Computer Vision is not my field, and I prefer to use experts rather than re-invent the wheel.

However, since I do not believe in re-inventing the wheel, I chose some friends for the journey. FriendsĬomputer Vision, Deep Learning, and Machine Learning are not new topics for me. Let’s meet the friends first then discuss how I used Yolo3 in my project. At least that is what I have been told by tech gurus for years. I am just a Finance guy at the end of the day. I needed help from some friends with Yolo3 since Computer Vision is not my field. That leaves me with Yolo3 and friends, and indeed that is fitting. We have discussed MotionEyeOs already in the column, so I propose to skip most of the MotionEyeOs discussion and defer my earlier articles. Spyder3 seems a bit dated and slightly slower on the Mac M1 than I expected. I will only add that I use Anaconda on my Mac M1 Mini these days and I see no difficulties. Python really needs no introduction to the readers here on Towards Data Science. We had even made a very early chart to plot motion events. My earlier posts described the camera build and early scripts to review the data and make sense of passing traffic. Doing Data Science from Scratch is involved but incredibly great fun.Īs a catch-up, I previously built a camera and then explained the need to tune the motion detection device(s). This article will push on with the work and describe how I tooled up for an initial end to end exercise. I wanted to count the number of cars passing my house using Computer Vision and Motion Detection. If you have been reading my column here on Towards Data Science, you will know that I am on a mission.

Opencv python mac m1