Hello !
Yes you can ! The easiest/fastest way according to me is to use a generalist pretrained image model (ImageNet, Vision Transformers…) and apply them on you images one by one. After that, you aim at getting one single embedding per image (depending on the model you can get it differently).
Those vectors can be later used to fuel a clustering model such as a DBSCAN or a KMEANS, this would give you clusters of image that are, according to the model, close in the representation space.
Warning : in the clustering, use the cosine distance rather than the euclidean one.
Based on the clusters, you can create your files !