Roboflow Annotation for YOLO

Question

We are using YOLO for object detection in satellite images to detect greenhouses. I'm annotating images through Roboflow. I've downloaded satellite images with different zoom levels. (zoom level means some of them are close and some of them are far away from the greenhouses).

I'm annotating images with different classes relevant to different features.

**My question is **when I'm annotating the images for several zoom levels for the same location, is it going to help the model for better prediction, or is it make the model confused in training (When we manually annotate the images, with different zoom level, annotations can have deviations from one to another)?

Our idea in the first place is to, have several zoom images to train the model so we can have a dataset with a wide variety.

My idea is to have a wide range of dataset samples so that the model would be able to learn more patterns from the dataset.

I'm expecting the model to detect greenhouses, when we input the images with different zoom level