barefootstache @barefootstache@qoto.org

One reason why squashing moths is a bad idea is that they can stain the surface they are on, especially if it's drywall. Scrubbing the stain after the matter usually makes the stain worse.

Instead of squashing moths a preferred method it to use an electric fly swatter and zap them in flight.

When moths are on the wall they have a tendency to fall/jump downwards. With this knowledge one takes the swatter while being live (active) and slowly travel upwards until one barely touches the moth. In the best case the moth will jump down and get instantly zapped. In the case it flies away, the racket is in the position to quickly flick the wrist and zap it in mid flight.

#moth #pest #LifeHack

#BloggingChallenge (54/100)

Summary:

MyRuckClub: mention the upcoming events

#BloggingChallenge (53/100)

Summary:

- Tutorial: How to add quick actions trays in #OsmAnd: https://en.osm.town/@barefootstache/112951157305917704
- 1 devlog: progress towards #MyRuckClub app with implementation of #turso

#BloggingChallenge (52/100)

After completing the #DailyBloggingChallenge for a year a couple of days ago, I will continue the practice of blogging on a weekly basis. This has been proven quite fruitful when doing the switch during the #MappingChallenge.

I am currently uncertain how the challenge shall continue, if it shall just be a summary over the week or a fully developed post.

The only goal that I will be placing onto myself is writing out one long form piece of content that is post worthy onto the barefootstache website. The couple that I did achieve to post in the past year, I really enjoyed the process much more than doing the daily posts.

My preferred way of making #tea is using a #FrenchPress since I use loose grounds/herbs.

Until recently, I could not figure out why when the plunger is all the way done and one tries to pour all the liquid in the beacon, there will always be some underneath the plunger. This made cleaning the soggy herbs more messy than necessary.

I finally noticed that if one pulls up the plunger ever so slightly, the leftover liquid will pour with more ease and thereby make cleanup easier.

#LifeHack #GreenTea #BlackTea #HerbalTea

While writing up a reflection of completing the #DailyBloggingChallenge for a year, I realized that my #Hugo based website is missing #SEO data in its head.

The [hugo clarity theme](https://github.com/chipzoller/hugo-clarity) comes with SEO though it is not activated by default and one would only realize it when going through the `layouts/partials/opengraph.html` code. There is the mention of the site param `blogDir` that is not implemented anywhere else within the code.

Thus to activate the SEO over #SchemaOrg and #JsonLd one needs to add the param `blogDir` and point it to the designated section. Using the exampleSite as a reference it would be `blogDir = "post"` in the `config/_default/params.toml` file.

#DailyBloggingChallenge (365/365)

The only caveat of the #Whisper project is that it only works on 16-bit #WAV files.

There is a #FFMPEG script on how to do it via the #terminal

`ffmpeg -i input.mp3 -ar 16000 -ac 1 -c:a pcm_s16le output.wav`

#DailyBloggingChallenge (364/365)

The 'Quick Start' section in the Readme sufficed for setting up.

The only thing that I had to change in the `./models/download-ggml-model.sh` script (1) is remove the option `--show-progress` on line 105. Seems like GNU Wget2 2.1.0 doesn't have that option.

Alternatively one can replace the option with

`--progress=bar --force-progress`

- 1: https://github.com/ggerganov/whisper.cpp/blob/master/models/download-ggml-model.sh

#wget #bash

#DailyBloggingChallenge (363/365)

Instead opted in to using #Whisper which also works with #KdenLive.

Although Whisper is originally written in #Python there is a #CPP project that makes transcribing very fast. It took less than 2min to transcribe the 26 min audio clip.

https://github.com/ggerganov/whisper.cpp

#DailyBloggingChallenge (362/365)

Originally wanted to use #VOSK to transcribe the #SpeechToText. Initially tried it out over #KdenLive and its 'Speech Recognition' tool.

This took quite awhile to setup, since it is not concrete what kind file format, if any, the VOSK model should have. Additionally, the recommendation of setting up a virtual #Python environment didn't work as expect and went with the global approach.

And finally scratched the whole approach, once realizing that transcribing 26 min audio clip is taking longer than 10min.