To start with, visit the Teachable Machine page on your desktop or laptop (not the Pi--it's too slow).
Click Get Started, then choose Image Project from the first screen, and you'll be presented with this empty project screen:
Now it's ready for you to input samples. Before you start, have a look at the guidelines for choosing and capturing samples below.
Now you need to find example images that include the objects you want to recognize. This can be the both the most important and most time-consuming part of retraining a machine learning model, so choose wisely!
Here are some tips for choosing example images:
- Choose realistic images. Your model won't behave predictably in scenarios it hasn't seen before.
- Choose varied images. It's really important that the only thing in common between the images is the thing you want to detect. As an example, if all of the images in one category have a blue background, the model might simply learn that a blue background indicates that category.
- Choose representative images. Make sure you include images that show all different angles of the object you'd like to recognize.
- Include an "empty" category. Try including a category that the machine can select when it isn't confident in any of the choices. This should have as much background variation as possible, and shouldn't include any objects you want to recognize.