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##FFmpeg greenscreen process

ffmpeg -hwaccel videotoolbox -i background.jpg -i out.mp4 -filter_complex "[1:v]colorkey=0x34d454:0.3:0.15[ckout];[0:v][ckout]overlay[despill];[despill] despill=green[colorspace];[colorspace]format=yuv420p[out]" -map "[out]" output.mp4

###Explanation

*hwaccel enable hardware accelartion profile videotoolbok is avlaiable on my mac for this codec *-i is the input, the greenscreen video is second and the background image is first *-filter_complex chains up the filters in a string *colorkey provides the color of the green screen in hex, the threshold to match (higher is more) and the blend (higher is more)

Google dork cheatsheet

Search filters

Filter	Description	Example
allintext	Searches for occurrences of all the keywords given.	`allintext:"keyword"`
intext	Searches for the occurrences of keywords all at once or one at a time.	`intext:"keyword"`
inurl	Searches for a URL matching one of the keywords.	`inurl:"keyword"`
allinurl	Searches for a URL matching all the keywords in the query.	`allinurl:"keyword"`
intitle	Searches for occurrences of keywords in title all or one.	`intitle:"keyword"`

Lecture 1: Introduction to Research — [📝Lecture Notebooks] [▶️Video]
Lecture 2: Introduction to Python — [📝Lecture Notebooks] [▶️Video]
Lecture 3: Introduction to NumPy — [📝Lecture Notebooks] [▶️Video]
Lecture 4: Introduction to pandas — [📝Lecture Notebooks] [▶️Video]
Lecture 5: Plotting Data — [📝Lecture Notebooks] [[▶️Vide

This is not working complete code.

This is strictly a v0, scrapy, proof of concept for the first version of a personal AI Assistant working end to end in just ~322 LOC.

It's only a frame of reference for you to consume the core ideas of how to build a POC of a personal AI Assistant.

To see the high level of how this works check out the explanation video. To follow our agentic journey check out the @IndyDevDan channel.

Stay focused, keep building.

Copied from http://code.lancepollard.com/complete-list-of-html-meta-tags/

Basic HTML Meta Tags

<meta charset='UTF-8'>
<meta name='keywords' content='your, tags'>
<meta name='description' content='150 words'>
<meta name='subject' content='your website's subject'>
<meta name='copyright' content='company name'>

	import torch
	import torch.nn as nn

	class LabelSmoothing(nn.Module):
	"""
	NLL loss with label smoothing.
	"""
	def __init__(self, smoothing=0.0):
	"""
	Constructor for the LabelSmoothing module.

	/** !
	* Floyd-Warshall example
	*
	* @author Jacob Smith
	* @file floyd-warshall.c
	* @date Fri Apr 19 21:06:53 MDT 2024
	*/

	// Standard library
	#include <stdio.h>

	# mihomo (Clash Meta) 懒人配置
	# 版本 V1.4.1-231211
	# https://gist.github.com/liuran001/5ca84f7def53c70b554d3f765ff86a33
	# 作者: 笨蛋ovo (bdovo.cc)
	# Telegram: https://t.me/baka_not_baka
	# 关注我的 Telegram 频道谢谢喵 https://t.me/s/BDovo_Channel
	# 修改自官方示例规则 https://wiki.metacubex.one/example/#meta
	# 转载请保留此注释
	# 尽量添加了较为详尽的注释，不理解的地方建议对照虚空终端 (Clash Meta) Docs 进行理解
	# 虚空终端 (Clash Meta) Docs 地址: https://wiki.metacubex.one

	#@title Stable Diffusion web UI Forge（最新版）をGoogle Colabで起動するためのコマンド

	#@markdown ## このColabノートブックについて
	#@markdown [Stable Diffusion web UI Forge](https://github.com/lllyasviel/stable-diffusion-webui-forge) をGoogle Colabで起動するためのノートブックとなります。

	#@markdown 利用したいモデルや拡張機能、LoRAなどにチェックを入れた上で実行ボタンを押すことで、設定した内容でStable Diffusion web UIが起動します。

	#@markdown また各項目には公式ページへのリンクをつけています。利用の際は公式ページよりライセンスなどを確認した上でご利用ください。

	### Stable Diffusion web UIインストール

	Registration Code
	Name : www.xyraclius.com
	Serial : OOCRYIMDMDPWRETFPSUZ