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No commits in common. "e4baf3d28f87c64e003d7ee5c6638d870eeb1ab0" and "1f5036effe93b8bb713c9cf765fe9cd7adbf9ec1" have entirely different histories.
e4baf3d28f
...
1f5036effe
1
.gitignore
vendored
1
.gitignore
vendored
@ -1,4 +1,3 @@
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vmaf.json
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*.csv
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encoded/
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*.log
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@ -50,7 +50,7 @@ encoding: dict[str, Any] = {
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# program version
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# make tests reproducible by tag
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version = "v0.0.1a3"
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version = "v0.0.1a2"
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# always round timestamp to integer
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def now():
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@ -66,23 +66,19 @@ def write_line(
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enctime: int,
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vmafmean: float,
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vmafmin: float,
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ssim: float,
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mse: float,
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):
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"""
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Write line to data csv
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Parameters:
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codec (str): Codec used
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crf (int): CRF used
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preset (str/int): Preset used
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infile (str): Input file name
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outfilesize (float): Size of output file
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enctime (int): Time to encode
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vmafmean (float): Mean VMAF score
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vmafmin (float): Min VMAF score
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ssim (float): SSIM Score
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mse (float): MSE Score
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codec (str): Codec used
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crf (int): CRF used
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preset (str/int): Preset used
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infile (str): Input file name
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outfilesize (float): Size of output file
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enctime (int): Time to encode
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vmafmean (float): Mean VMAF score
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vmafmin (float): Min VMAF score
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"""
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with open(datafile, "a", newline="") as file:
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write = csv.writer(file)
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@ -96,8 +92,6 @@ def write_line(
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enctime,
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vmafmean,
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vmafmin,
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ssim,
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mse,
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)
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)
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@ -185,19 +179,25 @@ def score_vmaf(outputfile: str, inputfile: str) -> dict[str, float]:
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return vmaf
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def parse_kv_files(inputfile: str) -> list[dict[str, Any]]:
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# create list of dicts. Each dict is one line in the file
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lines: list[dict[str, Any]] = []
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# Steps to get mse value
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with open(inputfile) as file:
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for line in file:
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linelist = line.rstrip().split()
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# NOTE stripping the last item because ssim has values like this in the location: (26.088579)
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# For PSNR, psnr_v:87.80 is affected. (YUV color space). Not really a priority to fix atm
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linedict = dict(kv.split(":") for kv in linelist[:-1])
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lines.append(linedict)
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def score_psnr(outputfile: str, inputfile: str):
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"""
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Calculate a file's MSE (mean-square error) using PSNR. A lower value is better
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return lines
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Parameters:
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outputfile (str): Path to output file
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inputfile (str): Path to input file
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Return:
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TBD
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"""
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ff = ffmpy.FFmpeg(
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inputs=OrderedDict([(outputfile, None), (inputfile, None)]),
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outputs={"-": "-lavfi psnr=stats_file=psnr.log -f null"},
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)
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ff.run()
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# Steps to get mse value
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def score_ssim(outputfile: str, inputfile: str):
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@ -218,51 +218,7 @@ def score_ssim(outputfile: str, inputfile: str):
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ff.run()
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# get average ssim value
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ssim: list[dict[str, Any]] = parse_kv_files("ssim.log")
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# add all ssim_avg values together
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ssim_tot: float = 0.0
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for i in ssim:
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ssim_tot += float(i["All"])
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# get mse average
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ssim_avg: float = ssim_tot / len(ssim)
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return ssim_avg
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def score_psnr(outputfile: str, inputfile: str) -> float:
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"""
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Calculate a file's MSE (mean-square error) using PSNR. A lower value is better
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Parameters:
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outputfile (str): Path to output file
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inputfile (str): Path to input file
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Return:
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TBD
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"""
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ff = ffmpy.FFmpeg(
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inputs=OrderedDict([(outputfile, None), (inputfile, None)]),
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outputs={"-": "-lavfi psnr=stats_file=psnr.log -f null"},
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# outputs={"-": "-filter_complex psnr=stats_file=psnr.log -f null"},
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)
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ff.run()
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# get average mse value
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psnr: list[dict[str, Any]] = parse_kv_files("psnr.log")
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# add all mse_avg values together
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mse_tot: float = 0.0
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for i in psnr:
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mse_tot += float(i["mse_avg"])
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# get mse average
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mse_avg: float = mse_tot / len(psnr)
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return mse_avg
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# Steps to get ssim value
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if __name__ == "__main__":
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@ -283,8 +239,6 @@ if __name__ == "__main__":
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"Encode time (s)",
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"VMAF Score (mean)",
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"VMAF Score (min)",
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"SSIM Score",
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"MSE Score",
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)
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)
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@ -333,10 +287,6 @@ if __name__ == "__main__":
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vmaf = score_vmaf(outputfile=outputfile, inputfile=inputfile)
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ssim = score_ssim(outputfile=outputfile, inputfile=inputfile)
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mse = score_psnr(outputfile=outputfile, inputfile=inputfile)
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write_line(
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codec=codec,
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crf=crf,
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@ -346,8 +296,6 @@ if __name__ == "__main__":
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enctime=difftime,
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vmafmean=vmaf["mean"],
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vmafmin=vmaf["min"],
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ssim=ssim,
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mse=mse,
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)
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os.remove(outputfile)
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