@@ -33,7 +33,7 @@ The new version of the dataset contains images from the 12th to 20th centuries i
## Steps
First you need to prepare two datasets. One small with the image-level annotations of classes which you plan to extend or add to the dataset, the second one - big non-annotated dataset from which we collect and annotate images on object level using proposed approach.
Next you need to train YOLO model using the original dataset which you want to extend, calculate objectnesses of the objects for the images from the big non-annotated dataset, using OWL-ViT2, create index file for the objectnesses using ANNOY.
Next you need to train YOLO model using the original dataset which you want to extend, calculate objectnesses of the objects for the images from the big non-annotated dataset, using OWL-ViT2, create index file for the objectnesses using ANNOY. Next, you need to annotate data on object level using create_owl_dataset.py. After that, annotate other objects using finetuned YOLO model using annotate_with_yolo.py.
To reproduce our steps you need finetuned on the original DEArt dataset YOLO model, file with calculated objectnesses for the images from Wikiart dataset and ANNOY index. These files are available upon a request.
