) +output_path = ttk.Entry(leftframe, width=30) +output_path.insert(0, "Output Path to File or Folder") +output_path.pack(pady=5) + + +# Creates that suggestions radiobuttons --> Yes, No STR +suggest_frame = ttk.Frame(leftframe, padding=10) +suggest_label = ttk.Label(leftframe, text = 'Suggestions? : ') +suggest_label.pack(anchor=W) + +suggest_var = StringVar() +suggestions = ttk.Label(leftframe, text='Suggestions? :') +suggestions_yes = ttk.Radiobutton(leftframe, text="Yes", variable=suggest_var, value='yes') +suggestions_no = ttk.Radiobutton(leftframe, text="No", variable=suggest_var, value='no') +suggestions_yes.pack(anchor=W, padx=10) +suggestions_no.pack(anchor=W,padx=10) + +# Creates the bit depth radiobuttons --> 10, 8, Unknown INT -- Unknown comes back as 999 +bit_frame = ttk.Frame(leftframe,padding=10) +bit_label = ttk.Label(leftframe, text='Bit Depth:') +bit_label.pack(anchor=W) +bitdepth_var = IntVar() +bitdepth_10 = ttk.Radiobutton(leftframe, text='8 Bit', variable=bitdepth_var,value=10) +bitdepth_8 = ttk.Radiobutton(leftframe, text = '10 Bit', variable = bitdepth_var,value=8) +bitdepth_ukn = ttk.Radiobutton(leftframe, text= 'Evaluate',variable = bitdepth_var,value=999) +bitdepth_10.pack(anchor=W,padx=10) +bitdepth_8.pack(anchor=W,padx=10) +bitdepth_ukn.pack(anchor=W,padx=10) + +# Select verbosity level +verb_var_begin=BooleanVar() +verb_var_expert=BooleanVar() +verbosity_frame = ttk.Frame(rightframe, padding=10) +verbosity_label = ttk.Label(rightframe, text='Verbosity Level:') +verbosity_label.pack(anchor=W) +verbosity_beginner = ttk.Checkbutton(rightframe, text='Beginner', variable=verb_var_begin) +verbosity_expert = ttk.Checkbutton(rightframe, text='Expert', variable=verb_var_expert) +verbosity_beginner.pack(anchor=W, padx=10) +verbosity_expert.pack(anchor=W, padx=10) + +# Video Type + +video_type_frame = ttk.Frame(rightframe, padding=10) +video_type_label = ttk.Label(rightframe, text='Video Type:') +video_type_label.pack(anchor=W) +video_type_var = StringVar() +video_type_color = ttk.Radiobutton(rightframe, text='Color', variable=video_type_var, value='color') +video_type_bw= ttk.Radiobutton(rightframe, text='Black & White', variable=video_type_var, value='bw') +video_type_bw.pack(anchor=W, padx=10) +video_type_color.pack(anchor=W, padx=10) + + +# Execute button --> retrieves the 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