Monday, August 6, 2018

TECH | Machine learning: Image classifier model automatically, instantly recognizes demons in images

But wisdom is justified of all her children.
— Luke 7:35

Anything but another demon pic, every one of my Facebook, Twitter, Google+, Instagram, Path, LinkedIn and Swarm followers have thought at one point or another–if not outright said. Are you obsessed with demons or something? all have thought—if not outright said.

I've always ignored these questions in the past, as they are so stupid to ask, and too stupid to answer; but, if I had answered them, I would have said, I hear ya, and, No, respectively.

Ironically, insodoing, I would have begged what I consider to actually be a valid question: Then, what's the deal?

I wouldn't have answered that one, either, though, until I finished that which is presented in this post. The answer would have sounded crazier than taking pictures of violent demons sounds; but, now that I am finished—and alive, thank you very much—I will answer that question:

Introducing the world's first and only machine-learning image classifier model for automatic and instant recognition of demons in digital media:

Registered Apple Developer Connection members can download the first version of the world's first and only demon-recognition CoreML Model (17 Kb) to integrate into their iOS 11.4 (or higher) camera or video apps

To make the model required lots of demon pics. Fortunately, lots of demons were available for recording on digital video. I posted hundreds of them over the past several months to my social media accounts as I acquired and processed them [see Social Media Ad Promos (2017-2018) on Behance.net]. As of yesterday, I fed about 100 of them into Apple's CreateML playground per the instructions in Creating an Image Classifier Model posted to the Apple Developer Connection site.

I got the idea to create the model after integrating Core Image's facial recognition plug-in into an experimental version of my upcoming app, Chroma. Although the framework supplied by Apple for integration by developers purports to recognize only human faces, it also captured some demon faces, too—albeit less than half. It stood to reason that a model trained with only demon faces would perform even better.

The process for creating and testing the model was incredibly simple, although preparing that many images for doing so was a bit tedious. Each image used for creating had to be cropped to just the demon's face only:



Once the images were cropped, they had to be categorized. To start, I separated the individual demons that sometimes group to create the facade of a much larger demon (they look like birds with outspread wings) from images showing actual larger demons (like the one shown in the video above). Then, using the Create ML developer tool in an Xcode playground, I trained and tested my image classifier model:

NOTE | Ever since Google shutdown my YouTube account (without warning and without reason—and without remedy), I've been uploading videos directly to the posts versus hosting them on YouTube; for whatever reason, some look okay (like the first video), while some don't (like the video above). You know, they sure do get a lot of investor money; what are they spending that on, exactly?

The following screen shot shows the statistical (and theoretical) end result of my efforts:
Version 0.1 of my image classified model identifies the smaller, bird-like demons that sometimes stack on top of each other to form a single (assembled) demon 98.91% of the time, whereas it recognizes an assembly of them 93.75% of the time; the model was trained with only 100 out of literally ten of thousands of images showing demons
Reactions to the release of this ground-breaking news can all be generalized based on this single comment:

Stubborn stupidity is a cross no one should bear under the circumstances
COMING UP | Incorporating the image classifier model in an iOS app (for developers only)

Thursday, August 2, 2018

Return to Indiana: Restored health, imperiled freedom, peace and quiet

But they that wait upon the Lord shall renew their strength; they shall mount up with wings as eagles; they shall run, and not be weary; and they shall walk, and not faint.
— Isaiah 40:31


It was the best of days; it was the worst of days—depending on how you look at it.

On one hand, it is clear that my health is on the mend if my leaderboard ranking in three of the Nike Run Club Monthly Challenges, which pits its members against each other in a race to get the most miles in the allotted time, is any indication. As of the time of this writing:
  • In the August Weekly Challenge, I rank #9 out of 49,923 runners world-wide, having in just two days logged 75.43 miles;
  • In the August 100K Challenge, I rank #10 out of 39,879 runners worldwide, having in just two days logged 45.97 miles;
  • In the August 50K Challenge, I rank #8 out of 63,672 runners, worldwide, having logged the same amount of miles as in the August 100K Challenge.
I am one of only three Americans placing in the top 10 of three of the Nike Run Club members' challenges

So far this week, I'm averaging 17 miles per day, having achieved nearly 22 just today:

I started off the month of August with a bang, having used the month of July to warm-up
Surprisingly, I'm suffering from only one (bad) blister on one toe; fortunately, new Nikes are on the way:

My new pair of Nike Air VaporMax 2s (Laser Orange) should arrive by August 7th
On the other hand, I was arrested while walking home from Walmart today. The Greenwood Police Department rolled up on me from behind about a half mile from the store, put me in cuffs, read me my rights and then shuttled me to the store to be identified:

The police car that shuttled me to Wal-Mart for suspect verification
When the officer and I arrived at the store, he pointed me out to the employee hired for loss prevention (pictured below); fortunately, he said it wasn’t me who shoplifted, so I was released at the scene.

The hero of the day, a loss prevention officer employed by Wal-Mart, whose honesty corrected a mistaken identity made by police
I don't have to tell anyone who has read this blog how unnerving unwarranted and surprise police contact can be for me. Nevertheless, I had my own apartment to come to, which, so far, has been extra quiet, and otherwise quite nice:

My living room needs curtains, but is otherwise finishedMy patio, while small, is rather invitingMy bathroom, a little overwrought decoration-wise, but clean