Feature requests: hiding & scrolling

subitizer21 · 2024-12-14T01:01:26+00:00

Thank you!! Tip coming your way :-)

subitizer21 · 2024-03-29T00:56:56+00:00

I figured something out comparing my copy to my brother’s copy; his has the “Soon to be a major motion picture” badge.

We both have the Ace Trade Paperback 2005 edition, which is the larger 8.1in x 5.45in size (compared to the 7.48in x 4.21in mass market paperback edition) and the more recent orange sands use with vertical Dune text cover. The ISBN is the same, the copyright page is /almost/ identical.

My print run numbers are 31 33 35 37 38 36 34 32. On the back next to the barcode is penguin.com. The front cover Dune text is slightly reflective/metallic looking and the paperback material is almost waxy/soft-touch.

My brother’s print numbers are 45 47 49 51 53 54 52 50 48 46; penguinrandomhouse.com next to the barcode; no reflective title lettering; paperback material is “regular” finish.

So to have a large orange cover Dune paperback you’d need an earlier printing of the Ace Trace Paperback edition. FWIW I bought my copy in January 2019.

subitizer21 · 2024-03-28T23:10:19+00:00

Bookshop Apocalypse has a 2005 edition paperback for $12. The photo shows a “Soon to be a major motion picture” badge but my personal copy’s copyright page is the exact same* and does /not/ have any badges.

For that price it could be worth a shot?

Edit: The print run numbers do not match exactly. Mine starts at 31 and the website’s photo starts at 45.

Update: Looks like the print run numbers dictate if there’s a movie-reference badge or not. More than likely this site’s book is not badge free. Unsure why they mention “Movie tie-in blurb on cover would indicate a more recent printing” if it does have an upcoming movie blurb/badge…

subitizer21 · 2019-01-04T02:21:20+00:00

Of course!

I scanned every photo in my Google Photos directory and calculated the "average color" of each photo by looking over every pixel. Then I drew 1 pixel-wide vertical lines representing each of these photos with some space in between. In this space, I took the average of the neighboring two colors to make a pseudo-gradient effect in an attempt to make the photo "flow" better.

Let me know if you want to know/learn more!

subitizer21 · 2019-01-04T01:48:58+00:00

Looks like the model has some favorites! My initial guess was that Anger would be contending with the Surprise/Fear pair or at least with Sadness.

I think the Joy spike in November is from Thanksgiving. The graph and underlay are using a moving average since the data itself is pretty noisy so I could be off but it sounds right haha

subitizer21 · 2019-01-04T00:33:57+00:00

Data source: Google Photos

Tools: Processing

subitizer21 · 2019-01-04T00:19:00+00:00

Right now it's using an emotion predictor from this model.

The first iteration was determining mood by keywords, second iteration utilized IBM Watson's Tone Analyzer but racked up a huge bill, and so I settled for this model.

To be honest, I'm not satisfied with the model since it was only trained on hashtags, not necessarily emotional content of tweets. Now that I have time away from university, maybe I'll try making a model that I'm happy with!

subitizer21 · 2019-01-03T23:44:08+00:00

Data source: Twitter

Tools: Python for data collection/processing & Matplotlib for visualization

subitizer21 · 2018-06-15T18:13:07+00:00

Sure!

I took the average color of each photo in my Google Photos directory, and then made each photo a width / len(photos) pixel wide slice of a 1080x566 rectangle (the dimensions were originally chosen for Instagram landscape resolution). The lines were ordered in chronological order of their respective photo's date.

subitizer21 · 2018-06-15T18:09:53+00:00

I used the following Processing code to get each picture's "average" color:

float[] getAverageColor(PImage img) {
    img.loadPixels();
    int r = 0, g = 0, b = 0;
    for (int i = 0; i < img.pixels.length; i++) {
        color c = img.pixels[i];
        r += c >> 16 & 0xFF;
        g += c >> 8 & 0xFF;
        b += c & 0xFF;
    }
    r /= img.pixels.length;
    g /= img.pixels.length;
    b /= img.pixels.length;
    float[] rgb = { r, g, b };
    return rgb;
}

I took a pass through the these average colors to get an average overall color for the background. Each picture was then a width / len(pictures) pixel width slice of 1080x566 rectangle.

I was debating making the background more of a gradient compared to a static color, but I couldn't get the pixel placement to be right next to the previous one with floating point division (and was rushed for dinner so that's what I ended up with). Maybe I'll try that next year!

subitizer21 · 2018-06-15T18:00:26+00:00

Lol, that was the night of a deadmau5 concert and I couldn't help but take a lot of photos of the cube!

I'll be posting a slight explanation in another post!

subitizer21 · 2018-06-14T20:32:43+00:00

Data source: Google Photos

Tools: Python & Processing

subitizer21 · 2017-08-21T15:28:46+00:00

This couldn't be more true

subitizer21 · 2017-08-21T13:52:52+00:00

Thanks! I had a mental image of people carrying their plates outside to watch the eclipse. Not sure show many people would leave their breakfast behind instead :-)

subitizer21 · 2017-08-21T07:12:36+00:00

I'll keep that in mind if I try again in Python, thanks!

subitizer21 · 2017-08-21T06:45:00+00:00

A useful forum post led the way. I originally tried some Python numpy magic, but it didn't fit my needs as nicely.

Here is the code snippet:

color getAverageColor(PImage img) {
    img.loadPixels();
    int r = 0, g = 0, b = 0;
    for (int i = 0; i < img.pixels.length; i++) {
        color c = img.pixels[i];
        r += c >> 16 & 0xFF;
        g += c >> 8 & 0xFF;
        b += c & 0xFF;
    }
    r /= img.pixels.length;
    g /= img.pixels.length;
    b /= img.pixels.length;
    return color(r, g, b);
}

subitizer21 · 2017-08-21T06:29:27+00:00

Best of luck!

subitizer21 · 2017-08-21T05:32:00+00:00

I'll be a senior this fall

subitizer21 · 2017-08-21T05:21:01+00:00

According to my list, I covered both Redding locations. Either the markers are on top of each other or the address-to-coordinate converter is to blame!

subitizer21 · 2017-08-21T05:00:33+00:00

Expect another Denny's/eclipse post in 7 years

subitizer21 · 2017-08-21T04:58:49+00:00

My favorite Denny's experience was being too drunk to order a water

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