Real-Time Road Sign Detection with YOLOv5 - Data Collection, Labelling and Preprocessing

Data Collection, Labelling and Preprocessing

David Landup
David Landup

Let's go ahead and get to the crux of the project. Data collection, labelling and preprocessing.

Object detection is a specialized application of computer vision, and typically, you'll need to detect something specific for a niche you're working in, such as the unique anomalies that can occur in a specific toy factory, on the line 25.

Each dataset will be relatively unique, so it'll be harder to find datasets to pre-train on, but not impossible. Transferring something is better than transferring nothing. You might be lucky enough that a team has gone out of their way to label the data for you and provide you with the clean files to work with, so you can call the train.py script and everything works!

Data Collection

More commonly, you'll be collecting your own data and labelling it yourself. Since local traffic signs will always be at least a tiny bit different (their frequency, positions and style) between countries - this is a great time for a little excercise! If you own a car, attach a phone to act as a dash cam, and record a few minutes of representative driving through your neighborhood. If you don't own a car, kindly ask a public bus driver to stand in the front to record. If all else fails, download a dashcam video from the internet.

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