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komatsu

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Collection of open source computer vision algorithms

openmmlab.com
1 points·by komatsu·3 jaar geleden·1 comments

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komatsu
·2 jaar geleden·discuss
Taking antibiotics after every random bite is overkill. Antibiotics overuse is a serious issue for your body and for the general antibiotics resistance as well.

When the tick is attached less than 24 hours it won't transmit Lyme disease according to the CDC. I check myself every evening after outdoor activities, remove 10-20 ticks every year and knock-knock never had Lyme disease yet.

I wasn't aware of the permethrin effectiveness though. Thanks for letting us know.
komatsu
·3 jaar geleden·discuss
I can highly recommend the author. His last book "Computer Vision: Models, Learning, and Inference" is very readable, approaches the matter from unorthodox viewpoints + includes lot of excellent figures supporting the text. I'm buying this on paper!
komatsu
·3 jaar geleden·discuss
The code is mostly licensed under the permissive Apache 2.0 license. The project is probably financed by SenseTime, but it's not clearly stated anywhere.
komatsu
·3 jaar geleden·discuss
You could use the front TrueDepth sensor that is behind FaceID unlocking. You will get quite detailed RGB + depth data. It could possibly capture even the subtle movements of upper chest.

see Steffen Urban, Thomas Lindemeier, David Dobbelstein, Matthias Haenel, "On the Issues of TrueDepth Sensor Data for Computer Vision Tasks Across Different iPad Generations" and Andreas Breitbarth, Timothy Schardt, Cosima Kind, Julia Brinkmann, Paul-Gerald Dittrich, Gunther Notni, "Measurement accuracy and dependence on external influences of the iPhone X TrueDepth sensor".
komatsu
·4 jaar geleden·discuss
Otsu's method finds a single threshold value in an adaptive way. This can't solve a scanned document thresholding problem.

btw: The iOS Notes app has quite a capable document scanning tool. It's cleverly hidden though.
komatsu
·4 jaar geleden·discuss
AI and ML: Simon J.D. Prince; Computer Vision: Models, Learning, and Inference. Thorough book with unorthodox explanations and great figures. The book is very pleasant to read. I'm eagerly awaiting new book on Deep Learning from the same author.