From 183336c4b2c78e53ab89cdb40e211beb4c1b648c Mon Sep 17 00:00:00 2001
From: RealStickman <mrc@frm01.net>
Date: Sun, 23 Oct 2022 20:01:10 +0200
Subject: [PATCH] Python script run through various encoding scenarios
 automatically

    - Saves results in a csv file
        - VMAF scoring (mean, min)
        - File size
---
 Sparks_in_Blender_encode.py | 172 ++++++++++++++++++++++++++++++++++++
 1 file changed, 172 insertions(+)
 create mode 100755 Sparks_in_Blender_encode.py

diff --git a/Sparks_in_Blender_encode.py b/Sparks_in_Blender_encode.py
new file mode 100755
index 0000000..70f53a1
--- /dev/null
+++ b/Sparks_in_Blender_encode.py
@@ -0,0 +1,172 @@
+#!/usr/bin/env python3
+
+import os
+
+import time
+
+import csv
+
+import ffmpy
+
+from multiprocessing import cpu_count
+
+from collections import OrderedDict
+
+import json
+
+# always round timestamp to integer
+def now():
+    return int(time.time())
+
+
+def write_line(
+    codec: str,
+    crf: str,
+    preset: str,
+    infile: str,
+    outfile: str,
+    outfilesize: float,
+    enctime: int,
+    vmafmean: float,
+    vmafmin: float,
+):
+    """
+    Write line to data csv
+
+    Parameters:
+        codec (str): Codec used
+        crf (str): CRF used
+        preset (str): Preset used
+        infile (str): Input file name
+        outfile (str): Output file name
+        outfilesize (float): Size of output file
+        enctime (int): Time to encode
+        vmafmean (float): Mean VMAF score
+        vmafmin (float): Min VMAF score
+    """
+    with open(datafile, "a", newline="") as file:
+        write = csv.writer(file)
+        write.writerow(
+            (
+                codec,
+                crf,
+                preset,
+                infile,
+                outfile,
+                outfilesize,
+                enctime,
+                vmafmean,
+                vmafmin,
+            )
+        )
+
+
+if __name__ == "__main__":
+    encoding = {
+        "libx264": {
+            "crf": [15, 20, 25, 30, 35],
+            "presets": ["fast", "medium", "slow", "veryslow"],
+        },
+        "libx265": {
+            "crf": [15, 20, 25, 30, 35],
+            "presets": ["fast", "medium", "slow", "veryslow"],
+        },
+        "libaom-av1": {"crf": [20, 25, 30, 35, 40], "presets": [0, 2, 4, 6]},
+        "libsvtav1": {"crf": [20, 25, 30, 35, 40], "presets": [0, 4, 8, 12]},
+    }
+
+    if not os.path.isdir("encoded"):
+        os.mkdir("encoded")
+
+    datafile = "data-" + str(now()) + ".csv"
+
+    with open(datafile, "w", newline="") as file:
+        write = csv.writer(file)
+        write.writerow(
+            (
+                "Codec",
+                "CRF",
+                "Preset",
+                "Input file",
+                "Output file",
+                "Output file size (MiB)",
+                "Encode time (s)",
+                "VMAF Score (mean)",
+                "VMAF Score (min)",
+            )
+        )
+
+    for codec in encoding:
+        for crf in encoding[codec]["crf"]:
+            for preset in encoding[codec]["presets"]:
+                outputfile = os.path.join(
+                    "encoded",
+                    (
+                        "Sparks_in_Blender-codec_"
+                        + codec
+                        + "-crf_"
+                        + str(crf)
+                        + "-preset_"
+                        + str(preset)
+                        + ".mkv"
+                    ),
+                )
+
+                # libaom needs additional options
+                if codec == "libaom-av1":
+                    ff = ffmpy.FFmpeg(
+                        inputs={"Sparks_in_Blender.webm": None},
+                        outputs={
+                            outputfile: "-c:v {videocodec} -crf {crf} -b:v 0 -cpu-used {preset} -row-mt 1 -tiles 2x2 -g 240 -map 0:v:0 ".format(
+                                videocodec=codec,
+                                crf=crf,
+                                preset=preset,
+                            )
+                        },
+                    )
+                else:
+                    ff = ffmpy.FFmpeg(
+                        inputs={"Sparks_in_Blender.webm": None},
+                        outputs={
+                            outputfile: "-c:v {videocodec} -crf {crf} -preset {preset} -g 240 -map 0:v:0 ".format(
+                                videocodec=codec,
+                                crf=crf,
+                                preset=preset,
+                            )
+                        },
+                    )
+
+                starttime = now()
+                ff.run()
+                endtime = now()
+                difftime = int(endtime - starttime)
+
+                outputfilesize = os.path.getsize(outputfile) / 1024 / 1024
+
+                ffvmaf = ffmpy.FFmpeg(
+                    inputs=OrderedDict(
+                        [(outputfile, None), ("Sparks_in_Blender.webm", None)]
+                    ),
+                    outputs={
+                        "-": "-filter_complex libvmaf=log_fmt=json:n_threads={cputhreads}:log_path=vmaf.json -f null".format(
+                            cputhreads=cpu_count()
+                        )
+                    },
+                )
+
+                ffvmaf.run()
+
+                with open("vmaf.json", "r") as file:
+                    vmaf = json.load(file)
+
+                write_line(
+                    codec=codec,
+                    crf=crf,
+                    preset=preset,
+                    infile="Sparks_in_Blender.webm",
+                    outfile=outputfile,
+                    outfilesize=outputfilesize,
+                    enctime=difftime,
+                    vmafmean=vmaf["pooled_metrics"]["vmaf"]["mean"],
+                    vmafmin=vmaf["pooled_metrics"]["vmaf"]["min"],
+                )