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dedublicating frames from video

good explanation
https://kodintent.wordpress.com/2020/04/19/ffmpeg-mpdecimate-parameters/

ffmpeg mpdecimate filter

    This will generate a console readout showing which frames the filter thinks are duplicates.

    ffmpeg -i input.mp4 -vf mpdecimate -loglevel debug -f null -

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from time import time
import csv

from ffmpeg import output
from  ffmpy import FFmpeg
from ffmpeg_quality_metrics import FfmpegQualityMetrics as metric

#crfs = [str(i) for i in range(27,40,5)]+
crfs = [str(i) for i in range(25,41,5)]
#presets = [str(i) for i in range(13,6,-1)]

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#!/bin/bash
#
# https://github.com/Nyr/wireguard-install
#
# Copyright (c) 2020 Nyr. Released under the MIT License.

# Example:    192:168:30:0 or 172.16.5.0 or 10.85.0.0
local_ip4_adress=10.7.0.0

# Example:    0000:0000:0000 or AFAF:AFAF:AFAF

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OBS 

subme=0 me=dia ref=5 deblock=-6,-6 psy=0 nr=100 bframes=2 b_bias=100 scenecut=0 qpstep=10 keyint=300

for twitch  keyint=120

preset PLACEBO
profile HIGH

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import torch
model = torch.load("model.ckpt")
for x in model['state_dict'].keys():
    model['state_dict'][x] = model['state_dict'][x].to(torch.float16)
torch.save(model,"model_f16.ckpt")

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from multiprocessing import pool

import zipfile as zf
import json
import os.path
import base64

def remove_binary(text, zipname = None, fb2name=None, image_zip=None):
    ts = text.split(b'<binary')
    image_cnt = 10000

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import argparse
import sys

import num2words.base
import transliterate


def process_text(filename,tokens):
    f = open(filename,'r', encoding="utf-8")
    txt :str = f.read()

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import argparse
import random

import gym
import numpy as np
from itertools import count

import torch
import torch.nn as nn
import torch.nn.functional as F

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// 1665-1650 Kh/s
"here is no filter here"

// 1635 Kh/s
if (T == 1) // high mining
            {
                bool good = true;
                for (int bcheck = 0; bcheck < conf.high / 8; bcheck++) {
                    if (sha512_hash[bcheck] != 0xFF)
                    {