How do you restrict the objects of a COCO dataset for retraining a tensorflow model?

The application that I make only needs to detect people.

The COCO dataset contains many people. I have used the fiftyone downloader to download the dataset with the tag of ‘persons’. However, this still downloads the label data for every other class in the image. It simply restricts the images to ones which contain a person.

So i’m training an SSD model from the model zoo. I’m training it from a checkpoint. How can I tell it to only detect instances of a person?

Is it simply a matter of removing everything from the label map except for:

item { name: "person", id: 50, display_name: "person" } 

Bare in mind, this is after ive already converted the records to .tfrecord (done via roboflow). Is there something I should do before converting to tfrecord?

I’m completely new to all this.

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