Creating a dataset of images for object detection for extremely specific task

Question

Even though I am quite familiar with the concepts of Machine Learning & Deep Learning, I never needed to create my own dataset before.

Now, for my thesis, I have to create my own dataset with images of an object that there are no datasets available on the internet(just assume that this is ground-truth).

I have limited computational power so I want to use YOLO, SSD or efficientdet.

Do I need to go over every single image I have in my dataset by my human eyes and create bounding box center coordinates and dimensions to log them with their labels?

Thanks

Answer 1

Yes, you will need to do that.

At the same time, though the task is niche, you could benefit from the concept of transfer learning. That is, you can use a pre-trained backbone in order to help your model to learn faster/achieve better results/need fewer annotations example, but you will still need to annotate the new dataset on your own.

You can use software such as LabelBox, as a starting point, it is very good since it allows you to output the format in Pascal(VOC) format, YOLO and COCO format, so it is a matter of choice/what is more suitable for you.