CoreML - Image Classifier vs Object Detection

Question

I was wondering, which would be better for the following:

I want to create a model to help distinct car models, take the Mercedes C250 (2014) and Mercedes C63 (2014) as an example.

I understand, object helps to identify multiple well... objects in a given image, however, looking at a tutorial online and seeing how IBM cloud can allow you to annotate such specifics say the badge on the car, certain detailing etc. Would an object detection work better for me as opposed to just an image classifier?

I understand, the more data that is fed, the better the results, but in a general sense, what should be the approach? Image classifier or object detection? Or maybe something else? I've used and trained multiple image classifiers but I am not happy at all with the results.

Any help or suggestions would be much appreciated.

Answer 1

Object detection better because simple image classifier broke if you have more than one different cars at one photo.