Python script run through various encoding scenarios automatically
- Saves results in a csv file - VMAF scoring (mean, min) - File size
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Sparks_in_Blender_encode.py
Executable file
172
Sparks_in_Blender_encode.py
Executable file
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#!/usr/bin/env python3
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import os
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import time
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import csv
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import ffmpy
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from multiprocessing import cpu_count
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from collections import OrderedDict
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import json
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# always round timestamp to integer
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def now():
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return int(time.time())
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def write_line(
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codec: str,
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crf: str,
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preset: str,
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infile: str,
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outfile: str,
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outfilesize: float,
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enctime: int,
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vmafmean: float,
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vmafmin: 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 (str): CRF used
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preset (str): Preset used
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infile (str): Input file name
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outfile (str): Output 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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write.writerow(
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(
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codec,
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crf,
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preset,
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infile,
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outfile,
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outfilesize,
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enctime,
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vmafmean,
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vmafmin,
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)
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)
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if __name__ == "__main__":
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encoding = {
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"libx264": {
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"crf": [15, 20, 25, 30, 35],
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"presets": ["fast", "medium", "slow", "veryslow"],
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},
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"libx265": {
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"crf": [15, 20, 25, 30, 35],
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"presets": ["fast", "medium", "slow", "veryslow"],
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},
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"libaom-av1": {"crf": [20, 25, 30, 35, 40], "presets": [0, 2, 4, 6]},
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"libsvtav1": {"crf": [20, 25, 30, 35, 40], "presets": [0, 4, 8, 12]},
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}
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if not os.path.isdir("encoded"):
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os.mkdir("encoded")
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datafile = "data-" + str(now()) + ".csv"
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with open(datafile, "w", newline="") as file:
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write = csv.writer(file)
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write.writerow(
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(
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"Codec",
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"CRF",
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"Preset",
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"Input file",
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"Output file",
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"Output file size (MiB)",
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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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)
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)
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for codec in encoding:
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for crf in encoding[codec]["crf"]:
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for preset in encoding[codec]["presets"]:
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outputfile = os.path.join(
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"encoded",
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(
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"Sparks_in_Blender-codec_"
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+ codec
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+ "-crf_"
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+ str(crf)
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+ "-preset_"
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+ str(preset)
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+ ".mkv"
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),
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)
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# libaom needs additional options
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if codec == "libaom-av1":
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ff = ffmpy.FFmpeg(
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inputs={"Sparks_in_Blender.webm": None},
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outputs={
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outputfile: "-c:v {videocodec} -crf {crf} -b:v 0 -cpu-used {preset} -row-mt 1 -tiles 2x2 -g 240 -map 0:v:0 ".format(
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videocodec=codec,
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crf=crf,
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preset=preset,
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)
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},
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)
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else:
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ff = ffmpy.FFmpeg(
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inputs={"Sparks_in_Blender.webm": None},
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outputs={
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outputfile: "-c:v {videocodec} -crf {crf} -preset {preset} -g 240 -map 0:v:0 ".format(
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videocodec=codec,
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crf=crf,
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preset=preset,
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)
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},
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)
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starttime = now()
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ff.run()
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endtime = now()
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difftime = int(endtime - starttime)
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outputfilesize = os.path.getsize(outputfile) / 1024 / 1024
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ffvmaf = ffmpy.FFmpeg(
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inputs=OrderedDict(
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[(outputfile, None), ("Sparks_in_Blender.webm", None)]
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),
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outputs={
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"-": "-filter_complex libvmaf=log_fmt=json:n_threads={cputhreads}:log_path=vmaf.json -f null".format(
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cputhreads=cpu_count()
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)
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},
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)
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ffvmaf.run()
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with open("vmaf.json", "r") as file:
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vmaf = json.load(file)
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write_line(
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codec=codec,
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crf=crf,
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preset=preset,
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infile="Sparks_in_Blender.webm",
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outfile=outputfile,
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outfilesize=outputfilesize,
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enctime=difftime,
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vmafmean=vmaf["pooled_metrics"]["vmaf"]["mean"],
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vmafmin=vmaf["pooled_metrics"]["vmaf"]["min"],
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)
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