Multiple classes present in the same image

Hi,
I have a problem regarding labeling of images containing instances from multiple classes I want to detect.

Say that I want to train a model to detect "guitars" and "human faces" in pictures.
I download images specifying the 2 classes, and I got (say 1K) images for each class, with the corresponding annotations for bounding boxes.
The problem is that, for every folder of images, only one class is annotated.

So, in the "human face" folder, I have 1000 images, and faces are labelled in every picture.
On the other hand, in the "guitar" folder, I have 1000 images with labelled guitars...however, as you can imagine, in most of the pictures of guitars there are also people, but their faces are not annotated.

At this point, I can't use them for training as they are, because all the faces in the "guitar" images are not labeled as such, and it would provide lots of false negatives to the model.
I tried using the multiclasses argument:

`python3 main.py downloader --classes Guitar Human_face --type_csv train --limit 1000 --multiclasses 1`

and it's the same, the images and annotations are downloaded in the same folder, but they are always separated per class.

Am I doing anything wrong here? Is there a way to download images with labels for all the classes I'm interested in?