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I think the author used Yolov5 to detect cars and their own method for counting them. Counting requires tracking object instances, which Yolo doesn't do.

He rant it every 60 seconds, so I don't think he was too concerned about tracking instances. And it doesn't really matter for purposes of classifying traffic levels.

Counting the different vehicles to boot strap it and have it start saving training images into the categories so that a new model could be trained against those images, and not rely on object detection to create new training data or power that app.

For the night images, I would imagine just number of red pixels would give a roughly accurate count which could be converted into "high" or "low"