Clustering of unlabeled ship images I want to create a ship detection classifier from a dataset that is formed by 4000 photos(3072*2048).

But the dataset  that i currently have is not labeled  so i can feed it to a cnn.So i want to cluster this dataset to 2 labels(or 2 directories) ship and no_ship.I tried running k-means but the results were dissapointing.Is some other more functional  way to do this?
In addition to the answers provided, you can:
1.) Train jointly a CNN (or Autoencoder) with clustering on your data. (DCN, kmeansNet,..)
2.) Pretrain a CNN using self-supervision on your data. (Have a look into the vast self-supervision literature, e.g. this work).
3.) Use an alternating scheme to train a CNN classifier on soft-labels provided by a clustering algorithm, e.g k-means (e.g. this work).