YOLO v3 anchors for traffic sign detection

The creators of YOLO v3 advice to regenerate “anchors” if you retrain YOLO for your own dataset. Here I describe what are anchors, how to generate them and also give specific anchor values for traffic sign detection problem.

bicycles prohibited traffic sign

(If you need the anchors for training of traffic sign detection on 16:9 aspect ratio images, scroll down to the end of the post)

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Birdsong.report B1 Model Classification Quality

Here are some important notices about the classification quality of B1 model currently deployed at (birdsong.report)

I made per class classification quality analysis (don’t know why I did not do it before!) and the results are both impressive and distressing.
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My bird song classifier

In this post I describe the neural network architecture that I try as a bird song classifier.

Intro

When I first came up with an idea of building a bird song classifier I started to google for the training dataset.
I found xeno-canto.org and the first thing that caught my attention was spectrograms.
spectorgram
(Sepctrogram is visual representation of how spectrum evolves through time. The vertical axis reflects frequency, the horizontal represents time. Bright pixels on the spectrogram indicate that for this particular time there is a signal of this particular frequency)

Well, spectrograms are ideal for visual pattern matching!
Why do I need to analyse sound when we have such expressive visual patterns of songs? That was my thoughts.
I decided to train neural net to classify spectrograms.

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