Labelling my own images

What you also could do, if there is a dataset, which is similar to your problem. You can use that to prelabel your own dataset, by using a network which was trained on that. And then you only need to check if your labels are correct, which is quicker.

You can label them manually with software labelImg for .xml and .txt files

Please check a basic tutorial on computer vision + tensorflow. PyImageSearch got plenty of free tutorials on different types of models you can train from scratch using TF.

Lacking details, most likely you have to draw masks for each image. This is a tedious process, so it is normal to use already labeled images to create the masks

I use Labeling for labelling datasets: https://github.com/tzutalin/labelImg

Make sure you label them using the right format. I think pascal VOC xml files are the most common but YOLOnet takes a different file type so make sure you use the correct one.

I’m assuming you want a simple solution. Put them in separate folders. That’s the simple process of labeling them that tensorflow makes use of in many cases.

Thanks for all of your input! I found this thread on stack: https://stackoverflow.com/questions/37340129/tensorflow-training-on-my-own-image

I will try this solution and also what you suggested with labelImg software. I have collected my own images and uploaded them to Kaggle, seems to be the easiest way to work with my images, as everything is cloud based.