text_queries = ["hat", "book", "sunglasses", "camera"]
inputs = processor(text=text_queries, images=im, return_tensors="pt")

Pass the inputs through the model, post-process, and visualize the results. Since the image processor resized images before
feeding them to the model, you need to use the [~OwlViTImageProcessor.post_process_object_detection] method to make sure the predicted bounding
boxes have the correct coordinates relative to the original image: