Create custom detection model - Image Object Detection

Question

I have some questions about object detections in images/videos.

I tried this tutorial with success: Train Object Detection AI with 6 lines of code

In this tutorial, we train a model to detect hololens. If I wanted to detect cars, I need to train a new model.

My question is: can I take my actual model (hololens) and make it detect hololens and cars?

In the end, I want to have one file (model) that detects all the objects that I put it to train. I will put a directory of 'n' images, and the model will try to detect everything it's trained to detect and return the name of the objects detected.

Sorry my bad english!!

Answer 1

Yes, you can train your model on any number of object classes. The tutorial is based on YOLOV3 which is one of the state-of-the-art object detection models which is fast enough to be used in real-time and videos. On the page you mentioned, in step 1 it explains how to prepare and annotate your dataset. Your data can have many categories of objects (like cars, hololens, etc) but you need to set this number in before training. Also, in the annotation step (giving label to the objects) you should assign the right names to the objects.

There is a link on this page that explains how to prepare your own data: Object Detection Training — Preparing your custom dataset

If the data is already prepared make sure it is in Pascal Voc format as it is necessary to be consistent with the model you are using. In the end, you only need one model to detect all kinds of objects. The accuracy depends on the number of iterations, the number of objects in each class, variety in shape, size, color, angle, etc of the objects and so on.