Compass | Silico Modeling of Metabolic Heterogeneity using Single | Genomics library

I have an ssh config file like this. I have a proxy jump to host1 from test2.

I have a dataset of items inside an orders collection:

I want to write a programm, that checks if a car is allowed to drive/turn on a crossroads. The cars are identified by colors (e.g. blue, grey, red), the positions of the cars are defined by compass direction (north, east, south, west). the function to check if allowed to drive is allow(Color). (e.g. allow(blue).)

This is my actual code:

I am having some issues with saving an object parameter into a mongoose map. My collection looks like this. The collection's name is guildtickets:

Context: I am trying to find the directional heading from a small image of a compass. Directional heading meaning if the red (north) point is 90 degrees counter-clockwise from the top, the viewer is facing East, 180 degrees is south, 270 is west, 0 is north. etc. I understand there are limitations with such a small blurry image but I'd like to be as accurate as possible. The compass is overlaid on street view imagery meaning the background is noisy and unpredictable.

The first strategy I thought of was to find the red pixel that is furthest away from the center and calculate the directional heading from that. The math is simple enough.

The tough part for me is differentiating the red pixels from everything else. Especially because almost any color could be in the background.

My first thought was to black out the completely transparent parts to eliminate the everything but the white transparent ring and the tips of the compass.

True Compass Values: 35.9901, 84.8366, 104.4101

These values are taken from the source code.

I then used this solution to find the closest RGB value to a user given list of colors. After calibrating the list of colors I was able to create a list that found some of the compass's inner most pixels. This yielded the correct result within +/- 3 degrees. However, when I tried altering the list to include every pixel of the red compass tip, there would be background pixels that would be registered as "red" and therefore mess up the calculation.

I have manually found the end of the tip using this tool and the result always ends up within +/- 1 degree ( .5 in most cases ) so I hope this should be possible

The original RGB value of the red in the compass is (184, 42, 42) and (204, 47, 48) but the images are from screenshots of a video which results in the tip/edge pixels being blurred and blackish/greyish.

Is there a better way of going about this than the closest_color() method? If so, what, if not, how can I calibrate a list of colors that will work?

For MongoDB 4.4.6

For a collection with an array - If I use

I have a collection "people" with documents like this one:

MongoDb documents looks like this:

Using Compass initially, I then need to convert it into the PHP library.

So far, I have a 1st stage that filters the documents on 2 fields using $match:

• comp.id (sub-document / array)
• playerId

Code is: $match (from drop-down)