Thanks for the question, wenhaowang.
Resizing images once as part of preprocessing to get consistent image sizes is allowed, since this is a basic requirement for many CV techniques.
Any form of augmentation is allowed during inference. For example, you could run inference on multiple augmentations of a single image and aggregate the results for that image independently of other images.
Augmentation (including resizing or cropping) for training purposes is only allowed on the training set, not the reference or query sets.
I hope this helps.
From the competition rules on augmenting:
- “Augmenting” images refers to applying a transformation to an image to generate a new image, such as the manner in which the query set images were derived from the reference set images.
- Augmenting reference images is permitted in the inference process of generating embeddings and matching scores, so long as each reference image is used independently without any interaction with other reference images. Use of augmented reference images for any other reason, including model training, is prohibited.