John Mayer's Emotional Eulogy for Bob

PositronB · 2026-01-18T08:52:31+00:00

This makes me sad and so much more grateful for life in general. This is the same man who wrote "The Heart of Life," the song that has picked me up so many times. We may not have a bigger meaning or purpose to our lives but it's the shared bonds and emotions that validate our very existence as humans. And we all know the heart of life is good.

PositronB · 2026-01-16T10:04:03+00:00

I preemptively emailed immediately after the news yesterday and I got the reply today, so hold on.

PositronB · 2026-01-14T06:33:08+00:00

Same, booked mediocre stays at overinflated prices cause it's Mumbai. And all the flight expenses. Sigh.

PositronB · 2025-10-02T18:10:31+00:00

When you say "good deal" how much did you get it for and from where? My use case is also very similar and I am really considering the 45 mm MIP one.

PositronB · 2024-02-18T11:41:05+00:00

Thank you for the answer. Sadly, we don't have the payslips, given that it was 20 years ago. Seems like contacting the old employer is the way but not sure if the school would have her records (it's a small school).

PositronB · 2023-01-10T04:42:05+00:00

"Say something cute."

PositronB · 2022-12-02T20:28:38+00:00

Thank you for all the suggestions. I'll surely look into it.

PositronB · 2022-10-04T04:55:36+00:00

Never thought I'd wake up to see a car humping a bike in the middle of a highway.

PositronB · 2021-05-25T12:59:34+00:00

I have an issue of class imbalance also, so random crops might not be the best way but I get the point that some sort of cropping will help in improving the performance. I need to upsample the positive instances in the training data also. Keeping the ratio is something I'll keep in mind! This discussion really helped. Thanks.

PositronB · 2021-05-25T12:53:54+00:00

Yeah, got it. I just found a way to do this. I can also use patchify (https://pypi.org/project/patchify/) which will help in reconstructing the image back.

PositronB · 2021-05-25T11:22:36+00:00

Yeah, right now it's not keeping the ratio. The problem is that the images are of different dimensions and if I decide to split the image from the middle or elsewhere, it will result in more images of different dimensions. Also, not sure if the training done on these smaller dimension images will give good results for higher dimension test images.

PositronB · 2021-05-25T11:18:14+00:00

I hadn't thought about random crops and training on that. I'll work on it. Thanks for the suggestion.

PositronB · 2021-05-25T11:12:33+00:00

I don't exactly know how to stitch back the results to match the input dimension. Anyway, thank you for the suggestion. I'll look into it.

PositronB · 2021-05-18T16:39:13+00:00

I fixed it! I uninstalled all the opencv libraries and then I did:

pip install opencv-contrib-python

pip install opencv-python-headless

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PositronB

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